[{"data":1,"prerenderedAt":828},["ShallowReactive",2],{"tags-autonomous-driving":3,"tag-posts-autonomous-driving":125},[4,11,19,26,32,40,47,54,62,69,76,83,89,97,105,112,119],{"id":5,"tag":6,"url":7,"list_order":5,"tag_title":8,"tag_description":9,"tag_image":10,"is_visible":5},1,"Amnon Shashua","amnon-shashua","Mobileye CEO and founder Prof. Amnon Shashua","Read the latest news and updates about Professor Amnon Shashua, the Chief Executive Officer and founder of Mobileye.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fea37d7e7751aae1f5f2e8d70c10c4cd1_1711444846898.jpg",{"id":12,"tag":13,"url":14,"list_order":15,"tag_title":16,"tag_description":17,"tag_image":18,"is_visible":5},4,"ADAS","adas",2,"Advanced Driver-Asssistance Systems from Mobileye","Read about assisted-driving technologies from Mobileye, the pioneering market leader in computer vision for advanced driver-assistance systems.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F36fcc73cd14c1cb4528f155e534bcd24_1710330031175.jpg",{"id":20,"tag":21,"url":22,"list_order":20,"tag_title":23,"tag_description":24,"tag_image":25,"is_visible":5},3,"Autonomous Driving","autonomous-driving","Autonomous Driving Technologies from Mobileye","Discover the full range of innovative advancements, groundbreaking technologies, and comprehensive solutions developed by Mobileye for autonomous vehi","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd68043f24c36c755b43d169bddaef49f_1710330004977.jpg",{"id":15,"tag":27,"url":28,"list_order":12,"tag_title":29,"tag_description":30,"tag_image":31,"is_visible":5},"AV Safety","av-safety","RSS™ and Autonomous Vehicle Safety at Mobileye","Delve into the latest updates and information about autonomous-vehicle safety and the Responsibility-Sensitive Safety™ model (RSS™) from Mobileye.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1a93aad27f5322b98336318873549b35_1710329987351.jpg",{"id":33,"tag":34,"url":35,"list_order":36,"tag_title":37,"tag_description":38,"tag_image":39,"is_visible":5},6,"Driverless MaaS","driverless-maas",5,"Driverless Mobility-as-a-Service from Mobileye","Dive into the technologies Mobileye develops to enable autonomous Mobility-as-a-Service solutions delivering self-driving mobility on demand.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa04eac1da266c8dd0caf775a243c6ff2_1716967989684.jpg",{"id":41,"tag":42,"url":43,"list_order":33,"tag_title":44,"tag_description":45,"tag_image":46,"is_visible":5},7,"Mapping & REM","mapping-rem","REM™ mapping technology from Mobileye","Discover the latest about Road Experience Management™ (REM™), Mobileye's innovative crowdsourced cloud mapping solution for assisted and autonomous dr","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd8847e0a8281f0cf9cb0f8bc2c051b1e_1716968001971.jpg",{"id":48,"tag":49,"url":50,"list_order":41,"tag_title":51,"tag_description":52,"tag_image":53,"is_visible":5},12,"Mobileye Inside","mobileye-inside","The latest about vehicles with Mobileye technology inside","Take a look under the hood at the latest vehicles incorporating the groundbreaking assisted and autonomous driving technologies from Mobileye.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe8b350759a9f7e7ca5c521f0866b9a48_1716968050502.jpg",{"id":55,"tag":56,"url":57,"list_order":58,"tag_title":59,"tag_description":60,"tag_image":61,"is_visible":5},9,"Opinion","opinion",8,"Opinion pieces from Mobileye Leadership","Read opinion pieces and editorials from the thought leaders at the helm of Mobileye, the company driving the autonomous vehicle evolution.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1de50bef1e21d144583a09eba0cc23ff_1716968025874.jpg",{"id":63,"tag":64,"url":65,"list_order":55,"tag_title":66,"tag_description":67,"tag_image":68,"is_visible":5},13,"Industry","industry","Updates about the automotive tech industry from Mobileye","Read the newest updates and insights about the industry from Mobileye, a leading developer and supplier of automotive technologies.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F616c61e1687b24b92c10c22ffddc0d3f_1716968063749.jpg",{"id":36,"tag":70,"url":71,"list_order":72,"tag_title":73,"tag_description":74,"tag_image":75,"is_visible":5},"Awards","awards",10,"Awards & Honors at Mobileye","Mobileye is honored to be recognized as a leader in assisted and autonomous driving technologies. Read about the awards and citations we've received.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fcbe44f82e8943ecb87748a0b21769a79_1716967974564.jpg",{"id":77,"tag":78,"url":79,"list_order":77,"tag_title":80,"tag_description":81,"tag_image":82,"is_visible":5},11,"Events","events","Events & Conferences at Mobileye","Find out about conferences, trade shows, and other events where Mobileye has showcased the innovations creating the autonomous driving future today. ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F091d61264ea4fdabfab5061ac817b098_1716968037984.jpg",{"id":58,"tag":84,"url":85,"list_order":48,"tag_title":86,"tag_description":87,"tag_image":88,"is_visible":5},"Video","video","Videos about Mobileye","Watch videos about Mobileye and our groundbreaking technologies and solutions that are driving the evolution from assisted to autonomous driving.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Facab36f96b5bf20ca9f7898eea8595c9_1716968015561.jpg",{"id":90,"tag":91,"url":92,"list_order":63,"tag_title":93,"tag_description":94,"tag_image":95,"is_visible":96},15,"Press Kit","press-kit","Press kits and media information from Mobileye","Find the latest press kits, media information, and other assets for journalists from Mobileye, the company driving the autonomous vehicle evolution.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcorporate\u002Fsocial\u002Fabout.jpg",0,{"id":98,"tag":99,"url":100,"list_order":101,"tag_title":102,"tag_description":103,"tag_image":104,"is_visible":96},16,"News","news",14,"News updates from Mobileye","Read the latest news from Mobileye, the innovative and pioneering developer and supplier of assisted and autonomous driving technologies.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc14e966bdd3a7bc6585a879ca05b6714_1716968104360.jpg",{"id":106,"tag":107,"url":108,"list_order":90,"tag_title":109,"tag_description":110,"tag_image":111,"is_visible":5},17,"Financial","financial","Financial updates from Mobileye [Nasdaq: MBLY]","Receive the updates on the financial performance and quarterly results of Mobileye, listed on Nasdaq stock exchange under the ticker symbol MBLY.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3bd26e0f4e9f88d3184254ab9d601fe1_1716968119194.jpg",{"id":113,"tag":114,"url":115,"list_order":98,"tag_title":116,"tag_description":117,"tag_image":118,"is_visible":5},18,"From our CEO","from-our-ceo","From the Desk of Mobileye CEO & Founder Prof. Amnon Shashua","Messages, editorials, and videos communicated directly from the mind and desk of Mobileye CEO and founder Professor Amnon Shashua.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd0b71dedc5a444b7ecf4959a28b5e4c5_1716968130886.jpg",{"id":120,"tag":121,"url":122,"list_order":106,"tag_title":123,"tag_description":124,"tag_image":61,"is_visible":5},19,"Physical AI","physical-ai","Mobileye Blog | Physical AI","Read the latest news and updates about Mobileye's Physical AI technologies",[126,139,150,160,170,180,190,200,210,220,230,240,250,260,271,281,291,301,311,321,331,342,352,361,371,381,391,401,411,421,431,441,451,461,471,481,491,501,511,520,530,540,550,560,570,580,590,600,610,620,630,640,650,660,670,680,691,701,711,721,731,740,750,760,770,780,790,800,809,818],{"id":127,"type":100,"url":128,"title":129,"description":130,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":130,"image":133,"img_alt":134,"content":135,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":5,"publish_date":137,"tags":138},329,"mobileye-to-establish-vertically-integrated-robotaxi-business","Mobileye 将打造垂直整合Robotaxi业务","全新业务布局突破原有自动驾驶系统供应商定位，与现有车企、移动出行合作项目形成互补","","en","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F86fdfc495d3212c3c26221fbe4f90e66_1781548502451.webp","Mobileye 拟推出的Robotaxi服务概念示意图。","\u003Cp>\u003Cstrong>中国上海，2026年6月16日\u003C\u002Fstrong> — Mobileye 今日宣布，计划进一步拓展自动驾驶出租车（Robotaxi）业务版图，从提供自动驾驶技术延伸至自主运营自动驾驶网约车服务。该新项目计划于2027年率先落地美国一座城市，标志着Mobileye战略的重要升级。届时，Mobileye将整合行业领先自动驾驶技术、车队运营、乘客出行服务与出行管理能力，打造垂直整合解决方案。这一新业务是在Mobileye现有商业模式基础上的进一步拓展 —— Mobileye将继续作为自动驾驶技术供应商，为全球汽车制造商和出行服务提供商提供解决方案，在持续为客户部署提供支持的同时，增设全新运营板块。\u003C\u002Fp>\n\u003Cp>目前 Mobileye Drive 作为独立自动驾驶系统，正整合进合作伙伴项目。根据新举措的规划，Mobileye将打通Robotaxi价值链，依托Mobileye Drive系统，整合旗下Moovit出行平台及消费端应用、多模式出行规划、自动驾驶运营调度、车队管理技术以及远程协助基础设施。\u003C\u002Fp>\n\u003Cp>这一新举措不会改变Mobileye继续向汽车制造商、出行运营商及其他客户提供Mobileye Drive的承诺。公司将自营Robotaxi业务视作互补市场化路径，其将有助于加速自动驾驶落地部署，沉淀一线运营经验，并进一步验证Mobileye Drive平台的规模化应用能力。公司计划客户合作项目与自有运营车队双线同步推进。\u003C\u002Fp>\n\u003Cp>Mobileye规划首批部署约100台自动驾驶车辆，并于2027年开始在美国一座大都市投入运营。部署工作将分阶段推进，旨在验证完全无人驾驶条件下的整套运营模式。待首支车队稳定运营后，公司还计划大幅扩大业务规模，目标未来五年内将车队规模扩展至约17,000辆。\u003C\u002Fp>\n\u003Cp>Mobileye创始人兼首席执行官Amnon Shashua教授表示：“Robotaxi领域的变革才刚刚起步，其重塑全球出行方式的潜力仍在持续增长。随着自动驾驶出行赛道热度攀升，行业高度依赖为数不多的技术供应商与商业模式。而我们认为，可以开拓全新的发展路径，依托深厚的自动驾驶技术积淀、强大的产业合作生态、以及覆盖整个出行体系的成熟落地能力，构建差异化布局。 二十余年来，Mobileye持续深耕自动驾驶底层技术研发。如今我们迈出了新的重要一步：自研技术叠加自主运营，开创一套可实现财务层面规模化扩展、跨区域复制的全球化Robotaxi业务。我们计划于2026年底前在美国举办资本市场日活动，届时将分享更多有关商业化、技术及运营方面的详细信息。”\u003C\u002Fp>\n\u003Cp>为完善端到端自动驾驶平台，Mobileye将与自动驾驶整车平台厂商、车队运营商、车辆集成合作伙伴以及关键技术供应商展开合作。依托这套生态体系，Mobileye将通过统一的业务部门，统筹自有自动驾驶网约车服务的建设与运营。”\u003C\u002Fp>\n\u003Cp>Amnon Shashua教授补充道：“这一举措并非取代现有合作伙伴关系，而是在此基础上的延伸。我们将一如既往地通过Mobileye Drive赋能车企与出行服务商；与此同时，运营自有出行服务也有助于我们加快技术的市场采用，积累一手运营经验，充分释放自动驾驶出行的潜力。”\u003C\u002Fp>\n\u003Cp>Mobileye Drive沉淀25年以上的计算机视觉、地图、感知及自动驾驶技术研发经验，搭载最新复合人工智能架构，融合多类AI算法，配套严谨的安全框架，并通过工程化架构实现落地。全球已有超2.3亿台车辆搭载Mobileye技术，在业内积累了业内领先的真实道路经验。\u003C\u002Fp>\n\u003Cp>这一业务布局同时也拓展了Moovit原有的业务战略。Moovit致力于解决复杂城市环境下，用户查询、规划、使用公共交通服务的全流程需求。Moovit出行平台覆盖全球112个国家、3500余座城市，支持45种语言，服务超17亿用户。Moovit在消费者出行服务、多模式线路规划、用户运营和车队运营方面的专业知识，为公司在全球范围内扩展自动驾驶出行服务提供了关键基础。\u003C\u002Fp>\n\u003Cp>___________________________________\u003C\u002Fp>\n\u003Ch6>Mobileye (Nasdaq: MBLY) leads the mobility revolution with our autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in artificial intelligence, computer vision and integrated software and hardware. Since our founding in 1999, Mobileye has enabled the global adoption of advanced driver-assistance systems that save countless lives and reduce crashes, while pioneering groundbreaking technologies such as REM™ crowdsourced road intelligence, Imaging Radar and Compound AI. These technologies drive the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions at scale, and powering industry-leading ADAS products. Through 2025, more than 230 million vehicles worldwide have been built with Mobileye’s EyeQ technology inside. In 2026, Mobileye acquired Mentee Robotics to pursue the future of physical AI and humanoid robots. Since 2022, Mobileye has been listed independently from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\" target=\"_blank\" rel=\"noopener noreferrer\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>.\u003C\u002Fh6>\n\u003Ch6>“Mobileye,” the Mobileye logo and Mobileye product names are registered trademarks of Mobileye Global. All other marks are the property of their respective owners.\u003C\u002Fh6>\n\u003Ch6>Forward-Looking Statements\u003C\u002Fh6>\n\u003Ch6>This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Statements in this release that are not statements of historical fact are forward-looking statements and should be evaluated as such, including statements regarding Mobileye’s expansion into a full ownership of an autonomous ride-hailing business, and the impact and potential benefits to Mobileye’s business. These statements often include words such as “anticipate,” “expect,” “suggests,” “plan,” “believe,” “intend,” “estimates,” “targets,” “projects,” “should,” “could,” “would,” “may,” “will,” “forecast,” or the negative of these terms, and other similar expressions, although not all forward-looking statements contain these words. We base these forward-looking statements or projections, including Mobileye’s full-year guidance, on our current expectations, plans and assumptions that we have made in light of our experience in the industry, as well as our perceptions of historical trends, current conditions, expected future developments and other factors we believe are appropriate under the circumstances and at such time. You should understand that these statements are not guarantees of performance or results. The forward-looking statements and projections are subject to and involve risks, uncertainties and assumptions and you should not place undue reliance on these forward-looking statements or projections. Although we believe that these forward-looking statements and projections are based on reasonable assumptions at the time they are made, you should be aware that many factors could affect our actual financial results or results of operations and could cause actual results to differ materially from those expressed in the forward-looking statements and projections. Detailed information regarding these and other factors that could affect Mobileye’s business and results is included in Mobileye’s SEC filings, including the company’s Annual Report on Form 10-K for the year ended December 27, 2025, particularly in the section entitled “Item 1A. Risk Factors”. Copies of these filings may be obtained by visiting our Investor Relations website at \u003Ca href=\"http:\u002F\u002Fir.mobileye.com\" target=\"_blank\" rel=\"noopener noreferrer\">ir.mobileye.com\u003C\u002Fa> or the SEC’s website at \u003Ca href=\"http:\u002F\u002Fwww.sec.gov\" target=\"_blank\" rel=\"noopener noreferrer\">www.sec.gov\u003C\u002Fa>.\u003C\u002Fh6>\n\u003Cp> \u003C\u002Fp>",null,"2026-06-16T07:00:00.000Z",[99,6,34,64,21],{"id":140,"type":141,"url":142,"title":143,"description":144,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":144,"image":145,"img_alt":146,"content":147,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":148,"tags":149},326,"blog","diagnosing-the-long-tail-how-mobileye-turns-edge-cases-into-targeted-training","解析长尾挑战：Mobileye如何将边缘案例转化为定向训练","Meteor与Genario：运用语义推理、生成式AI以及结构化验证机制，系统性识别并解决自动驾驶偶发故障","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0facc17a677c97be9cb60f05bfa8c53b_1779867009807.webp","自动驾驶系统必须具备对罕见的边缘案例的检测、理解与响应能力，以确保其在真实驾驶环境中安全地实现规模化应用。","\u003Cp>随着自动驾驶汽车在全球范围内加速部署，其现有技术的性能瓶颈也日益凸显。近期，自动驾驶系统在面对非常规或不确定场景时，表现受限的新案例不断涌现。自动驾驶技术研发人员将这类工况称作“长尾效应” ——该术语源自于统计学指代难以建模的边缘案例。能否攻克长尾挑战，将直接决定自动驾驶的未来形态：是受限于严格地理围栏的区域性自动驾驶出租车（Robotaxi），还是兼具高适配性和广泛社会效益的自动驾驶。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fec6bd20a1c635032055aa6e37bf961d2_1779871783016.webp\" \u002F>自动驾驶汽车需要应对的各类非常规和罕见驾驶场景\u003C\u002Fp>\n\u003Cp>这类场景构成了“物理AI”的核心挑战：设备需要在变化无穷的真实驾驶环境中实现安全运行。尽管人类的驾驶环境绝大多数情况都是规律且常规的，但恰恰是那极少比例的异常事件，最严苛地考验着系统的智能与安全性，而在这些场景下，任何一次失误的代价都极其高昂。\u003C\u002Fp>\n\u003Cp>如需深入了解Mobileye技术方案背后的理论依据，可参阅Amnon Shashua教授与Shai Shalev-Shwartz教授发布的两篇配套技术博文：一篇深入剖析\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fwhy-learning-from-data-gets-harder-in-the-tail\u002F\">自动驾驶长尾效应\u003C\u002Fa>的数学结构，另一篇则详解本次全新发布的两大核心技术引擎\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fdriving-the-long-tail\u002F\">Meteor与Genario所依托的AI方法论\u003C\u002Fa>。\u003C\u002Fp>\n\u003Cp>凭借多年研发驾驶辅助与自动驾驶技术的经验，我们总结出一条关键结论：数据规模必不可少，但单靠它还远远不够。绝大多数驾驶数据包含常规驾驶行为、车道保持、交通信号灯识别，以及规律通行下车流等。当自动驾驶系统需要在罕见的边缘案例中持续优化表现、实现极低出错率时，仅靠采集更多数据和扩展计算规模将导致边际收益递减。\u003C\u002Fp>\n\u003Cp>行业需要更高效的规模化发展思路：打造能够识别关键故障、分析故障成因，并针对问题开展系统性训练的技术体系。\u003C\u002Fp>\n\u003Cp>依托全球超过 2.3 亿辆车辆、逾 25 年的部署经验，Mobileye多年来持续研发适配真实驾驶环境的技术架构与验证体系。作为持续演进的一部分，我们推出两款自研AI工具：Meteor（基于假设驱动型数据挖掘引擎）与Genario（定向场景仿真器）。他们协作工作旨在系统性解决长尾问题，并进一步助力自动驾驶在全球范围内规模化部署。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Meteor\u003C\u002Fstrong>\u003Cstrong>：将偶发故障转化为自动化结构化学习\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>目前多数自动驾驶系统仅将故障（失效事件）片段当作海量数据中彼此独立的零散案例。行业面临的难题，不仅在于发现故障，更要甄别出具备代表性、可复现的系统短板，并开展系统性优化。\u003C\u002Fp>\n\u003Cp>Meteor是Mobileye专为自动驾驶打造的多智能体AI数据分析平台。该平台汇聚了不同国家、天气、道路类型及交通环境下累计数百万小时的驾驶数据，依托先进的视觉语言模型（VLM）特征提取技术与自动化推理流程，实现视频数据的规模化处理与分析。\u003C\u002Fp>\n\u003Cp>Meteor并非针对几乎无法复现、不具备训练价值的“黑天鹅”事件，而是聚焦可复现故障：也就是系统反复出现判断偏差的场景，例如局部被遮挡的行人、行为意图模糊的道路使用者，或密集交通中的异常交互。\u003C\u002Fp>\n\u003Cp>该系统可全程模拟AI数据分析师的工作逻辑，自动识别故障事件、推导故障诱因、生成语义检索指令，在全网数据中检索同类场景。随后提取补充案例开展测试，判断是否存在系统性技术缺陷。一旦问题得到验证，Meteor会自动筛选高价值训练样本，优化模型在对应边缘案例中的表现。\u003C\u002Fp>\n\u003Cp>Meteor的独特优势在于：从故障发现、成因假设、场景检索、结果验证到训练样本生成，全流程实现自动化、规模化运转。该方法基于Mobileye复合人工智能架构搭建，将端到端AI模型作为组件融入整套系统，兼顾高透明度、可验证性与规模化安全能力。Mobileye不再需要被动等待罕见故障在数十亿公里的行驶里程中随机重现，而是能够主动识别有价值的学习盲区，在关键场景快速完成性能优化。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9d15a21f7311459ea8f27577f9bec744_1779869756952.webp\" \u002F>\u003C\u002Fh6>\n\u003Ch6>\u003Cstrong>第一步：故障发生与成因假设\u003C\u002Fstrong>\u003Cbr \u002F>Meteor会自动分析数百万小时的驾驶数据，以识别可复现故障，例如图中所示未检测到道路危险物。然后推导成因假设：当低矮、小体积或视觉上模糊的障碍物与路面融为一体、处于远距离、亦或缺乏强语义先验信息支持时，模型会降低其识别优先级。若障碍物外形特殊、画面对比度低、可视区域受限，或是在行驶路径中出现位置不合常规的危险物，系统的检测置信度也会随之下降。\u003C\u002Fh6>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc6b2f06feb5841ffadf8492ba156d3fd_1779869826634.webp\" \u002F>\u003C\u002Fp>\n\u003Ch6>\u003Cstrong>第二步：基于假设开展场景检索\u003C\u002Fstrong>\u003Cbr \u002F>Meteor生成语义检索指令，检索各类相关场景，以此验证或修正此前推导的故障成因假设。\u003C\u002Fh6>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F579ffd80676723695e447fc74b4a3da4_1779869863501.webp\" \u002F>\u003C\u002Fp>\n\u003Ch6>\u003Cstrong>第三步：结果验证与训练样本扩充\u003C\u002Fstrong>\u003Cbr \u002F>若检索结果印证故障假设，Meteor会从全网数据中筛选典型边缘案例，通过定向训练系统性优化并提升模型性能。\u003C\u002Fh6>\n\u003Ch3>\u003Cstrong>利用生成式\u003C\u002Fstrong>\u003Cstrong>AI\u003C\u002Fstrong>\u003Cstrong>拓展实景边界：认识\u003C\u002Fstrong>\u003Cstrong>Genario\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>一旦识别出有意义的故障模式，接下来的挑战就是规模化。真实驾驶环境中的边缘案例本就十分罕见，即便成功被发现，可用样本也往往寥寥无几。Genario的作用就是结合Meteor输出结果（具体故障类型、根本诱因及触发条件），生成定向训练数据。\u003C\u002Fp>\n\u003Cp>这款模拟器将故障案例重构为完全合成的、照片级逼真的驾驶情景，随后可以在无数个受控变量中进行扩展。同一个基础场景，可切换昼夜、雨雪、眩光、大雾等环境，同时调整道路布局、障碍物位置与能见度条件。通过细微的参数改动，即可打造全新的感知与决策测试场景。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cdiv class=\"videoEmbed customEmbed\">\u003Cvideo src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fvideos\u002Fc80e5cbc8630b14e0e0fd97011232fd8_1779878846833.mp4\" autoplay=\"autoplay\" loop=\"loop\" muted=\"\" width=\"300\" height=\"150\">\u003C\u002Fvideo>\u003C\u002Fdiv>\n\u003Ch6>\u003Cstrong>利用Genario生成全新的边缘案例\u003C\u002Fstrong>\u003Cbr \u002F>结合Meteor已验证的故障模式，Genario通过变换障碍物的形状、尺寸、位置与道路环境，可自动生成虚拟行车场景，全面拓宽定向训练的场景覆盖范围。\u003C\u002Fh6>\n\u003Cdiv class=\"videoEmbed customEmbed\">\u003C\u002Fdiv>\n\u003Cdiv class=\"videoEmbed customEmbed\">\u003Cvideo src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fvideos\u002Fa6ae32e9439885c4d427f1168878754f_1779878822645.mp4\" autoplay=\"autoplay\" loop=\"loop\" muted=\"\" width=\"300\" height=\"150\">\u003C\u002Fvideo>\u003C\u002Fdiv>\n\u003Ch6>\u003Cstrong>多维度扩展环境条件\u003C\u002Fstrong>\u003Cbr \u002F>Genario可系统性切换光照、天气、能见度等条件，模拟降雨、降雪、眩光、夜间、大雾等各类场景，让自动驾驶系统能够批量针对更广泛的真实边缘案例组合进行训练。\u003C\u002Fh6>\n\u003Cp>目标并非取代真实驾驶环境中的行车数据，而是对其形成有效补充，尤其适用于长尾场景。因为仅依靠真实路采数据，无法快速完成这类场景的全覆盖。依托Genario，我们可以主动对系统开展压力测试，模拟各类罕见却具备实际意义的事件，同时精准把控测试环境的各项条件。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>超越数据本身的自动驾驶规模化\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>如今行业已具备采集海量驾驶数据的能力，而下一轮技术突破的核心，是从这些数据中挖掘最具价值的学习机会，并进行智能化运用。\u003C\u002Fp>\n\u003Cp>正因如此，Mobileye打造了Meteor与Genario作为自动驾驶汽车开发的更广泛AI工具矩阵的重要部分，专门用于系统性攻克长尾挑战。两套系统融合前沿人工智能，同时依托面向规模化部署与安全性设计的架构，代表着Mobileye在自动驾驶系统研发与验证体系上的全新升级。\u003C\u002Fp>\n\u003Cp>随着自动驾驶在全球范围内规模化部署，能够解决长尾挑战的AI驱动型解决方案终将成为行业必备具。我们相信，技术进步不仅仅源自于数据与算力的叠加，更要在边缘案例的挖掘、理解与解决能力上，实现智能的规模化进阶。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F66522fe8fb32dcd3e9616e1f93b84713_1779867346779.webp\" \u002F>\u003Cspan class=\"caption\">Meteor界面\u003C\u002Fspan>\u003C\u002Fp>","2026-05-27T07:00:00.000Z",[21],{"id":151,"type":141,"url":152,"title":153,"description":154,"primary_tag":63,"author_name":131,"is_hidden":96,"lang":132,"meta_description":154,"image":155,"img_alt":156,"content":157,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":158,"tags":159},319,"what-are-some-common-misconceptions-in-the-av-industry","自动驾驶汽车（AV）行业常见认知误区解读","本推文旨在厘清这一快速发展的领域中某些认知误区","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F2f4915cf46ad5205cd886cc1e4b2da45_1771416842474.jpg","自动驾驶：三大核心真相","\u003Cp>从自动驾驶的技术路线之争、驾驶风格差异，到规模化量产可行性的争议，误导性观点极易快速传播。本文梳理了行业内常见的认知误区，力求为这个正在高速发展的领域正本清源。 \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>问题一：自动驾驶只采用一种单一的“正确”\u003C\u002Fstrong>\u003Cstrong>AI\u003C\u002Fstrong>\u003Cstrong>技术路线吗？\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"1\" data-aria-level=\"1\">\u003Cstrong>误区：自动驾驶汽车只采用一种单一的\u003C\u002Fstrong>\u003Cstrong>AI\u003C\u002Fstrong>\u003Cstrong>技术路线\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli>\u003Cstrong>事实：融合路线具备显著价值。\u003C\u002Fstrong>人工智能是某些高阶ADAS功能与自动驾驶技术的核心支撑。但随着技术演进，关于何种AI方案更适配自动驾驶的讨论也在持续深化。 \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>一派观点认为，AI需要使用直接的原始传感器输入与数据（如摄像头、雷达数据）来学习驾驶功能。端到端AI便是典型方法。该模式下，输入数据量越大，系统表现越优异。经过海量多元驾驶数据训练后，有望实现高度自适应且类人化的驾驶行为。但其决策过程难以进行解释、验证或修改，从而增加了在不同地区与监督框架下部署的复杂性。\u003C\u002Fp>\n\u003Cp>另一派则采用模块化，或复合人工智能（Compound AI）架构，将感知、决策和规划拆分为独立层级。这种方法以安全与可预测性为设计目标，基于冗余设计，更贴合法规要求。\u003C\u002Fp>\n\u003Cp>Mobileye的复合人工智能方案正是将自动驾驶拆解为定义清晰的各个组件，采用模块化设计、多源独立感知与层级冗余，为各独立任务匹配最优工具并针对性优化，最终实现AI行为可解释、可调校、可验证。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>问题二：所有自动驾驶汽车的驾驶行为都一样吗？\u003C\u002Fstrong> \u003C\u002Fh3>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"1\" data-aria-level=\"1\">\u003Cstrong>误区：各台自动驾驶汽车之间没有区别\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"3\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"2\" data-aria-level=\"1\">\u003Cstrong>事实：驾驶行为可定制、可调校，车企可借此体现品牌特质、地域驾驶风格与设计理念\u003C\u002Fstrong>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>自动驾驶汽车并非千篇一律，也不应同质化。安全性和遵守交通规则是自动驾驶的核心基础，而驾驶策略决定了车辆在现实场景中的具体行为表现。自动驾驶汽车以及驾驶员运动脱离的驾驶系统不仅需要具备基本的平稳停车等灯、高速领航等功能，更应承载品牌调性与当地的驾驶文化。\u003C\u002Fp>\n\u003Cp>车辆的驾驶风格能够且应当体现品牌标志性特征。例如，有些品牌可能设计频繁变道逻辑，以便提升通勤效率，有些则优先考虑平顺并线，或在拥堵路况下采用更果断的驾驶方式，同时严守法规要求并满足终端用户的期望。\u003C\u002Fp>\n\u003Cp>部分车企认为，必须自研自动驾驶技术与驾驶策略才能掌控驾乘体验。但此举可能导致新车型上市周期延后、投入成本攀升。Mobileye DXP™可弥补这一鸿沟，车企能够依托Mobileye的模块化、可扩展技术平台，精细调校驾乘体验核心维度，快速开发高阶功能。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>问题三：运动脱离驾驶功能是否仅搭载于豪华车型？\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"4\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"1\" data-aria-level=\"1\">\u003Cstrong>误区：高阶自动驾驶目前无法普及至日常家用车型\u003C\u002Fstrong>\u003Cstrong> \u003C\u002Fstrong>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"4\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"2\" data-aria-level=\"1\">\u003Cstrong>事实：运动脱离驾驶功能正快速向大众市场车型普及\u003C\u002Fstrong> \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>“运动脱离驾驶功能仅属于豪华车”的观念已日渐过时。随着ADAS技术迭代与用户需求提升，自动驾驶体验正下沉至量产平台，走向大众化，满足用户对安全、舒适与便捷的持续需求。\u003C\u002Fp>\n\u003Cp>据IDTechEx报告，\u003Ca href=\"https:\u002F\u002Fwww.idtechex.com\u002Fen\u002Fresearch-report\u002Fpassenger-car-adas-market-2025-2045-technology-market-analysis-and-forecasts\u002F1080\">\u003Cu>因豪华车与大众市场车型同步搭载，以及运动脱离驾驶功能普及的推动，\u003C\u002Fu>\u003C\u002Fa>2045年全球L2+功能市场规模有望达到179.8亿美元。此外，监管政策完善、产品成熟、计算机视觉与感技术进步、AI可扩展性与性能提升，也共同促进这一增长。\u003C\u002Fp>\n\u003Cp>支持在高速公路工况下，搭载运动脱离驾驶功能的量产车型正日益普及。\u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fnews\u002Fvolkswagen-group-cooperates-with-valeo-and-mobileye-to-enhance-driver-assistance-in-future-mqb-vehicles\u002F\">\u003Cu>Mobileye\u003C\u002Fu>\u003Cu>近期与大众汽车集团以及法雷奥的合作\u003C\u002Fu>\u003C\u002Fa>便是例证。基于EyeQ™6H芯片的Mobileye 环绕式 ADAS™平台可在指定高速公路路段实现特定条件下的运动脱离驾驶、障碍物检测、交通拥堵辅助等功能，以量产化的规模提供豪华级驾乘体验。\u003C\u002Fp>","2026-02-18T08:00:00.000Z",[21],{"id":161,"type":100,"url":162,"title":163,"description":164,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":164,"image":165,"img_alt":166,"content":167,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":168,"tags":169},314,"mobileye-to-acquire-mentee-robotics-to-accelerate-physical-ai-leadership","Mobileye将收购 Mentee Robotics以加速建立物理AI领域领先地位","该收购将汇聚全球顶尖AI人才并推动驾驶自动化与人形机器人全球规模化落地","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe6d126b4d74e0fce47e379c3fff057e6_1767710135503.jpg","Mobileye 与 Mentee Robotics","\u003Cp>美国拉斯维加斯，2026年1月6日 — Mobileye 今日宣布已就收购AI（人工智能）人形机器人公司Mentee Robotics（Mentee）达成最终协议。Mentee目前已进入其第三代垂直整合的人形机器人研发阶段。此次收购将Mobileye先进的AI技术和全球量产经验，与Mentee突破性的人形机器人平台和深厚的AI人才储备充分结合，意在打造一家横跨驾驶自动化与人形机器人两大变革性赛道的全球物理AI（Physical AI）领域领先企业。\u003C\u002Fp>\n\u003Cp>Mobileye的高等级驾驶自动化业务及其核心的组合辅助驾驶（ADAS）技术正呈现出强劲的发展态势，得益于此，公司未来八年的汽车业务收入预期将达245亿美元，较2023年1月时的预期增长超过40%。\u003Csup>1\u003C\u002Fsup>此次收购进一步拓展了Mobileye的业务版图，成为其向物理AI领域迈出的决定性一步——物理AI系统致力于理解情境、推理意图，与人类进行自然交互，在物理世界中安全高效地运行，同时实现经济上的可扩展性。历经过去数年的发展，Mobileye的驾驶自动化技术栈已从专注于目标驱动型的领航辅助驾驶功能，进阶至全局情境感知与意图感知的推理能力，为实现通用机器人在满足严苛安全要求的前提下，与人类的高效协同奠定了坚实基础。\u003C\u002Fp>\n\u003Cp>本次收购还将加速Mentee的商业化进程，预计在2026年内将启动首批客户现场概念验证部署，旨在实现无需远程操控的机器人自主运行，其规模化量产与商业化落地则计划于2028年完成。\u003C\u002Fp>\n\u003Cp>本次收购对价总额约为9亿美元（具体金额可能因相关调整而发生变动），其中包括约6.12亿美元现金及至多约2620 万股Mobileye A类普通股（具体股数将根据交割前 Mentee 期权的归属情况做相应调整）。上述金额并非最终金额，将根据股份购买协议条款进行调整。该交易尚需满足惯常交割条件，预计于2026年第一季度完成。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Mentee初创阶段成果斐然\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mentee成立四年以来，在人形机器人领域取得显著进展，设计出了具有成本效益、面向真实场景规模化部署的人形机器人平台。该平台采用自研软硬件设计，并基于人机示范指导、小样本学习及仿真优先式训练构建了AI架构。不同于依赖大规模真实场景数据采集或持续远程操控的系统，Mentee的技术路线致力于让机器人通过自然示范与意图提示逐步掌握新技能，在保障与人类和物体对象交互的安全性与可预测性的同时，实现成本与实用性之间的最优平衡。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>核心竞争力：快速学习能力、高性价比、强大实用性\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cimg style=\"float: right; margin-left: 20px;\" src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F127b18f2ac06dc118ee1f59837cd4167_1767711405382.png\" alt=\"Mentee Robotics is developing an AI-first, vertically integrated humanoid robot designed for real-world usefulness and adaptability.\" width=\"270\" height=\"431\" \u002F>\u003C\u002Fp>\n\u003Cp>Mentee人形机器人具备强大的开箱即用功能，包括先进的场景理解与自然指令执行能力的深度融合，无需远程操控的端到端自主任务处理，可靠的位置移动和导航，以及对刚性物体的安全操控能力。目前，其团队正加速推进“小样本泛化”技术研发，以确保机器人通过少量的人类示范，即可快速学习并执行新技能与新任务。这一能力将推动人形机器人在多类现实场景中快速部署，既可成为人力增效工具，也能作为协作伙伴与人类并肩作业。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>两大支柱构筑Mentee技术优势\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>Mentee可扩展性的AI优势:\u003C\u002Fstrong> Mentee平台依托两大核心AI支柱，构筑了坚实的技术壁垒:\u003Cbr \u002F>\n\u003Cul>\n\u003Cli>集成型AI解决方案：将先进的基础模型与基于强化学习的运动模型相结合；\u003C\u002Fli>\n\u003Cli>纯仿真训练：凭借突破性技术，大幅缩小Sim2Real（仿真到现实）的差距。Mentee 的方案减少了对大规模现实场景数据采集的依赖，通过仿真来高效地习得技能，加速技术规模化并实现成本效益。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli>\u003Cstrong>垂直整合硬件支撑规模化部署:\u003C\u002Fstrong> Mentee核心硬件与嵌入式软件均为自主研发，具体包括:\n\u003Cul>\n\u003Cli>专有执行器：实现卓越的扭矩密度与紧凑的结构设计；\u003C\u002Fli>\n\u003Cli>高精度电机驱动器：保障优异的控制性能与行为透明度；\u003C\u002Fli>\n\u003Cli>坚固的高实用性机械臂：搭载电机触觉传感技术，提升模块化程度并降低系统复杂度；\u003C\u002Fli>\n\u003Cli>热插拔电池：支持全天候不间断运行。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>深度垂直整合的模式不仅缩小了Sim2Real的技术鸿沟，保障24\u002F7全天候作业能力，还能满足多元场景应用需求，支持低成本量产。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>驾驶自动化与人形机器人技术的融合\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>驾驶自动化与人形机器人两大领域面临相同的底层挑战：在人类主导的物理世界中，实现可靠运行并展现实用价值。要想取得成功，必须满足严苛的性能要求，达到可验证的安全水平，在边缘计算平台上高效运行，并实现具备经济可行性的规模化部署。\u003C\u002Fp>\n\u003Cp>正因如此，两大领域均依赖一套共通的物理AI技术栈，涵盖多模态感知、环境建模、意图感知规划、精准控制、以及在不确定性情况下的决策制定。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa6cab3bf8701a75779ffd976269f0830_1767711531677.png\" alt=\"Two MenteeBots demonstrate stability, accuracy, and adaptive control transferring 32 boxes across multiple racks.\" width=\"1000\" height=\"561\" \u002F>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>收购\u003C\u002Fstrong>\u003Cstrong>Mentee\u003C\u002Fstrong>\u003Cstrong>以实现关键战略协同效应\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye对Mentee的收购预计将产生可观的技术协同效应，推动物理AI在机器人与驾驶自动化两大分支的长足发展。\u003C\u002Fp>\n\u003Cul>\n\u003Cli>加强驾驶自动化技术栈：Mentee在VLA（视觉-语言-动作）技术和基于创新Sim2Real迁移技术的大规模仿真方面的进展，与Mobileye的驾驶自动化技术栈高度互补。这些能力通过优化长尾场景泛化能力，加速适应新环境，提高研发效率并缩短验证周期，能够进一步强化驾驶自动化系统性能。\u003C\u002Fli>\n\u003Cli>引领人形机器人安全性提升：在动态日常环境中与人类和其他机械设备共同作业的人形机器人，需要超越反应式避障的可验证安全级别。不同于固定式自动化设备，人形机器人必须对人类行为、共享空间、可移动物体及脆弱环境进行实时推理，产出可预测且经得起验证的结果。Mobileye将其在驾驶自动化领域验证有效的“安全优先”理念引入人形机器人领域，包括责任敏感安全模型（RSS）等严谨的安全模型，在不确定情况下基于数学模型的决策机制，以及经过规模化验证的系统级冗余架构。这些技术共同构成了定义、验证和执行安全行为的基础，进而为人形机器人实现经济可行性，最终推动其大规模商业化部署构建所必需的信任度、可靠性与监管合规基础。\u003C\u002Fli>\n\u003Cli>加速商业化进程：Mobileye 在将先进技术推向市场方面积累了二十多年的专业经验。依托符合严苛安全标准的工具链与基础设施、AI训练基础设施，以及与高产能精密制造商的深度合作关系，其将加速推动人形机器人解决方案在全球工厂、仓储及工业环境中的部署。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>通过综合人形机器人与驾驶自动化领域的各项突破性技术，Mobileye与Mentee将在物理AI领域形成复合优势，实现技术进步的持续叠加与相互强化。\u003C\u002Fp>\n\u003Cp>Mobileye创始人、总裁兼首席执行官Amnon Shashua教授表示：“这一收购为机器人与汽车AI领域开启了新篇章，同时也标志着Mobileye 3.0 时代的起点。Mentee在人形机器人领域取得了突破性的成果，Mobileye则在驾驶自动化领域拥有深厚的技术积淀，并具备将先进的AI技术产品化的能力。双方的强强联合将使我们把握时代赋予的独特机遇，在全球范围内引领物理AI技术在机器人与驾驶自动化领域的演进。“\u003C\u002Fp>\n\u003Cp>Mentee Robotics首席执行官Lior Wolf教授表示：“我为Mentee的跨学科团队在短短四年内取得的成就感到无比自豪。我们致力于打造一个融合前沿AI与深度整合硬件的平台，让人形机器人在现实场景中真正发挥实用价值。与Mobileye携手，我们将获得无可比拟的AI基础设施与商业化经验支持，从而加速实现我们的使命，将具有可扩展性、高安全性、高性价比的人形机器人解决方案推向市场。”\u003C\u002Fp>\n\u003Cp>本次收购由独立董事组成的战略交易委员会及Mobileye最大股东英特尔公司提议，已获Mobileye董事会批准。根据Mobileye最新修订的公司章程，英特尔作为Mobileye唯一的B类股东，亦批准了此次收购。担任Mentee董事长、联合创始人及主要股东的Amnon Shashua教授已就本次交易相关表决事项予以回避。\u003C\u002Fp>\n\u003Cp>收购完成后，Mentee将作为Mobileye旗下独立事业部运营，在保持团队与业务连续性的同时，依托Mobileye先进的AI训练基础设施，加速其AI软硬件能力的整合。预计本次交易将使Mobileye 2026年运营费用小幅增加，增幅为低个位数百分比。\u003C\u002Fp>\n\u003Cp>Amnon Shashua教授将于2026年国际消费电子展（CES）上发表主题演讲，进一步阐述Mobileye在物理AI领域的愿景。演讲将在美国太平洋时间1月6日下午1:45 进行线上直播，直播结束后提供回放。\u003C\u002Fp>\n\u003Cp>有关本次收购最终协议的条款详情，请参阅Mobileye将就本次交易向美国证券交易委员会（SEC）提交的8-K报表。\u003C\u002Fp>\n\u003Cp>本次收购中，高盛公司担任Mobileye的财务顾问；EBN律师事务所（Erdinast Ben Nathan Toledano）以及美国达维律师事务所（Davis Polk and Wardwell LLP）分别担任Mobileye的以色列法律顾问与美国法律顾问；西博雷特律师事务所（Shibolet & Co.）和普衡律师事务所（Paul Hastings LLP）分别担任Mentee的以色列法律顾问与美国法律顾问。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 8pt;\">\u003Csup>1 \u003C\u002Fsup>所列期间内的Mobileye收入，乃基于当前及潜在原始设备制造商（OEM）在相关车型设计定点时所提供的未来产量预测估算得出。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>___________________________________\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">Mobileye (Nasdaq: MBLY) leads the mobility revolution with our autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in artificial intelligence, computer vision, mapping and integrated software and hardware. Since our founding in 1999, Mobileye has enabled the wide adoption of advanced driver-assistance systems that bolster driving safety, while pioneering such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety™ (RSS). These technologies drive the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions at scale, and powering industry-leading advanced driver-assistance systems. Through 2024, more than 200 million vehicles worldwide have been built with Mobileye’s EyeQ technology inside. Since 2022, Mobileye has been listed independently from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003Ca href=\"https:\u002F\u002Fcts.businesswire.com\u002Fct\u002FCT?id=smartlink&url=https%3A%2F%2Fwww.mobileye.com&esheet=54167879&newsitemid=20241217366044&lan=en-US&anchor=https%3A%2F%2Fwww.mobileye.com&index=7&md5=25e995ce7275b1a687baef28e2f033a3\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">“Mobileye,” the Mobileye logo and Mobileye product names are registered trademarks of Mobileye Global. All other marks are the property of their respective owners.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">\u003Cstrong>Forward-Looking Statements\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">Mobileye’s business outlook, guidance and other statements in this release that are not statements of historical fact, including statements about our beliefs and expectations, are forward-looking statements and should be evaluated as such. Forward-looking statements include expectations and information regarding the development of robotics and AI capabilities, the impact of robotics and AI development on Mobileye’s business, the impact of the transaction on Mobileye’s operating expenses, and descriptions of our future business plan and strategies. These statements often include words such as “anticipate,” “expect,” “suggests,” “plan,” “believe,” “intend,” “estimates,” “targets,” “projects,” “should,” “could,” “would,” “may,” “will,” “forecast,” or the negative of these terms, and other similar expressions, although not all forward-looking statements contain these words. We base these forward-looking statements or projections, on our current expectations, plans and assumptions that we have made in light of our experience in the industry, as well as our perceptions of historical trends, current conditions, expected future developments and other factors we believe are appropriate under the circumstances and at such time. You should understand that these statements are not guarantees of performance or results. The forward-looking statements and projections are subject to and involve risks, uncertainties and assumptions and you should not place undue reliance on these forward-looking statements or projections. Although we believe that these forward-looking statements and projections are based on reasonable assumptions at the time they are made, you should be aware that many factors could affect our actual financial results or results of operations and could cause actual results to differ materially from those expressed in the forward-looking statements and projections.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">Important factors that may materially affect such forward-looking statements and projections include the following: the robotics technology and industry may not develop as expected; further deterioration of macroeconomic conditions due to ongoing global economic and political uncertainty (as our current guidance assumes the estimated production and\u002For demand impact of current tariff conditions); future business, social and environmental performance, goals and measures; our anticipated growth prospects and trends in markets and industries relevant to our business; business and investment plans; expectations about our ability to maintain or enhance our leadership position in the markets in which we participate; future consumer demand and behavior, including expectations about excess inventory utilization by customers; our ability to effectively compete in the markets in which we operate; future products and technology, and the expected availability and benefits of such products and technology; development of regulatory frameworks for current and future technology; changes in regulation and trade policy, including increased tariffs, in regions in which we operate, including the U.S., Europe and China; projected cost and pricing trends; future production capacity and product supply; potential future benefits and competitive advantages associated with our technologies and architecture and the data we have accumulated; the future purchase, use and availability of products, components and services supplied by third parties, including third-party IP and manufacturing services; uncertain events or assumptions, including statements relating to our estimated vehicle production and market opportunity, potential production volumes associated with design wins and other characterizations of future events or circumstances; adverse conditions in Israel, including as a result of war and geopolitical conflict, which may affect our operations and may limit our ability to produce and sell our solutions; any disruption in our operations by the obligations of our personnel to perform military service as a result of current or future military actions involving Israel; availability, uses, sufficiency and cost of capital and capital resources, including expected returns to stockholders such as dividends, and the expected timing of future dividends; and tax- and accounting-related expectations.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">Detailed information regarding these and other factors that could affect Mobileye’s business and results is included in Mobileye’s SEC filings, including the company’s Annual Report on Form 10-K for the year ended December 28, 2024, particularly in the section entitled “Item 1A. Risk Factors”. Copies of these filings may be obtained by visiting our Investor Relations website at ir.mobileye.com or the SEC’s website at www.sec.gov.\u003C\u002Fspan>\u003C\u002Fp>","2026-01-06T08:00:00.000Z",[64,99,107,49,21],{"id":171,"type":141,"url":172,"title":173,"description":174,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":174,"image":175,"img_alt":176,"content":177,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":178,"tags":179},304,"level-3-autonomy-explained","L3级有条件自动驾驶解析及其对车企的意义","何为L3级有条件自动驾驶？实现该级别驾驶需满足哪些条件？本文将探讨为何L3级有条件自动驾驶正在成为车企的战略核心","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Feaf2ceb1613e6963bc54063be51a9ef2_1759148050677.jpg","AI生成图片","\u003Ch3>何为L3级有条件自动驾驶？\u003C\u002Fh3>\n\u003Cp>L3级有条件自动驾驶，即具备 “运动脱离\u002F视觉脱离”驾驶能力，是实现驾驶自动化跨越式发展的关键节点。根据美国汽车工程师学会（\u003Ca href=\"https:\u002F\u002Fwww.sae.org\u002Fstandards\u002Fj3016_202104-taxonomy-definitions-terms-related-driving-automation-systems-road-motor-vehicles\">SAE\u003C\u002Fa>）的定义，L3级属于“有条件自动驾驶”，车辆在特定条件下无需人工干预即可自主行驶，但仍要求驾驶员在必要时随时准备接管车辆。该级别可提供真正的“运动脱离\u002F视觉脱离”驾驶体验，但仅适用于地图精准、环境可控的场景，例如高速公路或低速的拥堵路况。\u003C\u002Fp>\n\u003Cp>在消费级驾驶自动化汽车领域，L3级是目前最受关注的阶段：它既能实现“运动脱离\u002F视觉脱离”驾驶能力，享有高端驾乘体验，又无需承担无人工干预的L4级完全自动驾驶系统的复杂性和高成本。\u003C\u002Fp>\n\u003Ch3>为何L3级有条件自动驾驶具有重要意义？\u003C\u002Fh3>\n\u003Cp>L3级是驾驶体验发生实质性转变的分水岭。尽管驾驶员仍需在必要时接管车辆，但驾驶体验不再局限于 “持续掌控车辆” 。这一阶段让驾驶员可以获得短暂的放松时刻，例如回头看看后排的孩子，或在漫长通勤途中稍作放空。从用户心理层面看，L3级标志着人与驾驶行为之间新关系的开端。\u003C\u002Fp>\n\u003Cp>从技术层面来看，L2级与L4级之间虽仅相差一个等级，但差异却极为显著：L2级属于较低级别的驾驶自动化形式，需要驾驶员全程监督与参与；L4级则可在特定区域内实现完全自主行驶，无需驾驶员参与和操控、承担责任，更无需进行任何人工干预。\u003C\u002Fp>\n\u003Ch3>实现L3级有条件自动驾驶需满足哪些条件？\u003C\u002Fh3>\n\u003Cp>推动L3级有条件自动驾驶大规模量产落地，需综合考虑多方面因素，其中两项核心要素尤为关键：\u003C\u002Fp>\n\u003Cp>第一是稳定可靠的技术体系。其核心是实现驾驶员与人工智能（AI）之间的平稳安全接管转换。一套成熟的L3级有条件自动驾驶系统需具备多维度能力，以确保接管过程可靠、人机协作顺畅。其中，很大一部分取决于芯片的计算性能，以及其在处理完整驾驶功能栈时的速度与效率，包括高级辅助驾驶系统（ADAS）、驾驶员监控系统（DMS）、传感器感知、定位技术、自动泊车、在线升级（OTA）等。除驾驶自动化核心技术的可靠性外，还有如下第二项关键因素同样不可或缺。\u003C\u002Fp>\n\u003Cp>第二项因素来自汽车生产之外的外部环境——监管框架。L3级有条件自动驾驶的落地依赖于多方协同构建的生态：监管机构、公共政策制定者、车企、保险公司等，以真实路况数据为支撑，共同打造适合 “运动脱离\u002F视觉脱离” 驾驶发展的体系。该框架不仅需覆盖道路通行法规，还需考虑驾驶自动化技术对驾驶员行为习惯的影响。目前，行业围绕责任划分、监管标准、保险体系等方面的政策正在逐步完善与协调，以最终获得公众信赖和认可，为规模化应用创造条件。\u003C\u002Fp>\n\u003Cp>随着路况数据的持续积累，针对不同情境的监管与责任框架将会逐渐明朗化——无论是通过建立混合责任模式，还是推出能够公平覆盖各方利益的全新保险产品。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F6dc3c49165df922bfbcb7509adac8357_1759149226755.png\" alt=\"\" width=\"600\" height=\"233\" \u002F>\u003C\u002Fh6>\n\u003Ch6>“推动L3级有条件自动驾驶大规模量产落地，需综合考虑多方面因素”\u003C\u002Fh6>\n\u003Ch3>车企为何要投入研发L3级有条件自动驾驶系统？\u003C\u002Fh3>\n\u003Cp>若驾驶自动化系统可兼容不同等级的驾驶辅助功能，车企便能稳步推进驾驶自动化技术的提升。依托合理的技术基础，单一系统即可通过集成不同数量的系统集成芯片（SoC）实现系列不同功能配置。\u003C\u002Fp>\n\u003Cp>目前，自适应巡航（ACC）、自动紧急制动（AEB）等L1级与L2级辅助驾驶功能已成为多数新车的标配，消费者既关注安全性也重视便利性，而车企则需寻求差异化竞争优势。因此，L3自然成为下一步自动化发展方向。借助L3级技术，车企可实现特定场景下的“视觉脱离”驾驶，灵活兼容L1、L2、L3功能，并为更高级别的驾驶自动化技术奠定基础。如今，随着核心技术逐步具备量产条件、监管框架日趋完善，越来越多车企开始筹备L3级系统的市场化落地，进一步推动了有条件自动驾驶的关注度升温。\u003C\u002Fp>\n\u003Ch3>车企需要怎样的L3级解决方案？\u003C\u002Fh3>\n\u003Cp>Mobileye推出的L3级解决方案Mobileye Chauffeur™有条件自动驾驶系统，可在所有常规道路类型中实现时速达80 mph (130 km\u002Fh) 的 “视觉脱离” 驾驶。\u003C\u002Fp>\n\u003Cp>这套复合技术栈*整合了多维度硬件与软件能力：包含11套摄像头、环视式雷达组和一颗前向激光雷达的传感器套件，3颗EyeQ™6H系统集成芯片（SoC）；以及由智能路网技术支持、持续更新的众源地图。部分车企的落地路径为：先通过专业的高级辅助驾驶系统（ADAS）供应商或技术服务商部署核心辅助驾驶系统，因为这些供应商具备实施此类系统的专业经验，可提供不同等级的驾驶自动化方案定制，再通过后续升级逐步提升驾驶自动化级别。这也正是当前汽车行业“可扩展架构”的核心价值所在。\u003C\u002Fp>\n\u003Ch3>未来发展方向\u003C\u002Fh3>\n\u003Cp>L3级有条件自动驾驶不仅是一项技术里程碑，更是汽车行业的战略转折点。它在不进入完全自动驾驶系统的复杂性的前提下，为创新提供了空间，为整车厂提供了一条可行路径——既能在当下提供高端、差异化的驾驶体验，又能为未来的发展打下坚实基础。借助Mobileye Chauffeur™等解决方案，“运动脱离\u002F视觉脱离”驾驶的落地不仅具备可行性，还能实现规模化应用与灵活适配，并且能够随着监管政策、技术迭代与消费者需求共同演进。\u003C\u002Fp>\n\u003Cp>深入了解Mobileye Chauffeur™技术，请点击\u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fsolutions\u002Fchauffeur\u002F\">此处\u003C\u002Fa>。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>*注：功能可用性与性能受多重因素影响，包括产品及车辆规格、使用手册、设计运行范围（ODD）及法律法规限制。必要时，驾驶员需保持专注并准备随时接管车辆。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-10-29T07:00:00.000Z",[21,64,27],{"id":181,"type":100,"url":182,"title":183,"description":184,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":184,"image":185,"img_alt":186,"content":187,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":5,"publish_date":188,"tags":189},296,"mobileye-imaging-radar-chosen-by-global-automaker-for-eyes-off-driving","全球头部车企选用Mobileye成像雷达实现“驾驶员视觉脱离”驾驶","该技术突破促成了Mobileye与新客户的首个定点项目，将于2028年投产","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F220438c14cca71db62021f1e474931b8_1748429636893.png","彩色点状图模拟Mobileye独家成像雷达生成的密集且精确数据。","\u003Cp>耶路撒冷，2025年5月28日 - 经过对Mobileye技术与竞品系统长达数年的评估，一家全球头部车企首次选择Mobileye成像雷达（Mobileye Imaging Radar™）作为其即将推出的私家车驾驶员“视觉脱离”和“运动脱离”驾驶自动化系统的关键组件。该客户计划自2028年起使用Mobileye的成像雷达，实现高速公路速度下SAE（国际自动机工程师学会） L3级驾驶自动化，在雾、雨等对于当前传感器而言具有挑战性的条件下，以及在远距离行车中，提供对车辆、行人和物体的卓越探测能力。\u003C\u002Fp>\n\u003Cp>Mobileye的4D成像雷达自2018年开始研发，旨在通过其在挑战性光线、环境和交通场景中的卓越感知能力，提供传感器冗余，以经济的成本弥补摄像头感知的不足，进而打造安全且可扩展的驾驶自动化系统，实现从高度自动驾驶出租车到消费级高等级驾驶自动化汽车的全场景覆盖。\u003C\u002Fp>\n\u003Cp>“新客户选择我们的成像雷达，是对我们为开发这款雷达所做的突破性工作的充分肯定，”Mobileye总裁兼首席执行官Amnon Shashua教授表示。“在认识到这种传感模态对驾驶自动化的重要性后，我们打造了行业领先的成像雷达，能够满足高等级驾驶自动化系统所需的安全性和精确性。”\u003C\u002Fp>\n\u003Cp>现有的汽车雷达可检测障碍物距离、水平方位和动态速度变化。而成像雷达则增加了“高度”这一维度。\u003C\u002Fp>\n\u003Cp>基于突破性的架构，新一代Mobileye成像雷达通过Mobileye自主设计的雷达处理器，对所有信号进行端到端的全数字化处理。目标是在环境感知方面提供前所未有的精确度、细节和可靠性，进而巩固Mobileye驾驶自动化技术的领先地位。\u003C\u002Fp>\n\u003Cp>Mobileye成像雷达的核心是Mobileye自主设计的雷达射频集成电路（RFIC）。这些先进组件具有卓越的信号传输灵活性，能够在宽频带范围内接收并采样完整雷达信号，同时保持低噪声水平，旨在支持高置信度的目标探测。\u003C\u002Fp>\n\u003Cp>这些RFIC被嵌入到一个独特的架构中，所有雷达信号由一颗独家的专用处理器进行采样和数字处理。该处理器拥有高达11 TOPS的超强计算能力，能以每秒20帧的高帧率处理超过1500个虚拟通道。庞大的天线阵列还提供了小于0.5度的卓越角分辨率、低至-40 dBc的超低旁瓣电平，以及高达100分贝的行业领先动态范围（其他汽车雷达仅60分贝）。\u003C\u002Fp>\n\u003Cp>这种设计有助于Mobileye成像雷达在复杂场景中检测到远处的小目标，即使附近有卡车或公共汽车等大型车辆。同时，Mobileye成像雷达也能精确探测远处的小型危险物，例如护栏附近的轮胎，这对于在时速超过75英里（130公里）的高速公路场景中实现安全的驾驶自动化至关重要。该系统还能够探测距离达315米之外的道路使用者（行人、摩托车和自行车骑手），并可识别远达230米处的潜在危险。关键是，在传统雷达系统常常失效的场景，例如隧道、施工区以及其他复杂和杂乱的环境中，Mobileye成像雷达也表现出色。\u003C\u002Fp>\n\u003Cp>这款雷达的前向BSR（盲区4D成像雷达）版本提供全覆盖的感知能力，而用于车角安装的较小型的BSRC（4D成像角雷达）版本则拥有超过300个通道。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-05-28T07:00:00.000Z",[99,64,49,21],{"id":191,"type":141,"url":192,"title":193,"description":194,"primary_tag":12,"author_name":131,"is_hidden":96,"lang":132,"meta_description":194,"image":195,"img_alt":196,"content":197,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":198,"tags":199},294,"the-fast-lane-to-higher-levels-of-autonomy-with-the-eyeq6-soc","EyeQ™6系统集成芯片：通往更高等级驾驶自动化的快车道","作为最新一代系统集成芯片（SoC）解决方案，Mobileye EyeQ™6 系列可助力车企高效规划产品路线，加速产品上市进程。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F4cf0a8a6c1d2c1369d282109b1a4975e_1744873267353.jpg","该系列专为满足车企多样化需求打造，覆盖从常规标准车型到高端豪华车型的全产品矩阵。","\u003Cp>全新Mobileye EyeQ™6SoC不仅突破性能极限，更为车企提供定制高级驾驶辅助系统（ADAS）与高等级驾驶自动化技术的基础架构，同时精准对接从科技发烧友到普通用户的全场景消费级高度自动驾驶汽车市场需求。\u003C\u002Fp>\n\u003Cp>本文将解析EyeQ™6的新增功能，并揭秘其技术架构如何助力车企在ADAS与高度自动驾驶领域实现无缝升级。\u003C\u002Fp>\n\u003Ch3>EyeQ™6 全景解析\u003C\u002Fh3>\n\u003Cp>作为Mobileye最新技术体系的核心，EyeQ™6 SoC系列可满足从单个前视摄像头到多传感器的所有ADAS需求。\u003C\u002Fp>\n\u003Cp>其中，EyeQ™6 Lite (EyeQ™6L) 是一款低功耗芯片，可扩展入门级ADAS功能；EyeQ™6H是EyeQ™6L的进阶版本，在特定运行设计区间可支持高阶ADAS、有条件自动驾驶及完全自动驾驶方案（如Mobileye SuperVision™和Mobileye Chauffeur™\u002FMobileye Drive™）。车企可借助这一独特系统，采用模块化设计，根据目标用户灵活定制功能组合。  \u003C\u002Fp>\n\u003Ch3>技术架构探秘 \u003C\u002Fh3>\n\u003Cp>EyeQ™6系统集成芯片架构的核心竞争力源自其独特的软硬件协同设计。该系列芯片结合多核处理器、加速器与复合人工智能架构，可实现卓越能效。独创的XNN人工智能模型，支持复杂\u002F简易任务并行处理。\u003C\u002Fp>\n\u003Cp>该系列芯片还可分配合理负载、提升深度学习能力和优化数据流，进而带来综合性能的跃升。事实上，其深度学习性能较前两代SoC提升10倍，CPU性能提升1.1-1.9倍。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F91487f605322ce4c99830c4d950995e0_1744873738525.png\" alt=\"\" width=\"1200\" height=\"668\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>前瞻性设计，全产线赋能  \u003C\u002Fh3>\n\u003Cp>从常规标准车型到高端豪华车型，EyeQ™6系列全面适配多样化车型配置。更关键的是，车企可在保留核心ADAS安全功能的基础上，实现更高等级驾驶自动化或功能升级，无需重复认证和验证流程。这一设计为车企及供应商开辟了基于现有基础设施的升级路径，既能实现更高等级驾驶自动化，又可确保长期可行性，同时从高成本效益中获益。 \u003C\u002Fp>\n\u003Ch3>借助EyeQ™6L 拓展基础ADAS能力  \u003C\u002Fh3>\n\u003Cp>作为高性价比的面向大众市场的ADAS解决方案，EyeQ™6L提供专为前视摄像头传感器量身定制的优化架构，同时可选配雷达。车企可灵活选装独立功能模块，实现成本与性能的平衡。\u003C\u002Fp>\n\u003Cp>基于同款SoC稍作升级，车企即可集成乘员监控系统（OMS）与驾驶员监控系统（DMS）。此外，车企可灵活选择摄像头配置：既可选择高性价比的200万像素方案，也可选择适配高等级驾驶功能的800万像素方案（支持车道、交通标识、道路标线、施工区域及交通信号灯的色彩增强检测）。\u003C\u002Fp>\n\u003Cp>简而言之，车企可在基础ADAS框架内灵活调整，并依托同款SoC内置功能实现功能升级。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc2479642c97081cf05d556a0562fcfa9_1744873835527.jpg\" alt=\"\" width=\"1200\" height=\"670\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>从“辅助驾驶”逐步迈向“完全自动驾驶”\u003C\u002Fh3>\n\u003Cp>EyeQ™6H SoC引领驾驶自动化技术，实现了两个方面的重大飞跃：一方面是无缝实现向完全自动驾驶的升级，另一方面是确保新增功能之间产生更大协同效应。通过将安全关键功能与泊车应用、可视化等电子控制单元（ECU）整合至单颗系统集成芯片，构建集中化互联系统。\u003C\u002Fp>\n\u003Cp>这种设计赋予车企高度自由的组件选择空间，满足其对灵活性、集中化架构、快速上市及新盈利模式的追求。而EyeQ™6H正是这场变革的基石。\u003C\u002Fp>\n\u003Cp>在驾驶自动化方面，这一架构将推动整个行业进一步发展，更加注重软件定义。车企可在延续核心ADAS安全功能的同时，向更高阶辅助驾驶系统过渡。车企可从单颗EyeQ™6H驱动的“Mobileye环绕式ADAS™”方案起步，逐步升级至双EyeQ™6H SoC赋能的Mobileye SuperVision™（实现多数道路点对点驾驶员运动脱离驾驶），最终扩展至Mobileye Chauffeur™或Mobileye Drive™（分别解锁面向消费级市场和商用场景的驾驶员运动脱离驾驶及视觉脱离驾驶能力）。这有助于车企构建可持续扩展的驾驶自动化蓝图，专注于持续迭代。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F672c2922e4c5e0a8e25091f84d4bdf42_1745409779795.jpg\" alt=\"\" width=\"1200\" height=\"670\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>OTA赋能全生命周期升级 \u003C\u002Fh3>\n\u003Cp>EyeQ™6的关键特性在于通过智能设计实现的长期可用性。但真正将性能提升至新维度的是其在线升级（OTA）能力。OTA更新对现代车辆至关重要，特别是在软件定义汽车兴起的当下。OTA更新有利于车辆软件持续改进并保持系统最新状态，所有增强功能均通过远程无缝交付实现，无需人工干预。\u003C\u002Fp>\n\u003Cp>Mobileye将该功能深度集成至系统中，确保车辆在无需硬件升级的情况下持续适应未来需求。\u003C\u002Fp>\n\u003Ch3>加速驾驶自动化，守护驾乘舒适性 \u003C\u002Fh3>\n\u003Cp>随着出行新时代的到来，加之车辆向软件定义化转型，支撑这一转型的技术必须具备可扩展性、灵活性、高性能及持续增强能力。\u003C\u002Fp>\n\u003Cp>Mobileye深谙灵活性与可扩展性的价值，致力于提供定制化SoC解决方案，满足车企的软硬件需求。对于希望快速拓展市场的车企而言，在架构层面确保灵活性和可扩展性至关重要。\u003C\u002Fp>\n\u003Cp>Mobileye的第六代SoC能够满足多元化车企及其用户的需求，打造全方位解决方案，让所有人都能够享受全新驾驶体验，拥抱全维度驾驶自动化技术。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>","2025-04-17T07:00:00.000Z",[21,13],{"id":201,"type":141,"url":202,"title":203,"description":204,"primary_tag":15,"author_name":131,"is_hidden":96,"lang":132,"meta_description":204,"image":205,"img_alt":206,"content":207,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":208,"tags":209},289,"modularity-from-adas-to-av","Mobileye全新ECU系列：模块化架构，驱动ADAS到AV演进","该系列人工智能解决方案搭载Mobileye迄今为止最强大的芯片，提供覆盖辅助驾驶到高等级驾驶自动化汽车全域的模块化设计","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F97ee57a9843cd0c7ddfc4330047605f9_1740469437784.jpg","Mobileye全新ECU系列的核心是一块共享主板，配备双EyeQ6H芯片和一颗集成式MCU。","\u003Cp>自问世以来，Mobileye EyeQ™芯片就作为Mobileye高级驾驶辅助系统（ADAS）的算力基石，持续助力道路安全。秉承以视觉为核心的设计理念，该芯片可实现自动紧急制动、车道保持等挽救生命的技术功能。随着Mobileye EyeQ™芯片的全球装机量超过2亿颗、辅助驾驶与高等级驾驶自动化汽车平台间的模块化互通性进一步提高，我们正逐步将完全自动驾驶的未来愿景变为现实。\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"Mobileye ECU\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1060382068?h=599b761860&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>如今，我们依托Mobileye在技术创新、安全设计和系统扩展性方面的领先优势，积极推动未来愿景转化为现实应用，正在将这一创新推向新高度。Mobileye全新电子控制单元（ECU）系列专为未来扩展而生，提供三款产品配置，可以支持不同的驾驶自动化等级。三大平台均搭载最新一代Mobileye EyeQ™6H系统集成芯片（SoC），可助力汽车制造商在高等级驾驶自动化旅程中高效进阶，在为驾驶员提供安全性与舒适性的同时，降低开发与验证风险。\u003C\u002Fp>\n\u003Ch3>ECU的内核：具备卓越优势的EyeQ芯片\u003C\u002Fh3>\n\u003Cp>就打造可扩展的模块化高级驾驶平台而言，其核心挑战在于平衡SoC的灵活性与效率。Mobileye EyeQ6H采用我们最先进SoC的独特架构，旨在最大限度减少这种权衡。通过融合固定功能与通用处理能力，EyeQ6H可加速并行计算功能，包括执行要求严苛的AI深度学习任务，以及处理环视摄像头每秒捕获的超1,000帧画面。\u003C\u002Fp>\n\u003Cp>之后，我们将EyeQ6H集成到Mobileye自主研发的主板上。这种深度整合使我们能灵活满足车企需求，打造更顺畅的系统集成流程，并更好地适应车企未来的产品规划需求。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd4a8c7bdccdc1a58e536dc266b1556e9_1740469761906.jpg\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch3>一块主板赋能产品规划\u003C\u002Fh3>\n\u003Cp>这块共享主板是我们全新ECU系列的核心组件，配备双EyeQ6H芯片和一颗集成式MCU。这种紧凑而强大的架构为汽车制造商奠定了研发高等级驾驶自动化汽车解决方案的基础，仅需根据车辆未来的软硬件设计进行局部调整即可实现升级。\u003C\u002Fp>\n\u003Cp>全新ECU系列的基础配置为我们的“驾驶员运动脱离\u002F需注视”平台Mobileye SuperVision™。该平台采用11个摄像头，可选装雷达，并可执行最高130公里\u002F小时的领航辅助驾驶（需在可用区域，根据具体配置、操作手册、设计运行范围及相关法规要求并在驾驶员持续监督下使用）等特定驾驶动作，显著提升驾乘体验。这款人工智能系统仅重2.3公斤左右，体积与麦片盒相仿，内置高级泊车功能，耐久性设计可确保系统可靠性。\u003C\u002Fp>\n\u003Ch3>进阶“驾驶员视觉脱离”功能\u003C\u002Fh3>\n\u003Cp>我们在保留SuperVision™ ECU大部分设计的基础上增加副板，推出了面向消费级汽车的Mobileye Chauffeur™“驾驶员运动脱离\u002F驾驶员视觉脱离”驾驶平台（需在可用区域，根据具体配置、操作手册、设计运行范围及相关法规要求使用）。副板额外集成一颗EyeQ6H芯片，既可扩展功能，又可构建软硬件冗余系统。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F23c7d34b85eb407e222a5796f4c8fe75_1740469856076.jpg\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Cp>除摄像头感知层外，Mobileye Chauffeur™还引入由雷达和激光雷达传感器组成的感知网络，通过多传感器融合感知，实现在设计运行范围（ODD）内的“驾驶员视觉脱离”驾驶，在驾驶员需保持警觉并随时准备接管的同时，使车辆能自主应对路况。\u003C\u002Fp>\n\u003Cp>双板架构通过冗余设计提供额外的安全层，使系统可在必要时执行最小风险策略，并在发生故障时安全实现靠边停车。\u003C\u002Fp>\n\u003Ch3>迈向无人驾驶\u003C\u002Fh3>\n\u003Cp>Mobileye Drive™在主板基础上进一步扩展，车内甚至无需驾驶员。该平台专为出行即服务（MaaS）设计，主副板共搭载四颗Mobileye EyeQ6H芯片，采用13个摄像头，以及多个成像雷达及激光雷达。\u003C\u002Fp>\n\u003Cp>尽管Mobileye Drive™的设计初衷是面向出行服务提供商，而SuperVision™和Chauffeur™则主要服务于消费级车辆，但比较三款ECU时，可清晰发现其软硬件架构基本相同。三款系统在设计之初便充分考虑了模块化与可扩展性，采用相似的外形设计、接口标准、连接协议及统一的软件核心，使车企能够提前规划产品路线，并在不同平台间高效切换。\u003C\u002Fp>\n\u003Cp>全新ECU系列将Mobileye的愿景进一步变为现实，可为高等级驾驶自动化汽车发展的众多阶段提供量身定制的可扩展平台，进而助力汽车制造商打造更安全、更智能、适应性更强的汽车，在从“驾驶员运动脱离”驾驶到“驾驶员视觉脱离”驾驶，直至完全无人驾驶的演进过程中，实现性能与量产效率的完美平衡。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-02-27T08:00:00.000Z",[27,21,34,84],{"id":211,"type":141,"url":212,"title":213,"description":214,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":214,"image":215,"img_alt":216,"content":217,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":218,"tags":219},287,"mobileyes-ces-2025-showing","Mobileye在CES 2025的亮点回顾","Mobileye在拉斯维加斯展示的最新技术引得众人驻足","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe8f3cdb7e19232218e35664f2bec3a8c_1737633952001.jpg","Mobileye在CES 2025的精彩表现！","\u003Cp> 尽管CES 2025已圆满落幕，但我们的CES之旅仍令人回味无穷。得益于深入浅出的演讲、引人入胜的展台展示以及关于交通出行和高等级驾驶自动化汽车未来的精彩讨论，Mobileye的出行解决方案在为期四天的展会中无疑成为了焦点。\u003C\u002Fp>\n\u003Cp>我们展出了搭载Mobileye Drive™的两款车型——大众ID Buzz和Holon Mover，以及由多层有机玻璃打造的3D汽车外形互动产品方案，吸引了大量观众驻足观看。与此同时，Mobileye的高管们参与了多场圆桌讨论，分享了对汽车行业关键议题的独到见解。\u003C\u002Fp>\n\u003Cp>欣赏Mobileye在CES 2025的精彩时刻！\u003Cbr \u002F>\u003Ciframe title=\"Mobileye at CES 2025: Highlights\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1047443316?h=904d935a52&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>Now. Next. Beyond.  \u003C\u002Fh3>\n\u003Cp> Mobileye总裁兼首席执行官Amnon Shashua教授在其一年一度的CES主题演讲“Mobileye: Now. Next. Beyond.”中，分享了他对高等级驾驶自动化行业未来的愿景，探讨了高等级驾驶自动化汽车如何从Demo阶段迅速迈向现实生活的实际应用。\u003Cbr \u002F>\u003Ciframe title=\"Mobileye: Now. Next. Beyond CES 2025 Press Conference with Prof. Amnon Shashua\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1047296511?h=a4dba090ba&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe> \u003C\u002Fp>\n\u003Ch3>引擎盖下的秘密 \u003C\u002Fh3>\n\u003Cp>在我们展台上，高耸的时尚几何结构展示了Mobileye的最新产品，吸引了无数参观者前来了解我们的技术。展台内，除了展示最新的电子控制单元（ECU）套件外，还展示了Mobileye令人印象深刻的成像雷达及其他先进技术。\u003Cbr \u002F>\u003Ciframe title=\"Mobileye at CES 2025 Booth Walkthrough\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1047295510?h=b1bfab4cd2&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe> \u003C\u002Fp>\n\u003Ch3>Mobileye 主舞台\u003C\u002Fh3>\n\u003Cp>“安全”是Mobileye展台演示的核心主题。关于冗余、人工智能驱动的平台，与多方协作的讨论都涉及了提高平均故障间隔时间（MTBF）对安全出行的重要性。\u003C\u002Fp>\n\u003Cp>我们回顾了Mobileye从驾驶辅助系统到完全自动驾驶出租车的演变，探讨了人工智能驱动的高等级驾驶自动化技术路线，并阐释了在我们的系统中如何利用冗余机制提升可靠性。此外，Mobileye执行副总裁Johann (JJ) Jungwirth、大众汽车ADMT高级副总裁Sebastian Lasek和MOIA首席执行官Sascha Meyer还在展台主舞台进行了一场主题为“开启全球高等级驾驶自动化出行”的圆桌讨论。三位高管深入交流了Mobileye与大众汽车集团在无人驾驶服务和大众汽车ID Buzz AD方面的紧密合作，探讨了在不同地区实施项目时所采用的软硬件技术，以及对未来出行蓝图的共同愿景。\u003Cbr \u002F>\u003Ciframe title=\"Unlocking Autonomous Mobility Globally with Volkswagen, MOIA and Mobileye\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1047297083?h=60431b5f7a&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>高管活动 \u003C\u002Fh3>\n\u003Cp>Mobileye首席技术官Shai Shalev-Shwartz教授参加了一场关于高等级驾驶自动化汽车技术现状的圆桌讨论。在展望高等级驾驶自动化技术的现状和未来时，Shalev-Shwartz教授表示，未来几年内，私家车搭载的“驾驶员视觉脱离”驾驶系统，以及完全自动驾驶出租车服务成本的降低，极有可能改变我们目前对出行的看法。他认为“这是一个具有革命意义的时刻，创新产品将改变人们对通勤的认知”。\u003Cbr \u002F>\u003Ciframe title=\"CTA & PAVE Autonomous Vehicle Roundtable at CES 2025\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1047299158?h=32a75cd4b6&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003Cbr \u002F>Mobileye高等级驾驶自动化业务执行副总裁Johann (JJ) Jungwirth与行业领袖共同探讨了高等级驾驶自动化汽车融入社区、赢得消费者信任以及利用人工智能提升高等级驾驶自动化技术等话题。\u003Cbr \u002F>\u003Ciframe title=\"JJ at Autonomous Vehicles - The Future is Finally Here Panel (CES 2025)\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1049234229?h=ed2b30df34&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>展会互动\u003C\u002Fh3>\n\u003Cp>我们十分高兴与同样对未来出行充满热情的志同道合者们交流。\u003Cbr \u002F>\u003Ciframe title=\"Man On The Street at CES 2025\" src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F1051080523?h=a875a35f16&badge=0&autopause=0&player_id=0&app_id=58479\" width=\"600\" height=\"338\" frameborder=\"0\">\u003C\u002Fiframe>\u003C\u002Fp>","2025-01-23T08:00:00.000Z",[64,99,6,21,84],{"id":221,"type":141,"url":222,"title":223,"description":224,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":224,"image":225,"img_alt":226,"content":227,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":228,"tags":229},285,"prof-amnon-shashua-at-ces-2025","CES 2025: Amnon Shashua 教授畅谈未来出行变革","在CES 2025主题演讲 “Mobileye: Now. Next. Beyond.”中，Mobileye 总裁兼首席执行官Amnon Shashua教授向听众提出了一个核心问题 – 颠覆出行的关键是什么？","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7d850b79bb7c52216b36173a9f6bcfb3_1736363040927.jpg","通过融合尖端技术与智能路网专长，兼顾成本效益，Mobileye正在塑造未来出行蓝图","\u003Cp>这是Mobileye创始人兼首席执行官Amnon Shashua教授连续第十年分享他对驾驶自动化行业未来的愿景，探讨了在人工智能的突破性进展推动下，高等级驾驶自动化汽车迅速从实验阶段走向日常现实中。尽管完全自动驾驶出租车已经在北美和欧洲开始投入使用，但Mobileye认为高等级驾驶自动化技术还将在消费级出行领域引发一场革命。\u003C\u002Fp>\n\u003Cp>点击此处观看主题演讲。\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FMQnkqXoMEOc?si=VayQlJneUY5nIrwU\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>精确度 vs. 召回率\u003C\u002Fh3>\n\u003Cp>Shashua教授提到了实现可扩展的完全自动驾驶所需的两个关键维度：召回率（可用性）和精确度（安全性）。召回率可确保系统处理多样化的场景、地理环境和条件，而精确度则通过最大限度地减少错误来确保安全，更侧重于安全性。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3c584de8c954aee7d8eadcd75d1953b5_1736363079618.jpg\" alt=\"Precision vs. Recall\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch3>创建安全架构\u003C\u002Fh3>\n\u003Cp>在谈到Mobileye的安全架构及其如何应对不合理风险时，Shashua教授解释道，Mobileye的方法可以处理四种错误类型。他还详细阐述了Mobileye系统如何通过一系列软件和硬件冗余设计来减少这些错误的发生。随后，他介绍了Mobileye的创新融合方法 – 主系统-监护系统-备用系统（\u003Cstrong>Primary-Guardian-Fallback (PGF)\u003C\u002Fstrong>\u003Cstrong>）\u003C\u002Fstrong>，这种分层决策模型将多数法则扩展至非二元决策，从而增强系统在复杂场景下的可靠性和适应能力。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fced2c26cc06d0aeed8104fdf72d06dd3_1736363132926.jpg\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch3>工程创新：开辟全新视觉感知方式\u003C\u002Fh3>\n\u003Cp>Shashua教授还介绍了用于分层视觉的独特感知技术。这种先进的处理技术由Mobileye最新的系统集成芯片EyeQ6™驱动，可生成3D感知，从而构建一种冗余且可靠的环境理解。\u003C\u002Fp>\n\u003Cp>Mobileye在精度方面不断取得突破，尤其是在成像雷达技术的应用上，这项技术已经取得了显著进展。预计于2026年投产的成像雷达技术可提供高分辨率，其感知能力能够弥补摄像头存在的盲区和感知弱点。在Mobileye Drive™和Mobileye Chauffeur™中，这项技术发挥着关键作用，受到了客户的广泛关注。\u003C\u002Fp>\n\u003Ch3>展望未来\u003C\u002Fh3>\n\u003Cp>最后，他还谈及了产品从演示到规模化量产所面临的挑战，强调可购性是普及先进系统的关键。通过融合尖端技术与智能路网专长，兼顾成本效益，Mobileye正在塑造未来出行蓝图。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-01-08T08:00:00.000Z",[6,21,78,64,99],{"id":231,"type":141,"url":232,"title":233,"description":234,"primary_tag":63,"author_name":131,"is_hidden":96,"lang":132,"meta_description":234,"image":235,"img_alt":236,"content":237,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":238,"tags":239},282,"from-driver-assisting-to-self-driving","从辅助驾驶到高等级驾驶自动化汽车：Mobileye常见问题解答","10个问题帮助大众深入了解Mobileye","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9c9147cd067ec3b9bb3a238f5a908f87_1733904031431.png","“从基础ADAS，到高等级驾驶自动化功能，再到L4驾驶技术，我们设计所有解决方案时都将安全放在首位，道路使用者的安全始终是我们最看重的。”","\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>Mobileye是做什么的？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>Mobileye开发并提供全球领先的高等级驾驶自动化汽车和驾驶辅助技术解决方案，在计算机视觉、机器学习和定位技术方面掌握举世瞩目的专业技术。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>具体而言呢？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>简而言之，我们希望通过打造更安全、更智能的汽车，在无论是人类驾驶还是无人驾驶的情况下，都让道路更安全。我们拥有将微芯片编程并发挥其全部潜力的专业知识，同时还能将其与摄像头等传感器完美同步。\u003C\u002Fp>\n\u003Ch4>\u003Cstrong>\u003Cspan style=\"font-size: 12pt;\">那么Mobileye是一家什么性质的公司？是汽车公司、科技公司还是人工智能公司？\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh4>\n\u003Cp>这是一个非常有意思的问题。Mobileye三者兼而有之。虽然我们不生产汽车，但我们为汽车制造商提供安全驾驶解决方案。事实上，如果一辆汽车具有车道保持辅助、自动紧急制动或智能车速警示等功能，那么它很有可能搭载了Mobileye的EyeQ芯片、高级驾驶辅助系统（ADAS）的传感器或摄像头等装置。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>Mobileye从事这个行业多久了？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>Mobileye由Amnon Shashua教授于1999年创立，他提出了一个简单而前瞻性的想法 - 将摄像头传感器作为挽救生命技术的基础，由此奠定了公司的使命基调。此后，Mobileye不断开拓创新，推出突破性技术，并开发了真正冗余（True Redundancy™）感知体系和责任敏感安全模型（RSS™），为我们的高级驾驶辅助系统和高等级驾驶自动化汽车（AV）解决方案提供支持。我们业界领先的平台通过提升驾驶安全性来增强驾驶体验，并融入到车辆设计中，从单个摄像头到用于高等级驾驶自动化车辆的人工智能（AI），应有尽有。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F27efb38a1b51449ba186725bb1fb9b3d_1733904095025.png\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>你们生产什么产品？ \u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>很多很多。就高级驾驶辅助系统而言，我们开发了一系列能够提高安全性、提升驾驶体验并自动化执行某些驾驶功能的技术和功能。高级驾驶辅助系统分为多个级别，首先是基础ADAS，它包括一个用于提高安全性的前置摄像头。高级驾驶辅助系统包括自动紧急制动（AEB）、前防撞警告（FCW）、车道保持辅助、自适应巡航控制（ACC）和交通标志识别等功能。目前，这项技术已经被广泛应用于现今数百万辆车辆中，有效预防交通碰撞的事故并减少伤害。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>仅此而已吗？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>当然不是！Mobileye云增强驾驶辅助系统（Cloud-Enhanced Driver-Assist™ system）无需额外硬件，便可提供更安全、更顺畅、更舒适的驾驶体验，标志着高级驾驶辅助系统的一次性能飞跃。它利用来自全球数百万辆配备Mobileye的车辆发送的道路信息，提供定位服务。\u003C\u002Fp>\n\u003Cp>基于上述两大平台，我们又推出了Mobileye Surround ADAS™，这是一个用于高速公路的“驾驶员运动脱离\u002F需注视”解决方案，由我们迄今为止功能最强大的EyeQ™6H系统级芯片驱动。它利用多达六个摄像头和五个雷达，进而为车辆提供所需的数据，使其能够顺畅的在真实道路环境中行驶。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>可以谈一谈高等级驾驶自动化汽车吗？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>在深入探讨我们的高等级驾驶自动化平台之前，我们先花点时间来重点介绍一下Mobileye SuperVision™，这是连接我们高级驾驶辅助系统产品和高等级驾驶自动化汽车解决方案的桥梁。凭借其360°视觉和感知系统（最多可搭载11个摄像头及两颗EyeQ™6H系统集成芯片），SuperVision™开启标准驾驶功能后，可让驾驶员在几乎所有道路类型上实现“驾驶员运动脱离”驾驶但仍要求注视的领航辅助驾驶。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>“驾驶员运动脱离\u002F需注视”系统之后还会有什么提升？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>当然是“驾驶员运动脱离\u002F驾驶员视觉脱离”！基于我们的安全架构方法论、先进计算机视觉功能以及包括雷达、激光雷达和11个摄像头在内的硬件，我们面向消费级汽车的Mobileye Chauffeur™“驾驶员运动脱离\u002F驾驶员视觉脱离”解决方案，可实现最高130公里\u002F小时的车速行驶，并可在其规定的设计运行范围（ODD）内提供点到点的自动“领航辅助驾驶”体验。\u003C\u002Fp>\n\u003Cp>另外，我们还开发了端到端高等级驾驶自动化系统Mobileye Drive™，它将进一步提升我们的技术，有助于汽车制造商和交通运营商为完全自动驾驶出租车、拼车、公共交通和物流配送车等不同类型的高等级驾驶自动化车辆提供无人驾驶的解决方案。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>但是安全问题呢？高等级驾驶自动化汽车安全吗？比人类驾驶更安全吗？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>从基础ADAS，到高等级驾驶自动化功能，再到无人驾驶技术，我们设计所有解决方案时都将安全放在首位，道路使用者的安全始终是我们最看重的。我们最新的EyeQ6 SoC系列是我们迄今为止最先进的产品，可使车辆以更高的精度和可靠性在路上行驶。我们的责任敏感安全模型（RSS™）是一种基于数学的安全模型，遵循五大核心安全规则，并构建了Mobileye的驾驶策略。同时，我们的REM™技术创建了一个持续更新的智能路网，能够帮助汽车在我们的高级驾驶辅助系统和高等级驾驶自动化平台中实现更安全的驾驶。\u003C\u002Fp>\n\u003Ch4>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>那么Mobileye的未来愿景是怎样的？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh4>\n\u003Cp>Mobileye的未来愿景包含两大关键理念：一是借助高等级驾驶自动化能力大幅减少交通事故的发生；二是让消费者以全新的方式受益于L4级驾驶车辆，例如享受完全自动驾驶出行服务，缓解闹市区的交通拥堵及污染等问题。这就是我们的目标，虽然我们已有很多先进技术投入使用，但为推动完全自动驾驶成为现实，我们每天仍在努力解决各种复杂的场景和极限状况。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-12-12T08:00:00.000Z",[99,64,21],{"id":241,"type":92,"url":242,"title":243,"description":244,"primary_tag":5,"author_name":131,"is_hidden":96,"lang":132,"meta_description":244,"image":245,"img_alt":246,"content":247,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":248,"tags":249},281,"mobileye-at-ces-2025","Mobileye 闪耀 CES 2025","在展会期间，您可访问我们的新闻工具库，获取最新的活动、新闻、多媒体内容等信息。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1833572c15ccfb76fcd471355eedb899_1734044782739.png","Amnon Shashua 教授将于 1 月 7 日上午 11 点举行年度新闻发布会，拉开 Mobileye CES 2025 序幕。","\u003Cp>\u003Cstrong>Mobileye 亮相 CES 2025\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye 将加入并出席 CES 2025，展示推动道路安全与自动驾驶出行的创新技术与解决方案。从高级驾驶辅助系统（ADAS）到完全自动驾驶汽车（AV），了解我们如何引领智能驾驶的出行未来。\u003C\u002Fp>\n\u003Cp>欲了解更多关于新闻发布会、展位演示和重点活动的信息，请访问 \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2025\u002F\">mobileye.com\u002Fces-2025\u003C\u002Fa>。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>新闻\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-announces-ces-2025-press-conference\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye CES 2025 新闻发布会\u003C\u002Fa>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>在展会开幕之际，Mobileye 将举行年度 CES 新闻发布会“Mobileye: Now. Next. Beyond.”，创始人，总裁兼 CEO Amnon Shashua 教授将重点介绍多个平台和出行应用领域的创新解决方案，并分享我们对 2025 年及出行未来的愿景。\u003C\u002Fp>\n\u003Cp>点击\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-announces-ces-2025-press-conference\u002F\">这里\u003C\u002Fa>，了解更多关于我们的新闻发布会和 CES 2025 活动的咨询。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Mobileye 技术与解决方案\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:mobileye-technology-and-solutions[**]\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Mobileye SuperVision \u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:mobileyes-advanced-platforms-in-the-drivers-seat[**]\u003C\u002Fp>\n\u003Cp>\u003Cstrong>由 Mobileye 所驱动\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:driven-by-mobileye[**]\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Amnon Shashua 教授\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:professor-amnon-shashua[**]\u003C\u002Fp>\n\u003Cp>\u003Cstrong>图例\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:infographics[**]\u003C\u002Fp>\n\u003Cp>\u003Cstrong>视频\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]vimeo-press:1031870114[**]\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-12-08T08:00:00.000Z",[6,21,13,27],{"id":251,"type":141,"url":252,"title":253,"description":254,"primary_tag":5,"author_name":131,"is_hidden":96,"lang":132,"meta_description":254,"image":255,"img_alt":256,"content":257,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":258,"tags":259},280,"driving-ai","Mobileye Driving AI Day 活动的5大要点","首席执行官 Amnon Shashua 教授和首席技术官 Shai Shalev-Shwartz 教授介绍自动驾驶出行领域的关键人工智能技术的进展。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9d5275f3635f6d26bd00f9edf597d298_1732784251661.jpg","Shai Shalev-Shwartz 教授和 Mobileye 总裁兼首席执行官 Amnon Shashua 教授出席 Driving AI Day","\u003Cp>Mobileye是致力于开发完全自动驾驶系统的领军企业之一。我们的目标是搭建完全自动驾驶“可脱眼”系统，但这是一项十分复杂的工作，需要极高的安全标准，以及大量的长期投资。为了达成这一里程碑，我们凭借在高级驾驶辅助技术市场的领先地位创造当前收入，确保业务的可持续发展，同时始终聚焦于完全自动驾驶的最终目标。\u003C\u002Fp>\n\u003Cp>但要如何实现这一目标？上个月，我们的首席执行官Amnon Shashua教授和首席技术官Shai Shalev-Schwartz教授在Mobileye Driving AI Day活动中发表了演讲，讨论并分享了Mobileye为实现这一里程碑所采用的创新人工智能方法。\u003C\u002Fp>\n\u003Cp>观看演讲的五大要点，阐释了Mobileye以智能方式利用人工智能，从而逐步攻克自动驾驶技术的挑战。\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F92e5zD_-xDw?si=AFtw2AQWwgfm0Eoz\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"font-size: 14pt;\">单一方法无法解决自主性问题\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>在开场演讲中，Mobileye首席执行官Amnon Shashua教授概述了解决自主性问题的三种技术路线。以激光雷达为核心的复合人工智能系统（CAIS）方法，以纯视觉和端到端人工智能方法，以及Mobileye以摄像头为核心的复合人工智能系统（CAIS）方法。\u003C\u002Fp>\n\u003Cp>Shashua教授强调了评估每种方法时，需要基于四大关键支柱来衡量其是否成功实现自主性：成本、模块化、地域可扩展性和平均故障间隔时间（MTBF）。虽然每种方法都有其独特的优势和局限性，但没有一种方法能满足全部四大支柱并完全解决自主性问题。\u003C\u002Fp>\n\u003Cp>每种方法都有利有弊。某种方法可以提供高精度但生产效率却极度低下，而另一种方法本身则可能存在局限性或并不可靠。例如，以激光雷达为核心方法可提供高精度，从而实现极高（出色）的平均故障间隔时间，但其成本却限制了区域可扩展性，因此其难以适应更广泛的市场。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F53a8091b10a0f6baa10a8cac1aec0a67_1732785971870.png\" alt=\"\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>相反，依靠纯视觉或以摄像头为核心方法更为经济实惠，但通常会在实现高MTBF方面面临更多挑战，而且纯端到端方法会带来自动驾驶汽车领域的对齐问题（难以确保人工智能系统\u002F机器学习模型的目标与人类目标保持一致）。不过，经过平衡的方法可以弥合这些差距，既提供安全性，又能实现自动驾驶市场的可扩展性。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"font-size: 14pt;\">纯端到端方法存在局限性\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>端到端方法的前提是，向系统输入的数据越多，系统在模仿人类驾驶行为方面的能力就越优秀，最终达到甚至超越人类的驾驶水平。这种方法无需“粘合代码”或手动编码，而是完全依赖数据，尤其是无监督数据。\u003C\u002Fp>\n\u003Cp>基于Transformer的神经网络从数以百万计的汽车发送的驾驶数据中不断学习，消除了人工标注或解释数据的手动过程。。然而，这种方法面临三大挑战：缺乏抽象概念、存在捷径学习问题以及长尾问题。这三个挑战都凸显了当前系统在有效处理复杂现实驾驶场景方面的局限性。\u003C\u002Fp>\n\u003Cp>在演讲中，Shashua教授以“计算器问题”为例解释了缺乏抽象概念的局限性。其中，“计算器问题”是指ChatGPT因其基于语言的架构局限性，难以可靠地处理复杂多步骤计算的问题。\u003C\u002Fp>\n\u003Cp>要解决这个问题，答案其实极其简单：必须集成计算器工具（即集成Python环境来提高计算准确性）。然而，Shashua教授认为，仅仅依靠无监督数据的端到端方法来解决自动驾驶汽车这样的安全关键系统的所有复杂问题，既不可靠又充满风险。\u003C\u002Fp>\n\u003Cp>这种方法还有可能在学习阶段嵌入不良甚至危险的驾驶行为，且自动驾驶汽车的“对齐问题”也会更加显而易见，因为模型可能会优先考虑“常见但错误”的行为，而不是“罕见但正确”的行为。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc090cff3e255d37cf9c145fd17435972_1732784761464.jpg\" alt=\"\" width=\"1272\" height=\"825\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>例如，人类驾驶员通常会在接近停车标线时选择缓慢减速后继续前进，或做出鲁莽驾驶行为，此时，尽管这些行为并不正确，系统仍可能会将其视为常见行为进行学习。因此，区分正确和不正确的操作（尤其是在“罕见但正确”的场景中）仍然是一项复杂的挑战。\u003C\u002Fp>\n\u003Cp>这些问题可以通过特斯拉完全自动驾驶（FSD）系统收集的数据得到实际例证。我们可以看到，完全自动驾驶系统的数据表明，长尾问题在此显现，即使输入大量数据，模型也很难充分解决这些罕见事件，从而影响系统的整体安全性和可靠性，并阻碍系统在每一次产品升级中提高平均故障间隔时间（MTBF）的能力。\u003C\u002Fp>\n\u003Cp>这一问题凸显了仅依靠大型数据集的局限性，因为罕见但关键的驾驶场景往往在数据中被低估或缺失。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"font-size: 14pt;\">PGF(Primary-Guardian-Fallback) 融合对于打造安全系统至关重要\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>在整个驾驶过程中，我们需要进行无数次决策。从非常简单的二元选择——例如左转还是右转、刹车还是不刹车，到更复杂和微妙的判断——比如，如果我要刹车，是应该轻踩还是急刹？\u003C\u002Fp>\n\u003Cp>经典的处理方式是：多个系统提供答案，并采取少数服从多数的原则 – 如果三个系统中有两个决定向左并线，那么就向左并线。但是，如果这三个系统提供了三种不同的建议，例如分别是左转、右转或保持直行呢？在这种情况下，多数原则并不能解决问题。\u003C\u002Fp>\n\u003Cp>这时候就需要PGF（Primary-Guardian-Fallback）融合方法。PGF系统是一个分层决策模型。其工作原理如下：\u003C\u002Fp>\n\u003Cul>\n\u003Cli data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\">\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"auto\">Primary 主系统: \u003C\u002Fspan>\u003C\u002Fstrong>该系统是标准自动驾驶系统（SDS），用于生成车辆的轨迹 - 规划的路线或行动方案。在大多数情况下，它是主要决策者，输出初步建议的行驶路线或行动方案。\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\">\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"auto\">Fallback 备用系统: \u003C\u002Fspan>\u003C\u002Fstrong>与Primary主系统一样，Fallback备用系统是另一种能自动生成路径轨迹或替代路线的自动驾驶系统。它是“Primary”主系统遇到问题或Guardian监护系统检测到潜在问题时的备用系统。\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli data-leveltext=\"\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\">\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"auto\">Guardian 监护系统: \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-contrast=\"auto\">Guardian监护系统是一个监控层。它不会直接生成路径，而是对Primary主系统的轨迹进行评估，以确保其符合一定的安全性和可行性标准。简而言之，Guardian监护系统会评估Primary主系统建议的行动方案是否安全可行。如果Guardian监护系统发现问题，则可以触发Primary主系统切换到Fallback备用系统，以确保车辆的安全领航行驶。\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>在决定是否刹车的二元情景中，以使用三重传感器系统为例：摄像头（“Primary”主系统）、雷达（“Guardian”监护系统）和激光雷达（“Fallback”备用系统），按多数原则进行决策：如果摄像头和雷达决策一致，就直接执行；如果不一致，就遵从激光雷达的建议，而激光雷达的建议必然会与另外两个系统其中之一的建议保持一致，确保服从多数 - 因此，PGF相当于秉持了2\u002F3多数原则。\u003C\u002Fp>\n\u003Cp>“三个子系统中的多数”这一概念只在二元决策中具有明确的定义。然而，我们在驾驶过程中需要做出的许多决策都不是二元决策。\u003C\u002Fp>\n\u003Cp>最值得注意的是，车道的几何形状并不是二元决策，而这种几何形状对责任敏感安全模型（RSS）的决策有着深远的影响。因此，我们提出了一种对多数原则的概括，称之为PGF（Primary-Guardian-Fallback）融合系统。这种融合系统遵循“Primary”主系统或“Fallback”备用系统的建议，具体取决于“Guardian”监护系统的输出。\u003C\u002Fp>\n\u003Ch3>\u003Cspan data-ccp-props=\"{}\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb241684e79737202ff86b19c995c3fb1_1732784889378.jpg\" alt=\"\" width=\"1272\" height=\"825\" \u002F>\u003C\u002Fspan>\u003C\u002Fh3>\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"font-size: 14pt;\">Transformer 效率可提高100倍\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>在目标物检测领域，通信至关重要。将图像准确输入标记化流程 - 将其转换为可解读和可处理的数据 -需要尽可能精确的执行。而要进一步提升效率，不仅需要智能的标记化过程，还需要构建一个系统，使标记能够以高效且有序的方式进行大规模相互通信，从而实现更高级别的协同处理。\u003C\u002Fp>\n\u003Cp>需要注意的是，由于单个芯片的计算要求很高，通信过程必须高效。为使芯片流畅运行，则必须优化数据流，以防止芯片性能滞后，从而导致通信速度变慢。\u003C\u002Fp>\n\u003Cp>在演讲中，Mobileye首席技术官Shai Shalev-Schwartz教授解释了Mobileye利用稀疏类型注意力（STAT）方法解决这一问题，并将Transformer效率提高100倍。稀疏类型注意力方法通过将标记组织成结构化的组来优化标记之间的通信。想象一下，成千上万人试图在一个巨大的体育场内互相交谈，必然会导致混乱。同样的概念也适用于成千上万的标记，在相同的场景下，它们很难有效地相互交流。而STAT方法正是为解决这一问题而设计的。\u003C\u002Fp>\n\u003Cp>除非将其划分为特定的角色 - 例如“常规标记”和“管理者标记” - 以创建更有组织的通信结构，或者更准确地说，是相关的连接方式。这基本上就是稀疏类型注意力背后的理念，通过改进类型和组织方式，引入结构和参数来提高模型效率。\u003C\u002Fp>\n\u003Cp>那我们是如何做到这一点的呢？我们通过用“管理者”或链接标记，对标记进行划分和分组来建立秩序，让常规标记可以独立地与链接标记（“管理者”）进行通信。例如，通过将300个常规标记与32个链接标记分组，常规标记就可以与链接标记通信，而链接标记之间也可以相互通信。这种结构化方法大大降低了复杂性，将模型效率提高了100倍。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"font-size: 14pt;\">在效率与灵活性之间寻找最佳平衡点\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Shai Shalev-Schwartz 教授阐述了芯片运行中效率和灵活性之间的平衡。简而言之，如果我们要设计只具单一内置用途的超高效芯片，那么它的效率会非常高，但同时功能也非常有限。\u003C\u002Fp>\n\u003Cp>另一方面，如果设计一款多任务处理芯片，那么它的灵活性就会很高，但其性能却不会那么高效。这就是效率和灵活性之间的基本权衡 - 尤其是对于车载芯片而言。然而，EyeQ™6 High芯片恰好能够满足自动驾驶的需求，实现了灵活性和效率之间的完美结合。\u003C\u002Fp>\n\u003Cp>为实现这一目标，EyeQ™6 High芯片内部包含了多种组件，每种组件都具有不同程度的灵活性和效率。Shai Shalev-Schwartz教授提到了五种不同架构的组件，这些组件从高度专用、高效到高度灵活，不一而足。从两种高度灵活的中央处理器 - MPC和MIPS，到高效且特定的XNN，再到介于两者之间的两种加速器，EyeQ™6 High芯片可根据操作的不同进行调整，以适用于不同的应用范围。\u003C\u002Fp>\n\u003Cp>在执行苛刻的人工智能深度学习任务时，Mobileye EyeQ6 High的效率令人印象深刻。其34 TOPS（每秒万亿次运算）的算力大大超越了前代产品EyeQ5。然而，单纯比较TOPS数字并不能完全反映其优势。\u003C\u002Fp>\n\u003Cp>衡量芯片在自动驾驶应用中有效性的真正标准，在于其在各种神经网络任务中每秒可处理帧数的能力。例如，EyeQ5每秒仅能处理91帧的像素标注神经网络，而EyeQ6 High每秒可处理超过1000帧，效率提高了十倍以上。这一升级不仅来自于更高的时钟速度，还源于XNN的专用架构，该架构针对特定应用的高效利用进行了优化。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F53a8091b10a0f6baa10a8cac1aec0a68_1732785971875.png\" alt=\"\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>例如，英伟达Orin芯片的算力可达到275 TOPS，相比之下，其原始数据可能更胜我们一筹。然而，在运行标准的ResNet-50网络时，两者的帧数处理能力差距仅为2倍。\u003C\u002Fp>\n\u003Cp>这表明，仅凭TOPS并不足以衡量芯片的有效性；环境和效率才是关键。总体而言，EyeQ6High的设计侧重于量身定制的功能和效率，并辅以强大的软件堆栈（在各种加速器之间优化任务分配）。从本质上讲，EyeQ6 High的真正优势在于它的智能设计。而这种为高效处理特定任务而量身定制的设计证明，单纯TOPS数据并不能反映其真正的性能。\u003C\u002Fp>\n\u003Cp>总而言之，Mobileye在人工智能领域的专业技术与为提高效率而优化的专用硬件相结合，为实现区域可扩展的自动驾驶技术开辟了一条清晰的道路。随着我们不断获得突破，我们正一步步实现完全自动驾驶的未来愿景。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-11-27T08:00:00.000Z",[6,21,27],{"id":261,"type":141,"url":262,"title":263,"description":264,"primary_tag":113,"author_name":265,"is_hidden":96,"lang":132,"meta_description":264,"image":266,"img_alt":267,"content":268,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":269,"tags":270},279,"the-mobileye-safety-methodology-for-fully-autonomous-driving","Mobileye 高等级驾驶自动化系统安全架构方法论","我们的高等级驾驶自动化系统安全架构方法论以基本原则和行业标准为基础，旨在降低不同类型的风险。","Prof. Shai Shalev-Shwartz and Prof. Amnon Shashua","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F114f82911350ead2e8d23f09ea3935a9_1732626715488.jpg","图片来源：大众汽车集团","\u003Cp>就自动驾驶而言，怎样才算足够安全？\u003C\u002Fp>\n\u003Cp>迄今为止，即使全球已有数以千计的自动驾驶汽车上路行驶，且自动驾驶汽车的商业化也指日可待，自动驾驶的安全问题仍然悬而未决。目前的一个关键基准指标是平均故障间隔时间（MTBF）- 从根本上说，该指标可确定在事故或伤害发生的频率方面，自动驾驶系统的水平是否优于普通人类？这一指标极易掌握和测量，但仔细研究就会发现其局限性——违规和粗心驾驶严重影响人类的统计数据，而自动驾驶系统不可能酒驾，也不会在开车时向他人发短信。更重要的是，衡量人类驾驶的标准不仅是事故，而且应该包括避免鲁莽行为 – 即：对自己和其他道路使用者承担谨慎驾驶的责任，避免不合理的风险。因此，我们认为，虽然足够高的平均故障间隔时间至关重要，但它并不足以证明自动驾驶系统的安全性。\u003C\u002Fp>\n\u003Cp>经过多年的突破性发展，如今，Mobileye及整个行业对完全自动驾驶的安全要求有了更清晰的认识。在发布的一篇新论文中，我们介绍了一个旨在大规模部署安全自动驾驶系统的框架。该框架基于两大关键原则：\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\n\u003Cp>系统的总体平均故障间隔时间应至少与针对人类的数据一样好。\u003C\u002Fp>\n\u003C\u002Fli>\n\u003Cli>\n\u003Cp>系统应消除不合理风险，同时使自动驾驶系统提供商明确界定合理与不合理风险的边界。\u003C\u002Fp>\n \u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>第一项要求使用平均故障间隔时间作为指标，解决了底线问题 —— 自动驾驶车辆所造成的伤害不得超过人类驾驶车辆所造成的伤害。然而，这还不够，因此我们补充了第二项要求 —— 消除不合理风险。该要求使用调整后的平均故障间隔时间指标，其中包含了透明度、问责制和遵守严格安全标准等原则。\u003C\u002Fp>\n\u003Cp>第二项要求的难点在于：如何严格界定“合理”与“不合理”风险之间的边界，以及如何制定消除不合理风险的方法论。有关我们具体实施的技术细节，请阅读我们的\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Ffiles\u002FSDS_Safety_Architecture.pdf\">论文\u003C\u002Fa>。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-11-26T08:00:00.000Z",[6,21,114],{"id":272,"type":100,"url":273,"title":274,"description":275,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":275,"image":276,"img_alt":277,"content":278,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":279,"tags":280},277,"lyft-and-mobileye-team-up-to-enable-autonomous-mobility-at-scale","Lyft携手Mobileye推动自动驾驶出行服务规模化发展","Lyft与Mobileye宣布合作计划，旨在助力行业领先的车队运营商推动自动驾驶汽车出行服务的广泛商业化进程。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3b2365766871f66fc014d639f6d51eac_1730848606995.jpg","Lyft and Mobileye ","\u003Cp>11月6日 —— 北美最大的网约车公司之一Lyft（纳斯达克股票代码：LYFT）与领先的自动驾驶技术和高级驾驶辅助系统（ADAS）提供商Mobileye（纳斯达克股票代码：MBLY）今日宣布将联手合作，助力行业领先的车队运营商推动自动驾驶汽车出行服务的广泛商业化进程。\u003C\u002Fp>\n\u003Cp>Mobileye将最新的人工智能技术进展应用于自动驾驶领域，为一众专用车辆制造商提供自动驾驶技术，使其能够将Mobileye的先进技术整合到自动驾驶功能就绪车辆中，以供车队运营商及运输服务提供商直接采买。Lyft选择与Mobileye联手，旨在基于自身在北美网约车服务市场的领先地位以及每年4000万的庞大用户基础，为搭载Mobileye Drive™的自动驾驶车队提供无缝需求平台。\u003C\u002Fp>\n\u003Cp>此次合作主要面向期望未来在北美各大都市地区部署和管理大规模车队的自动驾驶汽车运营商，使其能够从车辆制造商处采买搭载了Mobileye Drive™并能直接接入Lyft服务的车辆，通过Lyft接取用户出行订单，并优化车队的利用率和盈利能力。\u003C\u002Fp>\n\u003Cp>两家公司还计划利用Mobileye最新的云基础自动驾驶汽车需求技术，使搭载了Mobileye Drive™的车辆与自动驾驶车队运营商互联互通。通过Mobileye的一站式自动驾驶汽车生态系统和Lyft的自动驾驶汽车合作伙伴API套件，自动驾驶车队有望变现盈利，为Lyft用户提供更快速、更广泛的自动驾驶汽车出行服务。\u003C\u002Fp>\n\u003Cp>Lyft首席执行官David Risher表示：“Mobileye的全栈技术是让自动驾驶车队接入Lyft网络的重要一环。每年有4000万用户通过Lyft出行，随着服役的自动驾驶汽车越来越多，我们将全力打造一个平台，让车队所有者能够满怀信心地将资产投入运营。在通往自动驾驶未来的道路上，我们非常欢迎Mobileye加入，成为我们重要的战略合作伙伴。”\u003C\u002Fp>\n\u003Cp>Mobileye总裁兼首席执行官Amnon Shashua教授表示：“与领先的出行服务提供商和运营商合作是推动自动驾驶出行服务落地的关键之举。将Mobileye Drive™与Lyft在北美地区每年4000万的庞大用户网络相结合，有助于我们的自动驾驶汽车客户通过自动驾驶服务进入新的市场和地区，在发挥自身技术优势的同时，构建可持续发展的业务模式。”\u003C\u002Fp>\n\u003Cp>此次合作是Mobileye实现“为全球乘客提供自动驾驶出行服务”这一雄心壮志中的又一重要里程碑。通过与网约车服务商、车辆运营商和汽车制造商合作，Mobileye已为欧洲和北美的各大“出行即服务”项目提供了自动驾驶汽车技术支持。目前，德国、挪威、克罗地亚和美国的多家出行服务运营商正针对搭载Mobileye Drive™的车辆开展试点。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-11-06T08:00:00.000Z",[21,64,99],{"id":282,"type":141,"url":283,"title":284,"description":285,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":285,"image":286,"img_alt":287,"content":288,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":289,"tags":290},268,"mobileyes-imaging-radar-takes-the-wheel","Mobileye 成像雷达引领行业潮流","Mobileye 的成像雷达开创了全新类别","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Faf7696dab443a2b5d1483cef50715beb_1720082783552.jpg","\"Unlike traditional radar systems, Mobileye’s imaging radar has more detailed object detection capabilities\"","\u003Cp>Today, hands-free (but eyes-on) autonomous driving solutions are possible with cameras-only. However, as the mobility industry advances towards more and more autonomous capabilities, key challenges such as reliability and accuracy within intricate driving environments remain. Overcoming them pushes the industry to seek appropriate solutions that prioritize safety for passengers and pedestrians, while also ensuring vehicles can assist drivers and eventually operate independently.  \u003C\u002Fp>\n\u003Cp>To achieve safe autonomous driving capabilities, some in the industry agree that additional sensing modalities beyond cameras are necessary. Mobileye’s approach, known as True Redundancy™, relies on Lidars and Mobileye’s new category of Imaging Radars to create a sensing state that operates independently from the camera-based sensing state.  This allows for different sensor configurations that enhance autonomous capabilities and road safety.  In this approach, our radar technology is emerging as a key tool in enabling autonomous features.  \u003C\u002Fp>\n\u003Cp>On the road, traditional ADAS\u003Cspan class=\"NormalTextRun SCXW236082798 BCX0\"> (Advanced Driving Assistance Systems)\u003C\u002Fspan> radars are effective in simple, less dense environments as they provide sparse information on dynamic objects, but they face challenges in detecting static objects. To overcome these challenges, Mobileye developed its new category of radars that delivers reliable output independently of cameras or lidars. This innovation supports the core principles of the \"True Redundancy\" architecture.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fb3WSAYguMaY?si=gnhNwvXMLpvj3M-g\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe> \u003Cbr \u002F> Radar Technology: From Basic ADAS to Reliable Autonomous Driving, VP Radar Yaniv Avital\u003C\u002Fh6>\n\u003Ch3>Mobileye’s sense \u003C\u002Fh3>\n\u003Cp>From its inception, the Mobileye imaging radar was purposefully designed for autonomous driving capabilities to achieve an AV system that outperforms human perception and decision-making on the road. This advanced imaging has a higher level of dynamic range than traditional radars in challenging scenarios, such as the ability to detect a child 150 meters away on a road when a bus is only 10 meters from the vehicle.  \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ffb0dae917e686f8e58cf1218bfa02486_1720083684181.jpg\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003Cbr \u002F>\"Mobileye developed its new category of radars that delivers reliable output independently of cameras or lidars\" \u003C\u002Fh6>\n\u003Cp>Unlike traditional radar systems with limited levels of object detection, Mobileye’s imaging radar has more detailed object detection capabilities with heightened elevational resolution. This precise detection enables the system to discern objects in unique scenarios, such as stationary vehicles under a bridge. It generates a rich point cloud that facilitates AV driving capabilities such as exact lane assignment and the ability to react quickly at high speeds. The system can detect road users- pedestrians, motorcycles, and cyclists- at a distance of 350 meters and identify potential hazards up to 230 meters away.  \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F3onQ-ZLadOU?si=pbzXFW6ENHC6v3lh\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe> \u003Cbr \u002F>Mobileye's Imaging Radar fits perfectly with the VW ID Buzz, VP of Autonomous Vehicles Johann Jungwirth  \u003C\u002Fh6>\n\u003Ch3>A radar that hits the mark \u003C\u002Fh3>\n\u003Cp>The automotive industry is experiencing a profound shift in radar aimed at advancing and enhancing current capabilities. The Mobileye Radar portfolio features high angular resolution, expansive dynamic range, and substantial sidelobe suppression, enabling detection in challenging situations. This ensures reliable detection of small and low-reflective objects on the highway while driving up to 130km\u002Fhours. The development of the Mobileye imaging radar comes as a commitment from Mobileye to shape the future of the automotive industry by consistently innovating and introducing new categories of expertise.  \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-07-10T07:00:00.000Z",[27,21,84],{"id":292,"type":100,"url":293,"title":294,"description":295,"primary_tag":33,"author_name":131,"is_hidden":96,"lang":132,"meta_description":295,"image":296,"img_alt":297,"content":298,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":5,"publish_date":299,"tags":300},267,"verne-unveils-urban-mobility-service-driven-by-mobileye","Verne推出由Mobileye赋能的城市出行服务","在Rimac 园区举办的活动展示了极具特色的汽车设计，以及由 Mobileye Drive™ 赋能的自动驾驶平台、服务理念以及功能。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb190119bb4ff513af98a9e27a3d9ea6d_1719345826270.jpg","Introducing Verne, a new urban autonomous mobility ecosystem using the Mobileye Drive™ platform.","\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">Zagreb, Croatia, June 26, 2024\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-contrast=\"none\"> - Verne, a redefined approach to urban autonomous mobility in cities, has been introduced. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Founded by Mate Rimac and two of his closest colleagues and friends from Rimac Group - Marko Pejković, now CEO of Verne, and Adriano Mudri, the designer of Nevera and Chief Design Officer at Verne.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">A collaboration with Mobileye, a world leader in autonomy, enables Verne’s autonomous capabilities. The vehicle will be fully autonomous, with a system capable of driving in dynamic urban traffic. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">For the past several years, the company has been cooperating with Mobileye. Mobileye's advanced AD platform Mobileye Drive™, will be integrated into the purpose-built Verne vehicle and together with a sophisticated sensor set of cameras, radar and lidar enable the automated driving capabilities. The platform is designed to be highly flexible and scalable, to meet the demands of autonomous driving in a variety of locations, on different road types, under varying weather conditions and even taking local driving styles into account, within its operational design domains. All of this is crucial for Verne’s future plans.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">“Around the world, the promise and benefits of autonomous vehicles to road safety and accessibility have started to come into focus,” said Johann “JJ” Jungwirth, Executive Vice President, Autonomous Vehicles at Mobileye.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003Cspan data-contrast=\"none\">“Verne’s innovative new vehicle platform and ecosystem reflect the potential autonomous mobility has to change our expectations of personal transportation. Only with a system like Mobileye Drive™, that’s built for scalability would something like this be possible, and we’re proud to work with Verne on this program.”\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"134233117":false,"134233118":false,"201341983":0,"335559738":0,"335559739":160,"335559740":276}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Named after Jules Verne, the author who imagined humanity's potential through amazing journeys, Verne was formerly known as P3 Mobility. The collaboration with Mobileye was first \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-and-project-3-mobility-announce-collaboration-for-scalable-urban-autonomous-mobility-project\u002F\">\u003Cspan data-contrast=\"none\">announced\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> in February 2024.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">\u003Cspan class=\"TextRun SCXW233002470 BCX8\" lang=\"EN-GB\" xml:lang=\"EN-GB\" data-contrast=\"none\">\u003Cspan class=\"NormalTextRun SCXW233002470 BCX8\">Visit \u003Ca href=\"https:\u002F\u002Fwww.letsverne.com\u002Fmedia\u002Fverne-journey-to-the-future-of-mobility\">letsverne.com\u003C\u002Fa> to learn more. \u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>","2024-06-26T07:00:00.000Z",[21,34,99],{"id":302,"type":141,"url":303,"title":304,"description":305,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":305,"image":306,"img_alt":307,"content":308,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":309,"tags":310},265,"mobileye-drive-hits-the-road-with-deutsche-bahn","搭载Mobileye Drive™的德国铁路(Deutsche Bahn)车辆开启L4级自动驾驶路测","Mobileye 自动驾驶汽车平台通过了德国公共交通道路测试的严格法规要求","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Faa49509be5d446c6917a5cf97eb4bb85_1719229227061.jpg","Photo: RMV\u002FDB\u002FLandwehr","\u003Cp>In a big push towards an autonomous future, Mobileye's fully autonomous no-driver system (also known as L4) has been \u003Ca href=\"https:\u002F\u002Fwww.deutschebahn.com\u002Fde\u002Fpresse\u002Fpressestart_zentrales_uebersicht\u002FPionierprojekt-KIRA-startet-mit-autonomen-Fahrzeugen-fuer-den-OePNV--12926526\" target=\"_blank\" rel=\"noopener\">announced\u003C\u002Fa> for in-traffic testing in Germany. The Mobileye Drive™ platform was introduced by the country’s Deutsche Bahn (DB) aboard six on-demand shuttles (with no passengers at this point) in Darmstadt and Offenbach in the Rhine-Main area. The KIRA project, as it's called, plans to utilize Mobileye Drive to expand on-demand shuttle service, and to further include rural areas into the Rhein-Main-Verkehrsverbund (RMV) service area. \u003C\u002Fp>\n\u003Cp>This accomplishment speaks volumes to Mobileye’s software and hardware abilities, since the platform had to clear Germany’s \u003Ca href=\"https:\u002F\u002Fwww.kba.de\u002FEN\u002FThemen_en\u002FTypgenehmigung_en\u002FAutonomes_automatisiertes_Fahren_en\u002Fnationale_Betriebserlaubnis_en\u002Fnationale_betriebserlaubnis_node_en.html\" target=\"_blank\" rel=\"noopener\">“national type approval for motor vehicles with a fully automated driving function,”\u003C\u002Fa> or AFGBV, a regulation process that standardizes AV testing and could be used as a blueprint for regulators and institutions beyond Germany.  \u003C\u002Fp>\n\u003Cp>It is worth noting that Mobileye Drive is designed as a “one-size-fits-most\" platform, meaning its agnostic nature allows it to work in different ODDs in certain circumstances. Combined with its regulatory success so far, the platform could be attractive for various projects, as demonstrated by this recent progress as well as by the March announcement of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fvolkswagen-admt-announces-agreement-with-mobileye-for-autonomous-driving\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye and VW’s collaboration on the ID Buzz\u003C\u002Fa>, and by the number of European local governments and providers who are eyeing the platform as a way of reshaping mobility in their cities. Parking congestion, pollution, and ill-suited public transportation services are just a few causes for the growing interest in AV solutions such as Mobileye Drive.  \u003C\u002Fp>\n\u003Ch3>A track record shaping the future \u003C\u002Fh3>\n\u003Cp>The DB collaboration is far from the first time Mobileye's solutions have passed rigorous regulations, and in some cases, it has helped shape the industry’s expectations. Based on extensive research and experience, Mobileye delivers more than its hardware\u002Fsoftware know-how, it also offers a record of fulfilling OEMs’, regulators’, policy makers’ and end users’ demands and expectations, doing so in a manner that is safe, cost-effective and scalable.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F033ee1c99dc649bb62512b0a54c2970e_1719214588031.jpg\" alt=\"Photo: “RMV\u002FDB\u002FLandwehr”\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch6>Photo: RMV\u002FDB\u002FLandwehr\u003C\u002Fh6>\n\u003Cp>In early 2024 it was announced that Mobileye Drive will begin \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-and-project-3-mobility-announce-collaboration-for-scalable-urban-autonomous-mobility-project\u002F\" target=\"_blank\" rel=\"noopener\">testing and validation in Zagreb, Croatia\u003C\u002Fa> as part of a collaboration with local company Project 3 Mobility. It has also been tested on the streets of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fvolkswagen-commercial-vehicles-begins-av-testing-with-mobileye-drive\u002F\" target=\"_blank\" rel=\"noopener\">Munich and Austin\u003C\u002Fa> as part of Mobileye's work with the VW group. The company also reinforced our commitment to the highest level of safety regulation at \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-at-ncap24-centering-on-safety\u002F\" target=\"_blank\" rel=\"noopener\">the first Global NCAP Forum\u003C\u002Fa>. So, as the demand from consumers, automakers and regulators for safe mobility solutions constantly grows, Mobileye delivers essential capabilities that drive the automotive industry forward. \u003C\u002Fp>\n\u003Ch3>Street level autonomous MaaS  \u003C\u002Fh3>\n\u003Cp>Autonomous mobility-as-a-service (MaaS) solutions operating on the street, such as on-demand shuttles, have an important role in the future of mobility. Public transport operators and authorities aspire to offer greater access to mobility to more people through cost-efficient services, despite a growing scarcity of drivers. These are pains autonomous MaaS could help alleviate. \u003C\u002Fp>\n\u003Cp>Communities often look for innovative ideas that could reinvigorate public mobility services within their borders while also satisfying regulators’ demands. Mobileye’s progress in Germany reflects an ambitious vision, reimagining how people travel, which is turning into a reality.  \u003C\u002Fp>","2024-06-25T07:00:00.000Z",[34,21,99,78],{"id":312,"type":141,"url":313,"title":314,"description":315,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":315,"image":316,"img_alt":317,"content":318,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":319,"tags":320},263,"maas-for-av-day","深入探究“出行即服务”(Mobility as a Service)","Mobileye如何改变我们的出行方式","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7ba4fe7b30605759e4dd694b95d8b6b3_1717068889627.jpg","“也许是时候将手从方向盘上移开，并托付于自动驾驶出行的愿景了”","\u003Cp>人们热爱旅行、探索和发现。我们经常想象在未来场景下，我们只需设定好路线，然后便可抵达目的地。随着技术的进步和生活方式的改变，也许是时候将手从方向盘上移开，并托付于自动驾驶出行的愿景了。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>“出行即服务”(MaaS) 和自动驾驶\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>自动驾驶系统正在改变我们的通勤和出行方式，以及对公共空间的体感。然而，在探讨穿梭于城市和街道的未来出行时，我们必须将其与今天所熟知的MaaS区分开来。因为目前的公共交通服务、网约车或物流配送服务，都仍然需要由人类来操控。\u003C\u002Fp>\n\u003Cp>就Mobileye而言，我们并不是重造公共交通或出租车，而是在努力使它们实现自动驾驶。我们创新的专有技术和过往久经考验的业绩记录，\u003Cstrong>都可支持现有出行服务实现无人驾驶\u003C\u002Fstrong>，并提高现有基础设施的安全性、成本效益以及可扩展性。可以说，Mobileye不是通过重新发明方向盘，而是依靠经过测试和验证的出行概念 (如“最后一公里”接驳车) ，来解决出行问题的。同时，我们还与不同背景的出行专家合作，共同推动出行愿景的实现。\u003C\u002Fp>\n\u003Cp>目前，Mobileye已经确立了在该领域的核心地位，能够联合汽车主机厂、交通运营商和政府部门通力合作，响应所有参与方的需求，同时始终考虑终端用户，确保其从中获益。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fcce12f287c437a3e728459b62909cc59_1717069139023.png\" alt=\"\" width=\"600\" height=\"389\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>驾驶解决方案 \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>Mobileye Drive™\u003C\u002Fstrong>是Mobileye推出的\u003Cstrong>用于公共交通的完全自动驾驶系统\u003C\u002Fstrong>，该系统是Mobileye拥有进一步重塑出行潜力的重要例证。与我们的其他平台和技术一样，Drive系统满足严格的法规和测试要求，甚至在某些情况下，凭借我们丰富的知识能力，还能可以帮助和提升行业期望的标准。\u003C\u002Fp>\n\u003Cp>该平台的“通用”性特点使其能够在不同地区、不同车型上运行，以帮助解决许多城市和社区面临的各类问题。2024年初，Mobileye宣布，Mobileye Drive™将在克罗地亚萨格勒布与当地的Project 3 Mobility公司合作开展测试。此外，作为Mobileye与大众汽车集团合作的一部分，Mobileye Drive™还在慕尼黑和德克萨斯州奥斯汀的道路上进行了测试，并在奥斯陆与Ruter和Holo合作开展了测试。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan class=\"TextRun SCXW183597323 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\">\u003Cspan class=\"NormalTextRun SCXW183597323 BCX0\">自动驾驶的深远影响 \u003C\u002Fspan>\u003C\u002Fspan>\u003Cspan class=\"EOP SCXW183597323 BCX0\" data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>全球的大城市间有诸多相似之处：人口众多、拥有大规模的基础设施系统、公共教育体系和促进文化繁荣的各种场所。然而，随着上世纪城市的发展，城市居民对汽车的依赖性也在增加，进而导致了道路日益拥堵、环境污染加剧、驾驶安全系数不断降低等问题。与此同时，每个城市也有其个性所在，无论是大都市、城镇或乡村都有其与众不同的特点和需求。在应对这些挑战时，出行方式也必须不断发展，否则将会成为城市发展的障碍。通过\u003Cstrong>为MaaS基础设施提供自动驾驶解决方案\u003C\u002Fstrong>，我们将重塑任意畅行的出行方式。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>","2024-05-31T07:00:00.000Z",[78,27,64,21],{"id":322,"type":141,"url":323,"title":324,"description":325,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":325,"image":326,"img_alt":327,"content":328,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":329,"tags":330},262,"when-we-say-consumer-av","消费级自动驾驶汽车是指什么？","消费级自动驾驶汽车不仅仅是能够实现自动驾驶的汽车，它还可以提供一系列可能我们可能根本没有意识到的功能。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0b9fbe78808b5e1596844c568893f989_1716204022667.png","作为一款“可脱手\u002F可脱眼” 系统，Mobileye Chauffeur™意味着我们向完全自动驾驶更进一步。","\u003Cp>\u003Cspan style=\"font-size: 12pt;\">谈起自动驾驶汽车，很多人脑中浮现的是在电影或电视上看到的场景：汽车自动行驶在路上，而主人公坐在车内望向窗外出神，亦或在打盹，反正根本不关心路况。汽车自身保持着行驶状态，而且经常是以高速在行进，有时甚至会悬浮于空中，可能车上没有方向盘，或是可能车内与人在讨论。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Csection>\n\u003Csection>\n\u003Csection>\n\u003Csection>\n\u003Csection>\n\u003Csection>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">科幻片中的自动驾驶汽车为我们描绘了一个美妙的未来，这是一种非常奏效的叙事手段，但对于一项复杂的技术来说，这种呈现方式未免过于单一。银幕上的这些车辆根本没有体现出自动驾驶解决方案的核心价值 - 汽车不是独立在工作，与驾驶者也不存在对抗关系，是人类与机器共同努力的成果。\u003C\u002Fspan>\u003C\u002Fp>\n\u003C\u002Fsection>\n\u003C\u002Fsection>\n\u003C\u002Fsection>\n\u003C\u002Fsection>\n\u003C\u002Fsection>\n\u003C\u002Fsection>\n\u003Ch3>\u003Cspan style=\"font-size: 12pt;\">\u003Cstrong>人机之间：谁是老大？\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fh3>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">自动驾驶的概念包括多个级别。美国汽车工程师学会（SAE）将其细分为L0（全手动驾驶）到L5（全场景下完全自动驾驶），但自从Amnon Shashua教授提出新的分类标准后，大众更容易通过简单的观察来理解这一概念，这件事就是“谁监督谁”？\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">值得注意的是，使得道路更加安全的自动驾驶功能其实已经存在多年。我们的汽车可以防止驾驶员偏离车道，可以在紧急情况下制动，并提醒我们减速。虽然我们双手握在方向盘上，眼睛注视着道路，但在某种程度上，汽车会在我们驾驶时实时进行监督，并在必要时采取行动。Mobileye高级驾驶辅助系统（ADAS）和云增强驾驶辅助系统（Cloud-Enhanced Driver-Assist™ ）可以让汽车或被动或主动地干预我们的驾驶行为。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">ADAS的终极进化版，也是自动驾驶分类中的下一个级别，开始颠覆驾驶员与汽车之间的角色划分。对应的解决方案是Mobileye SuperVision™，它是一个 “可脱手\u002F需注视” 的平台，意味着在指定的设计运行范围（ODD）内驾驶和操控汽车时，驾驶员需要关注路况并监督车辆。借助该平台的11个摄像头和Mobileye的专有技术，驾驶员可以坐在驾驶位，只在必要时参与驾驶，同时观察路况并监控ODD内的驾驶情况。一些汽车制造商已经基于SuperVision平台为车主提供了高速场景下“可脱手\u002F需注视”的服务，城区场景也将很快跟上。最近，大众汽车集团宣布将加强与Mobileye的合作，双方将基于SuperVision平台，把更多自动驾驶功能引入至量产车项目中。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>\u003Cspan class=\"TextRun SCXW6534606 BCX0\" lang=\"EN-US\" style=\"font-size: 12pt;\" xml:lang=\"EN-US\" data-contrast=\"auto\">\u003Cspan class=\"NormalTextRun SCXW6534606 BCX0\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0b9fbe78808b5e1596844c568893f989_1716204022668.png\" alt=\"\" width=\"1000\" height=\"388\" \u002F>\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fh3>\n\u003Ch3>\u003Cspan class=\"EOP SCXW6534606 BCX0\" style=\"font-size: 12pt;\" data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":279}\">\u003Cstrong>人机协同，赢得时间\u003C\u002Fstrong> \u003C\u002Fspan>\u003C\u002Fh3>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">除 Mobileye SuperVision 外，大众集团还将 Mobileye Chauffeur™平台应用至其量产车中。作为一款“可脱手\u002F可脱眼”系统，Chauffeur 代表着向完全自动驾驶更进一步。采用 Chauffeur 平台，驾驶员和汽车之间的协同作用和信任度大大提高，因为在 ODD 特定区域和道路（如高速公路和上下匝道）上，驾驶员无需关注路况，可将注意力放在其他事务上，从而赢得时间，同时，在汽车发出需要注意信号时，也可以随时介入。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ciframe src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F935584586?h=960d25a662\" width=\"640\" height=\"360\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" data-mce-fragment=\"1\">\u003C\u002Fiframe>\u003Cspan style=\"font-size: 10pt;\">“我们想做一些消费者能够理解的产品，所以首要问题是由谁驾驶？”Shai Shalev-Shwartz教授在彭博社人工智能大会上如此解释自动驾驶汽车的人机协同。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">Mobileye Chauffeur 凭借上述各项技术，成为了一款物有所值的消费级自动驾驶系统，可在各种道路类型和地区运行，适用于不同车型，并已准备好投放至市场。采用这款系统，汽车制造商可以选择通过定制自动驾驶体验的某些要素，来保留其独特品牌和声誉，并保持其原有驾驶风格；同时，得益于 Mobileye REM™技术，这些功能不受地域限制。此外，两个互为备份的独立系统（一个摄像头子系统和一个雷达\u002F激光雷达子系统）为Mobileye真正冗余（True Redundancy™）的方法赋能。将这些元素结合起来就可以模拟其他道路使用者的驾驶风格，打造更高水平的安全自动驾驶体验。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 12pt;\">这种新水平的协同作用赋予了驾驶员（支配时间）和汽车（支配驾驶）的自主能力。表明了自动驾驶并不仅仅是银幕上可以自行驾驶的未来汽车，还是汽车和驾驶员在驾驶过程中相互协助、相互配合、相互监督、确保行程安全的一系列能力。 \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-05-20T07:00:00.000Z",[21,27],{"id":332,"type":141,"url":333,"title":334,"description":335,"primary_tag":5,"author_name":336,"is_hidden":96,"lang":132,"meta_description":335,"image":337,"img_alt":338,"content":339,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":340,"tags":341},261,"autonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology","自主决策：自动驾驶技术中的偏差-方差权衡","大语言模型和自动驾驶应用中，单一人工智能系统与复合人工智能系统的比较","Prof. Amnon Shashua and Prof. Shai Shalev-Shwartz","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff8167f28d4d800bd54b3e04c9fda5a5d_1715717822589.jpg","Monolithic versus compound AI systems in LLMs and autonomous driving.","\u003Cp>Back in November 2022, the release of ChatGPT garnered widespread attention, not only for its versatility but also for its end-to-end design. This design involved a single foundational component, the GPT 3.5 large language model, which was enhanced through both supervised learning and reinforcement learning from human feedback to support conversational tasks. This holistic approach to AI was highlighted again with the launch of Tesla’s latest FSD system, described as an end-to-end neural network that processes visual data directly “from photons to driving control decisions,\" without intermediary steps or “glue code.\" \u003C\u002Fp>\n\u003Cp>While AI models continue to evolve, the latest generation of ChatGPT has moved away from the monolithic E2E approach. Consider the following example of a conversation with ChatGPT:\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fchatgpt_blog2.png\" alt=\"\" width=\"746\" height=\"448\" \u002F>\u003C\u002Fp>\n\u003Cp>When asked to compute \"what is 3456 * 3678?,\" the system first translates the question into a short Python script to perform the calculation, and then formats the output of the script into a coherent natural language text. This demonstrates that ChatGPT does not rely on a single, unified process. Instead, it integrates multiple subsystems—including a robust deep learning model (GPT LLM) and separately coded modules. Each subsystem has its defined role, interfaces, and development strategies, all engineered by humans. Additionally, 'glue code' is employed to facilitate communication between these subsystems. This architecture is referred to as “\u003Ca href=\"https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\" target=\"_blank\" rel=\"noopener\">Compound AI Systems\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn1\">\u003Csup>1\u003C\u002Fsup>\u003C\u002Fa>” (CAIS).\u003C\u002Fp>\n\u003Cp>Before we proceed, it is crucial to dispel misconceptions about which system architecture is \"new\" or \"traditional\". Despite the hype, the E2E approach in autonomous driving is not a novel concept; it dates back to \u003Ca href=\"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F1988\u002Ffile\u002F812b4ba287f5ee0bc9d43bbf5bbe87fb-Paper.pdf\" target=\"_blank\" rel=\"noopener\">the Alvinn project (Pomeraleau, 1989)\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn2\">\u003Csup>2\u003C\u002Fsup>\u003C\u002Fa>. The CAIS approach is also not new, but as we have shown above, it has been adopted by the most recent versions of ChatGPT.\u003C\u002Fp>\n\u003Cp>\u003Cem>This blog aims to explore the nuances between E2E systems and CAIS, by drawing a deep connection to the \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FBias–variance_tradeoff\" target=\"_blank\" rel=\"noopener\">\u003Cem>bias-variance tradeoff\u003C\u002Fem>\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn3\">\u003Cem>\u003Csup>3\u003C\u002Fsup>\u003C\u002Fem>\u003C\u002Fa>\u003Cem> in machine learning and statistics. For concreteness, we focus the discussion on self-driving systems, but the connection is applicable more generally to the design of any AI-based system.\u003C\u002Fem>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The bias-variance tradeoff\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The grand question, driving any school of thought for building a data-driven system, is the \"bias\u002Fvariance\" tradeoff. Bias, also known as “approximation error,\" means that our learning system cannot reflect the full richness of reality. Variance, also known as “generalization error,\" means that our learning system overfits to the observed data, and fails to generalize to unseen examples.\u003C\u002Fp>\n\u003Cp>The total error of the learned model is the sum of the approximation and generalization errors, so in order to reach a sufficiently small error, we need to delicately control both. There is a tradeoff between the two terms since we can decrease the generalization error by restricting the learned model to come from a specific family of models, but this might introduce a bias if the chosen family of models cannot reflect the full richness of reality.\u003C\u002Fp>\n\u003Cp>Based on this background, we can formalize the two approaches for building a self-driving system. A CAIS, or an “engineered system,\" deliberately puts architectural restrictions on the self-driving system for the sake of reducing the generalization error. This introduces some bias. For example, going from \"photons\" to a “sensing state,\" which is a model of reality surrounding the host vehicle—location and measurements of road users, roadway structures, drivable paths, obstacles and so forth—and from there to control decisions introduces bias. The reason for this bias is that the sensing state might not be rich enough to reflect reality to its fullest and therefore the capacity of the system is constrained. In contrast, an E2E network skipping the sensing state step and instead mapping incoming videos directly to vehicle control decisions would not suffer from this bias of the “sensing state abstraction.\" On the other hand, the E2E approach will have a higher generalization error, and the approach advocated by the E2E proponents is to compensate for this error with huge amounts of data, which in turn necessitates a huge investment in compute, storage, and data engines.\u003C\u002Fp>\n\u003Cp>To recap, the E2E approach – in the simplistic form being communicated to the public – is to define a system with zero bias while incrementally reducing variance through volumes of data for training the system with the purpose of gradually eliminating all “corner cases\". In an engineered approach, on the other hand, the system starts with a built-in bias due to the abstraction of the sensing state and driving policy while (further) reducing variance through data fed into separate subsystems with a high-level fusion glue-code. The amount of data required for each subsystem is exponentially smaller than the amount of data required for a single monolithic system.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The devil is in the AI details\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The story, however, is more delicate than the above dichotomy. Starting from the bias element, it’s not that E2E systems will have zero bias—since the neural network resides on an on-board computer in the car, its size is constrained by the available compute and memory. Therefore, the limited compute available in a car introduces bias. In addition, the approximation error of a well-engineered approach is not necessarily excessively large for several reasons. For one, Waymo is clear evidence that the bias of an engineered system is sufficiently small for building a safe autonomous car. Moreover, in a well-engineered system we can add a subsystem that skips some of the abstractions (e.g., the sensing state abstraction) and thus further reduce the bias in the overall system.\u003C\u002Fp>\n\u003Cp>The variance element is also more nuanced. In an \"engineered\" system, the variance is reduced through abstractions (such as sensing state) as well as through the high-level fusion of multiple subsystems. In a pure E2E system, the variance should be reduced only through more and more data. But this process of reducing variance through a data pipeline deserves more scrutiny. Take the notion of mean time between failures (MTBF) and let's assume that failures are measured by critical interventions. Let's take MTBF as a measure of readiness of a self-driving vehicle to operate in an \"eyes-off\" manner. In Mobileye's engagement with car makers the MTBF target is 10\u003Csup>7\u003C\u002Fsup> hours of driving. Just for reference, \u003Ca href=\"https:\u002F\u002Fwww.teslafsdtracker.com\u002Fhome\" target=\"_blank\" rel=\"noopener\">public data\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn4\">\u003Csup>4\u003C\u002Fsup>\u003C\u002Fa> on Tesla's recent V12.3.6 version of FSD stands around 300 miles per critical intervention which amounts to an MTBF of roughly 10 hours – which is 6 orders of magnitude away from the target MTBF. Let's assume that somehow the MTBF has reached 10\u003Csup>6\u003C\u002Fsup> hours and we wish merely to improve it by one order of magnitude in order to reach 10\u003Csup>7\u003C\u002Fsup> hours. How much data would we need to collect? This is a question about the nature of the long tail of a distribution. To make things concrete, assume we have 1 million vehicles on the road driving one hour per day and the data in question is event-driven—i.e., when an intervention of the human driver occurs then a recording of some time around the event is being made and sent to the car maker for further training. An intervention event represents a \"corner case\" and the question of the long tail is how those corner cases are distributed. Consider the following scenario where B is the set of “bad” corner cases. An example of a heavy tail distribution is when B = {b_1,...,b_{1000}} and the probability of b_i to occur is 10\u003Csup>-9\u003C\u002Fsup> for every i. Even if we assume that when a corner case is discovered then we can somehow retrain the network and fix that corner case, without creating any new corner cases, we must knock off around 900 corner cases so that P(B) = 10\u003Csup>-7\u003C\u002Fsup>. Because the MTBF is 10\u003Csup>6\u003C\u002Fsup> then we encounter one corner case per day. It follows that we will need around 3 years to get this done. The point here is that no one knows how the long tail is structured - we gave one possible long tail scenario but in reality it could be worse or it could be better. As mentioned previously, while there is a precedent that the bias of an engineered system is sufficient for building a safe autonomous car (e.g. Waymo), there is still no precedent that reducing variance solely by a recurring data engine is sufficient for building a safe autonomous car.\u003C\u002Fp>\n\u003Cp>It follows that to solely double-down on a data pipeline might be too risky. What else can be done in the E2E approach for reducing variance? To lead into it lets ask ourselves:\u003C\u002Fp>\n\u003Cp>\u003Cbr \u002F>  (i) Why does Tesla FSD have a sensing state in their display? The idea of an E2E system is you go from \"photons to control\" while skipping the need to build a sensing state. Are they doing that solely for the purpose of notifying the driver what the system “sees?\" Or does it have a more tacit purpose?\u003C\u002Fp>\n\u003Cp>\u003Cbr \u002F>  (ii) Why has Tesla \u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2024\u002F5\u002F7\u002F24151497\u002Ftesla-lidar-bought-luminar-elon-musk-sensor-autonomous\" target=\"_blank\" rel=\"noopener\">purchased 2,000 lidars\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn5\">\u003Csup>5\u003C\u002Fsup>\u003C\u002Fa> from Luminar? Presumably for creating ground truth (GT) data for a supervised training. But why?\u003C\u002Fp>\n\u003Cp>The two riddles are of course related.\u003C\u002Fp>\n\u003Cp>Imagine an E2E network comprising of a backbone and two heads - one for outputting vehicle control and the other for outputting the sensing state. Such a network is still technically E2E (from photons to control) but also has a branch for sensing state. The sensing state branch needs to be trained in a supervised manner from GT data, hence the need for 2,000 lidars. The real question is whether the GT data can be created automatically without manual labeling. The answer is definitely yes because Mobileye does that. We have an \"auto-GT\" pipeline for training for sensing state. And, the reason why you would want a branch outputting the sensing state is not merely for displaying the sensing state to the driver. The real purpose of the sensing state branch is to reduce the variance (and more importantly the sample complexity of the system which is the amount of data needed for training) of the system through the \"multi-tasking\" principle. We addressed this \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1604.06915\" target=\"_blank\" rel=\"noopener\">back in 2016\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn6\">\u003Csup>6\u003C\u002Fsup>\u003C\u002Fa> and gave as an example an agricultural vehicle on the side of the road. The probability of observing a rare vehicle type somewhere in the image is much higher than the probability of observing such a vehicle immediately in front of us. Therefore, without a sensing state head (that detects the rare vehicle type on the shoulder even if it is not affecting the control of the host vehicle) one would need much more data in order to see such a vehicle immediately in front us, which affects the control of the host vehicle. What this comes to show is that the sensing state abstraction is important as it hints to the neural network that a good approach for giving correct control commands may need to understand the concept of vehicles and to detect all of the vehicles around us. Importantly, this abstraction is learned through supervised learning, using GT data which is created automatically (by a well-engineered offline system).\u003C\u002Fp>\n\u003Cp>Another component of the popular E2E narrative is \"no glue-code\" in the system. No glue-code means no bugs being entered by careless engineers. But this too is a misconception. There is glue-code – not in the neural network but in the process of preparing the data for the E2E training. One clear example is the automatic creation of GT data. Elon Musk gave such an example – that of human drivers not respecting stop signs as they should and instead perform a \u003Ca href=\"https:\u002F\u002Fwww.teslarati.com\u002Ftesla-rolling-stop-markey-blumenthal-letter-elon-musk\u002F\" target=\"_blank\" rel=\"noopener\">rolling stop\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn7\">\u003Csup>7\u003C\u002Fsup>\u003C\u002Fa>. The rolling stop events had to be taken out of the training data so that the E2E system would not adopt bad behavior (as it is supposed to imitate humans). In other words, the glue-code (and bugs) are shifting from the system code to data curation code. Actually, it may be easier to detect bugs in system code (at least there are existing methodologies for that) than to detect bugs in data curation.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Don’t get into the way of analytic solutions\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Finally, we would like to point out that when we have an analytical solution for a problem, it is certainly not better to use a purely E2E machine learning method. For example, the long multiplication exercise mentioned at the start of this blog highlights the fact that ChatGPT+, rightfully so, uses a good old calculator for the task and does not attempt to \"learn\" how to do long multiplication from a massive amount of data. In the driving policy stack (determining the actions the host vehicle should do and outputting the vehicle control commands) there are numerous analytical calculations. Knowing when to replace \"learning\" with analytical calculations is crucial for variance reduction but also for transparency, explainability and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fmobileye-dxp-as-a-novel-approach\u002F\">tuning\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn8\">\u003Csup>8\u003C\u002Fsup>\u003C\u002Fa> (imitating humans is somewhat problematic because many of them are not good drivers).\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Final words\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>AI is progressing at a remarkable pace. The revolution of foundation models of the like of ChatGPT began as a monolithic E2E model (back in 2022) whereas today it evolved into \u003Ca href=\"https:\u002F\u002Fopenai.com\u002Fchatgpt\u002Fpricing\" target=\"_blank\" rel=\"noopener\">ChatGPT+\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn9\">\u003Csup>9\u003C\u002Fsup>\u003C\u002Fa> which represents an engineered solution built on top of AI components including the base LLM, plugins for retrieval, code interpreter and image generation tools. There is much to be said about the claims that the future of AI is \u003Ca href=\"https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\" target=\"_blank\" rel=\"noopener\">shifting\u003C\u002Fa>\u003Ca href=\"..\u002F..\u002Fblog\u002Fautonomous-decisions-the-bias-variance-tradeoff-in-self-driving-technology\u002F#_edn10\">\u003Csup>10\u003C\u002Fsup>\u003C\u002Fa> from monolithic models to compound AI systems. We believe that this trend is even more important given the extremely high accuracy requirement for, and safety-critical aspect of, autonomous driving.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cu>References:\u003C\u002Fu>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn1\" href=\"#_ednref1\" name=\"_edn1\">\u003C\u002Fa>\u003Csup class=\"ref\">1\u003C\u002Fsup> Compound AI Systems\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\">https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn2\" href=\"#_ednref2\" name=\"_edn2\">\u003C\u002Fa>\u003Csup class=\"ref\">2\u003C\u002Fsup> the Alvinn project (Pomeraleau, 1989)\u003Cbr \u002F>\u003Ca style=\"word-wrap: break-word;\" href=\"https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F1988\u002Ffile\u002F812b4ba287f5ee0bc9d43bbf5bbe87fb-Paper.pdf\">https:\u002F\u002Fproceedings.neurips.cc\u002Fpaper\u002F1988\u002Ffile\u002F812b4ba287f5ee0bc9d43bbf5bbe87fb-Paper.pdf\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn3\" href=\"#_ednref3\" name=\"_edn3\">\u003C\u002Fa>\u003Csup class=\"ref\">3\u003C\u002Fsup> Bias-variance tradeoff\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FBias–variance_tradeoff\">https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FBias–variance_tradeoff\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn4\" href=\"#_ednref4\" name=\"_edn4\">\u003C\u002Fa>\u003Csup class=\"ref\">4\u003C\u002Fsup> Public data on Tesla's recent V12.3.6 version of FSD\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fwww.teslafsdtracker.com\u002Fhome\">https:\u002F\u002Fwww.teslafsdtracker.com\u002Fhome\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn5\" href=\"#_ednref5\" name=\"_edn5\">\u003C\u002Fa>\u003Csup class=\"ref\">5\u003C\u002Fsup> Tesla purchased 2000 Lidars from Luminar\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fwww.theverge.com\u002F2024\u002F5\u002F7\u002F24151497\u002Ftesla-lidar-bought-luminar-elon-musk-sensor-autonomous\">https:\u002F\u002Fwww.theverge.com\u002F2024\u002F5\u002F7\u002F24151497\u002Ftesla-lidar-bought-luminar-elon-musk-sensor-autonomous\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn6\" href=\"#_ednref6\" name=\"_edn6\">\u003C\u002Fa>\u003Csup class=\"ref\">6\u003C\u002Fsup> On the Sample Complexity of End-to-end Training vs. Semantic Abstraction Training \u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fpdf\u002F1604.06915\">https:\u002F\u002Farxiv.org\u002Fpdf\u002F1604.06915\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn7\" href=\"#_ednref7\" name=\"_edn7\">\u003C\u002Fa>\u003Csup class=\"ref\">7\u003C\u002Fsup> Human drivers not respecting stop signs as they should and instead perform a rolling stop\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fwww.teslarati.com\u002Ftesla-rolling-stop-markey-blumenthal-letter-elon-musk\u002F\">https:\u002F\u002Fwww.teslarati.com\u002Ftesla-rolling-stop-markey-blumenthal-letter-elon-musk\u002F\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn8\" href=\"#_ednref8\" name=\"_edn8\">\u003C\u002Fa>\u003Csup class=\"ref\">8\u003C\u002Fsup> Mobileye DXP as a novel approach \u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fmobileye-dxp-as-a-novel-approach\u002F\">https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fmobileye-dxp-as-a-novel-approach\u002F\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn9\" href=\"#_ednref9\" name=\"_edn9\">\u003C\u002Fa>\u003Csup class=\"ref\">9\u003C\u002Fsup> ChatGPT+\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fopenai.com\u002Fchatgpt\u002Fpricing\">https:\u002F\u002Fopenai.com\u002Fchatgpt\u002Fpricing\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp style=\"font-size: 1.3rem; margin-top: 1.4rem;\">\u003Ca id=\"_edn10\" href=\"#_ednref10\" name=\"_edn10\">\u003C\u002Fa>\u003Csup class=\"ref\">10\u003C\u002Fsup> Future of AI is shifting from monolithic models to compound AI systems\u003Cbr \u002F>\u003Ca href=\"https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\">https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\u003C\u002Fa>\u003C\u002Fp>","2024-05-15T07:00:00.000Z",[6,21],{"id":343,"type":100,"url":344,"title":345,"description":346,"primary_tag":98,"author_name":131,"is_hidden":96,"lang":132,"meta_description":346,"image":347,"img_alt":348,"content":349,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":5,"publish_date":350,"tags":351},256,"automated-driving-volkswagen-group-intensifies-collaboration-with-mobileye","大众汽车集团与Mobileye进一步深化合作","大众汽车和Mobileye将基于Mobileye SuperVision™和Mobileye Chauffeur™平台为量产车带来全新的自动驾驶功能。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fbfa4e22ac1493ebbc99323bb415a2f7e_1710795224355.jpg","Logos of the Volkswagen Group and Mobileye.","\u003Cp>\u003Cstrong>Wolfsburg\u002FJerusalem, March 20, 2024 – \u003C\u002Fstrong>The Volkswagen Group is welcoming further strategic collaboration and significantly accelerating its development efforts in the field of automated and autonomous driving. Now, Volkswagen is intensifying its partnership with Mobileye in the domain of automated driving. Together, the two companies will bring new automated driving functions to series production. Mobileye is to provide technologies for partially and highly automated driving based on its Mobileye SuperVision and Mobileye Chauffeur platforms.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa12beac8db6dc870c38f86797bcdc466_1710847421403.jpg\" alt=\"\" width=\"1504\" height=\"420\" \u002F>\u003C\u002Fp>\n\u003Cp>\u003Cem>Volkswagen Group and Mobileye will work on three levels of technology; hands-free, eyes-on driving; hands-free, eyes-off systems and fully autonomous vehicles.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>In the future, the Volkswagen Group’s Audi, Bentley, Lamborghini and Porsche brands will use these technologies to rapidly introduce new premium-oriented driving functions to their model portfolios across powertrain types. These include advanced assistance systems for highway and urban driving, such as automated overtaking on multilane highways in permitted areas and conditions, as well as automatic stopping at red lights and stop signs, and support in intersections and roundabouts. In addition, Mobileye is set to supply further technology components for automated driving to Volkswagen Commercial Vehicles. In the long term, the Volkswagen Group aims to rely on its own complete in-house system: Partnerships with Bosch and Qualcomm, as well as with Horizon Robotics in China, will be continued with a focus. All driver assistance systems are to be based on the software architectures developed by Volkswagen’s Cariad company.\u003C\u002Fp>\n\u003Cp>“Our goal is to offer our customers throughout the world outstanding products with cutting-edge technology,” says Oliver Blume, CEO of the Volkswagen Group and Porsche AG. \"New automated driving functions will significantly boost convenience and safety. These functions, which will be tailored to our brands and products, will make every trip a personal, individual experience. In Mobileye, we have an additional first-class partner to shape this automotive future together.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa12beac8db6dc870c38f86797bcdc466_1710847421407.jpg\" alt=\"\" width=\"1200\" height=\"675\" \u002F>\u003C\u002Fp>\n\u003Cp>The Volkswagen Group and Mobileye have been collaborating on advanced driver assistance systems for some time. In the future, Mobileye is set to also provide technologies for driving functions with enhanced Level 2 capabilities (\"partially automated driving\") within the Volkswagen Group. When such functions will be available, and subject to its operational design domain, drivers will be allowed to take their hands off the steering wheel but must remain attentive to the traffic and ready to intervene at any time. In addition, Volkswagen is working with Mobileye on Level 3 functions (\"highly automated driving.\") At this level, the vehicle will be able to temporarily take over driving tasks in specified areas; drivers are not required to monitor the system continuously. Volkswagen and Mobileye are jointly developing these technologies into cross-brand systems.\u003C\u002Fp>\n\u003Cp>In addition, Mobileye will also offer certain production-ready functions for the new E3 1.2 premium-oriented software architecture. This new architecture is managed by Cariad and will be gradually implemented within the group by Audi, Bentley, Lamborghini, and Porsche. As part of their product strategy, the brands decide on the specific deployment of the systems and tailor them to a brand-specific driving experience.\u003C\u002Fp>\n\u003Cp>Furthermore, the Volkswagen Commercial Vehicles brand is set to be supplied by Mobileye with software and hardware to achieve Level 4 (\"fully automated driving\"). Volkswagen ADMT, a Volkswagen Group subsidiary, will implement these components in fully electric development platforms based on the Volkswagen ID. Buzz. The goal of Volkswagen ADMT is to bring self-driving ID. Buzz vehicles to series production for mobility and transportation services.\u003C\u002Fp>\n\u003Cp>“We are proud to work closely with Volkswagen Group to make the future of driving safer, more automated and more rewarding,“ says Prof. Amnon Shashua, President and CEO of Mobileye. “Through these programs, we see Volkswagen Group leading the industry in putting AI-powered advanced driver assistance technology in the hands of consumers globally and developing new services with autonomous vehicles.“\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Volkswagen Group sharpens its development strategy for driver assistance systems\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Volkswagen is further clarifying the division of development tasks for driver assistance systems between in-house innovation and collaboration for its new E\u003Csup>3\u003C\u002Fsup> 1.2 and E\u003Csup>3\u003C\u002Fsup> 2.0 software architectures. This will streamline processes and reduce complexity. With strategic partners such as Mobileye, Volkswagen Group is accelerating the rapid delivery of the premium-oriented E\u003Csup>3\u003C\u002Fsup> 1.2 architecture, while, in the long term, the Group will rely on its own complete in-house (‘stack’) for automated driving across all brands.\u003C\u002Fp>\n\u003Cp>For the future E\u003Csup>3\u003C\u002Fsup> 2.0 architecture, the Volkswagen Group plans to forge ahead and consolidate its resources and development responsibilities within Cariad, its software company. Together with Bosch, Cariad aims to develop the Group's proprietary complete system. This system will be integrated into the future all-electric, fully digital, and highly scalable mechatronics Group platform, the Scalable Systems Platform (SSP)\u003C\u002Fp>\n\u003Cp>“We are sharpening our development strategy for driver assistance systems at the same time as heightening our customer focus. We are concentrating on fast, reliable delivery,” says Michael Steiner, Head of Research and Development of the Volkswagen Group and Member of the Executive Board, Research and Development of Porsche AG.\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">\u003Cstrong>About the Volkswagen Group\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">The Volkswagen Group is one of the world's leading car makers, headquartered in Wolfsburg, Germany. It operates globally, with 114 production facilities in 19 European countries and 10 countries in the Americas, Asia and Africa. With around 684,000 employees worldwide. The Group’s vehicles are sold in over 150 countries. With an unrivalled portfolio of strong global brands, leading technologies at scale, innovative ideas to tap into future profit pools and an entrepreneurial leadership team, the Volkswagen Group is committed to shaping the future of mobility through investments in electric and autonomous driving vehicles, digitalization and sustainability. In 2023, the total number of vehicles delivered to customers by the Group globally was 9.2 million (2022: 8.3 million). Group sales revenue in 2023 totaled EUR 322.3 billion (2022: EUR  279.1 billion). The operating result before special items in 2023 amounted to EUR 22.6 billion (2022: EUR 22.5 billion).\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size: 10pt;\">Mobileye (Nasdaq: MBLY) leads the evolution of mobility with its autonomous driving and driver-assistance technologies, based on world-renowned expertise in artificial intelligence, computer vision, mapping, and integrated hardware and software. Since its founding in 1999, Mobileye has enabled the wide adoption of advanced driver-assistance systems while pioneering groundbreaking technologies such as REM™ crowdsourced mapping, True Redundancy™ sensing, Responsibility-Sensitive Safety™ (RSS™) driving policy and Driving Experience Platform (DXP). These technologies support a product portfolio structured for scale and designed to unlock the full potential of mobility, offering a range of solutions from premium ADAS to autonomous vehicles. By the end of 2023, about 170 million vehicles worldwide had been equipped with Mobileye technology. In 2022, Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>.\u003C\u002Fspan>\u003C\u002Fp>","2024-03-20T07:00:00.000Z",[99,64,21,13,34,42],{"id":353,"type":100,"url":354,"title":355,"description":356,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":356,"image":357,"img_alt":358,"content":359,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":96,"featured":96,"publish_date":350,"tags":360},257,"volkswagen-admt-announces-agreement-with-mobileye-for-autonomous-driving","大众ADMT宣布与Mobileye达成自动驾驶协议","大众ADMT将与mobileye合作量产自动驾驶车队，这在全球汽车制造商中尚属首次。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc245a61f928c539a7fe4569114de035b_1710931574541.jpg","The Volkswagen ID. Buzz AV built on the Mobileye Drive™ autonomous platform. ","\u003Cp>− Volkswagen is the first vehicle manufacturer to develop an autonomous Level 4 service vehicle for large-scale production\u003C\u002Fp>\n\u003Cp>− The aim is to use it in the commercial sector, for example for mobility and transport services in Europe and the USA\u003C\u002Fp>\n\u003Cp>− High synergies with systems for automated driving within Volkswagen Group: shared module use from Level 2+ to Level 4\u003C\u002Fp>\n\u003Cp>Hannover, 20 March 2024 – Autonomous driving is coming. Following an extensive pilot phase with road testing in Germany and the USA, Volkswagen ADMT GmbH, part of Volkswagen AG, is announcing a cooperation agreement with the Israeli technology company Mobileye Global Inc. Mobileye shall develop and supply software, hardware components and digital maps for the self-driving ID. Buzz AD.\u003C\u002Fp>\n\u003Cp>The main part of the agreement covers delivery and use of a self-driving system (SDS) based on the Mobileye Drive™ platform for a special version of the ID. Buzz, which has been under development for autonomous driving since 2021. It corresponds to the so-called Level 4 definition of the Society of Automotive Engineers (SAE), in which the autonomous vehicle operates self-driving in a defined area such as a city. The basis for this are various software and hardware components, including two independent high-performance computers as well as 13 cameras, nine lidar and five radar units, each of which is capable of producing 360-degree surroundings. A constant online connection to clouds provides the autonomous vehicles with swarm data from other road users about the traffic situation as well as updates to the three-dimensional maps.\u003C\u002Fp>\n\u003Cp>“Bringing autonomous shuttles on the road in large quantities requires cooperation from strong partners,” says Christian Senger, member of the Board of Management at Volkswagen Commercial Vehicles, responsible for Autonomous Driving: “We are developing the first fully autonomous large-scale production vehicle, and Mobileye brings its digital driver on board.”\u003C\u002Fp>\n\u003Cp>An advantage of the cooperation is the synergy with systems for automated driving in the Volkswagen group; depending on the expansion level, modules can be shared across SAE levels from 2+ to 4. The aim of Volkswagen ADMT GmbH is to develop the fully electric autonomous ID. Buzz AD for the use in mobility and transport services from 2026.\u003C\u002Fp>\n\u003Cp>This also includes intelligent fleet control: The Volkswagen Group company MOIA has been operating Europe's largest private ride pooling service in Hamburg since 2019 and has transported more than ten million passengers to date. MOIA brings its practical know-how into the development: Unlike individual (partially) autonomous cars, which are used individually by vehicle owners, mobility services are dedicated to transporting passengers to their desired destinations within the defined urban area and drop them off safely.\u003C\u002Fp>\n\u003Cp>Another use case for self-driving vehicles is, for example, the transport of packages. The logistics market has grown significantly in recent years due to the increasing share of e-commerce. Delivery capacity is already one of the biggest challenges the industry is facing due to the driver shortage. Autonomous transport will therefore be a possible solution to ensure long-term delivery capability and participate in market growth. Volkswagen ADMT GmbH is working intensively on autonomous freight transport for various industries as a second important pillar alongside autonomous passenger transport. In the future, autonomous vehicles shall be able to drive to certain loading and unloading stations or to customer addresses independently.\u003C\u002Fp>\n\u003Cp>Autonomous vehicles for mobility and transportation services solve the driver shortage that has been the case for many years. Robo-shuttles promote both the quality of life and the economic development of cities.\u003C\u002Fp>\n\u003Cp>\u003Cbr \u002F>\u003Cspan style=\"font-size: 10pt;\">Volkswagen Commercial Vehicles: We Transport Success, Freedom and Future\u003C\u002Fspan>\u003Cbr \u002F>\u003Cspan style=\"font-size: 10pt;\">As a leading manufacturer of light commercial vehicles, the Volkswagen Commercial Vehicles brand (VWCV) is reshaping the transportation of goods, services and people in a fundamental and lasting way. Our vehicles transport construction workers, families and adventurers, bread rolls, parcels and surfboards. Every day they help countless people all over the world to do a good job, they operate as mobile workshops and they bring \u003C\u002Fspan>\u003Cspan style=\"font-size: 10pt;\">paramedics and police personnel to wherever they are needed. At our sites in Hanover (D), Poznań (PL), Września (PL) and Pacheco (ARG), around 24,000 employees produce the Transporter, the new Multivan, Caddy, Crafter and Amarok model lines, and since May 2022 the ID. Buzz – the fully electric version of our iconic Bulli. Within the Volkswagen Group, VWCV is also the lead brand for autonomous driving and mobility offerings such as Mobility-as-a-Service and Transport-as-a-Service - areas in which we are shaping the future of mobility. In this way, the brand is transporting the society of tomorrow with all its requirements for clean, intelligent and sustainable mobility. It is this that Volkswagen Commercial Vehicles stands for with its brand promise: We transport success, freedom and future.\u003C\u002Fspan>\u003C\u002Fp>",[21,34,42,64,49,99],{"id":362,"type":57,"url":363,"title":364,"description":365,"primary_tag":55,"author_name":265,"is_hidden":96,"lang":132,"meta_description":365,"image":366,"img_alt":367,"content":368,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":369,"tags":370},254,"mobileye-dxp-as-a-novel-approach","采用全新的Mobileye DXP平台解决定制化需求","Mobileye DXP 解决了定制需求与上市时间和性能风险之间的矛盾","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd3e61ddfe04ec9f19f25187580a6c1f7_1708003321461.jpg","Mobileye's DXP addresses the tension between the need to customize and time-to-market and performance risks.","\u003Cp>Over the past decade, as we have embarked on the gradual transition from driver assist towards autonomous driving, there have been several crossroads along the way where the conventional industry approach has overlooked an inconvenient reality and thus limited the potential for safer and ubiquitous autonomous vehicles – the shared goal in the industry. The path of least resistance often leads to a choice of what seems doable now, but isn’t practical or scalable later.\u003C\u002Fp>\n\u003Cp>We saw this when it was understood that AVs needed HD maps on a level that regular navigation maps could not support, and the common approach was to use dedicated lidar-equipped vehicles to manually map an area for AV driving. This was slow, costly, geographically limited, and generated maps that were quickly out of date. This was when we came up with the idea of REM crowdsourced mapping using cameras already onboard ADAS-equipped vehicles travelling on their typical routes.\u003C\u002Fp>\n\u003Cp>We also saw this when the industry came to a consensus that cameras, radars, and lidars were all necessary for redundant sensing for AVs, but overlooked how equipping vehicles with that many sensors would make them highly expensive, dramatically limiting profitable business models. This is why we are investing in developing imaging radar with lidar-like output, to reduce the number of lidars included and thereby significantly lowering the hardware costs per vehicle. We even see today that our then-radical early 2000s decision to design our own chip and tightly couple hardware with software is proving central to cost-effective high-performance delivery, while others are only now considering this route.\u003C\u002Fp>\n\u003Cp>The industry is now at another crossroads, where we must not overlook an important reality, even if it is inconvenient or hard to overcome, and it has to do with the inherent tension between, on one hand, automakers' desire to customize their offerings and, on the other hand, the time-to-market and performance risks involved in full development of automated driving systems from scratch.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The differentiability-scalability-risk tradeoff \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>For automated driving to become commonplace, automakers will want to customize their driving experience for their particular consumers' expectations. How to do this optimally must take into consideration three key factors: the ability for the automaker to differentiate among other brands, the ability for the supplier to scale to many automakers, and a need to minimize the risk of not executing to the desired performance, cost, and timeline. Given the numerous announcements about ambitious projects in recent years that never came, or have yet to come, to fruition, this execution risk cannot be overlooked.  \u003C\u002Fp>\n\u003Cp>  \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1381038603fa2dbc89d8fcbcd240c2ef_1708001820543.jpg\" alt=\"\" width=\"650\" height=\"300\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Where to draw the line between sense, plan, and act?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The foundation of all robotics is sense-plan-act: perceive the environment, make a plan, and execute the plan. If differentiability is desired, the automaker must control some part of this stack, but the hard question is where to draw the line between what the supplier controls and what the automaker controls, with all three aspects of the tradeoff in mind. If the supplier provides part of the perception and the automaker develops the rest, differentiation is obtained, but the risk to the automaker is very high; development is difficult, time-consuming, and costly. Integrating everything into one complete and robust system is extremely hard.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F945570dd6474b8083bf5dfaf1dbcdcd6_1708002027160.jpg\" alt=\"\" width=\"650\" height=\"337\" \u002F>\u003C\u002Fp>\n\u003Cp>On the other hand, if the supplier provides all of the driving policy and the automaker handles only the actions taken by the vehicle, either not enough differentiation is achieved on the part of the automaker, \u003Cem>or\u003C\u002Fem> the supplier needs to handle all of the automaker’s driving experience requirements, which is a challenge to scalability.  \u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff23a6c4da27193d5421b3baceea322c2_1708002148211.jpg\" alt=\"\" width=\"650\" height=\"332\" \u002F>\u003C\u002Fp>\n\u003Cp>So then the answer seems easy – draw the line between perception and planning. Get all your sensing from the supplier, and the automaker can build their own driving policy and actuation stack.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fbce90c5eac3727c9ca12d4f1ab1a58e3_1708002252931.jpg\" alt=\"\" width=\"650\" height=\"331\" \u002F>\u003C\u002Fp>\n\u003Cp>While tantalizing, this too is highly problematic, and where a key reality of AV development gets overlooked: perception is never perfect, and a driving policy must be robust enough to anticipate those imperfections, requiring an intimate integration of perception and planning. Many attempts have been made with this approach and are at various stages of failure, due to what we call the \"underestimation plague\" – a tendency to vastly underestimate how hard driving policy really is.\u003C\u002Fp>\n\u003Cp>Driving policy must deal with predictions, intentions, uncertainties, and risks of decision-making errors and is therefore highly complex. This approach is therefore also not scalable for the automaker, as driving policy is intimately integrated with perception and must be continually adapted and revalidated as perception changes. \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Separating the universal from the unique \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Given the above, the better path to enable differentiation while also minimizing execution risk and enabling scalability is to draw the line \u003Cspan style=\"font-style: normal !msorm;\">\u003Cem>in the middle of\u003C\u002Fem>\u003C\u002Fspan> the policy stack, with the goal of keeping the perception and sensing integrated, while offering space to the automaker to define behavioral elements of the vehicle.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd694ea364ba1e8f44b1ca1fb90b6eaff_1708003677023.jpg\" alt=\"\" width=\"650\" height=\"366\" \u002F>\u003C\u002Fp>\n\u003Cp>In order to do this, we must define which aspects are universal and should be the same for all systems, and which aspects are unique – where differentiation can and should be possible. Perception is clearly universal, and the way the vehicle performs actions is clearly unique. Driving policy, however, is partially universal and partially unique. On the one hand, it must be tailored to sensing, and on the other hand, it is responsible for the look and feel of the driving experience. The art is to find the right granularity of abstractions that will enable us to make the separation between the universal content (which we want to standardize) and the unique content (which we want to customize around).\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc7d9afa73d33066de2b13baa1b7d31be_1708003813431.jpg\" alt=\"\" width=\"650\" height=\"360\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Mobileye DXP: When, what, and how\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Mobileye Driving Experience Platform, or DXP, is a programming language that separates between the universal and the unique, by organizing the decision-making according to when, what, and how. The \"when\" and \"what\" are universal, and the \"how\" is unique. For example, \"when\" approaching a stop sign, the vehicle must brake to stop (the \"what\"). But \"how\" each vehicle model brakes is unique – later and stronger, or earlier and milder, for example. Or, when approaching a roundabout, the vehicle must decide whether to yield or to proceed in front of another vehicle. Assuming both are safe, what should the vehicle do? This is the “how” category, and different automakers will want to tune their systems differently.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa9661f51c4a3e05dadefe3c330c7d06e_1708003943206.jpg\" alt=\"\" width=\"650\" height=\"367\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>How it works inside DXP\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Within a given scenario – the \"what\" and \"when\" – the automaker defines packages or families of \"how\" – a variety of implementations of how to brake to stop for example. The automaker constructs packages of “how instances” out of the platform’s “how families\". The platform provides online and offline tools for creating these packages. The platform also offers reference designs for required packages, in order to reduce execution risk, such that the automaker doesn't need to implement all packages from day one, but can focus on where it specifically wants to provide differentiation.\u003C\u002Fp>\n\u003Cp>Automakers then create code that selects the appropriate package during online driving, based on application parameters like locality, road type, regulation, driving mode, and weather conditions. This solves the differentiability-scalability-risk tradeoff by offering differentiability without breaking the intimate integration between sensing and policy, by using the right abstractions, and, accordingly, reducing execution risk, because the platform will be based on a working product out of the box, and all efforts can focus on differentiation. Automakers can also make post-production tweaks to the driving experience in response to consumer feedback.\u003C\u002Fp>\n\u003Cp>The backbone of this platform is based on redundancy in perception engines, and driving policy using Responsibility-Sensitive Safety combined with analytical calculations and intentions (you can learn more about that in \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=_z3qBZ6vQL8&t=1349s\" target=\"_blank\" rel=\"noopener\">this video)\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>We see great potential in DXP, and in the short time since we unveiled it at CES, several automakers have expressed interest in learning more. The tangible benefits of automated driving systems should help an automaker further define its brand. DXP offers a better roadmap to that future.\u003C\u002Fp>","2024-02-21T08:00:00.000Z",[56,6,64,114,21],{"id":372,"type":100,"url":373,"title":374,"description":375,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":375,"image":376,"img_alt":377,"content":378,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":379,"tags":380},253,"mobileye-and-project-3-mobility-announce-collaboration-for-scalable-urban-autonomous-mobility-project","Mobileye与Project 3出行宣布达成可拓展城市自动驾驶出行项目合作","利用Mobileye Drive可扩展的自动驾驶技术打造新的城市自动驾驶出行生态系统","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa3432d1bf7442959befeecc389c5ee8a_1707767336699.jpg","Logos of Project 3 and Mobileye on a circuit board","\u003Cp>Jerusalem and Zagreb, February 13, 2024 – Mobileye (Nasdaq: MBLY), a global leader in autonomous driving solutions, and Project 3 Mobility (P3), a Croatian company building a new ecosystem for urban autonomous mobility, today announced a collaboration to explore a new mobility service, utilizing Mobileye’s scalable self-driving technology, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fdrive\u002F\">Mobileye Drive™\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>Project 3 Mobility aims to significantly improve transportation in urban areas and revolutionize mobility in cities. The first P3 service is aimed to be launched in Zagreb in 2026, with testing and validation of Mobileye's AV solution on the streets of the Croatian capital targeted to start in 2024.\u003C\u002Fp>\n\u003Cp>Project 3 Mobility's mission is to redefine urban mobility into a safe, effortless, and premium user experience. By leveraging technology and innovation, P3 is creating a ground-breaking ecosystem consisting of three key elements: an autonomous electric vehicle, specialized infrastructure, and a mobility service platform. Project 3 Mobility is developing a fully autonomous electric vehicle fundamental for implementing this new urban mobility ecosystem. The vehicle is built on a completely new platform designed around safety and comfort, fully utilising the benefits of autonomous driving. Mobileye technology will be integrated into the P3 vehicle, which will use the Mobileye Drive autonomous driving solution that has also been adopted by some of the world’s leading automotive companies.\u003C\u002Fp>\n\u003Cp>For the past two decades, Mobileye has used the power of computer vision and artificial intelligence to improve automotive safety, with approxtimately 170 million vehicles integrating Mobileye technology to date. The Mobileye Drive combination of redundant camera and lidar-radar sensing, REM™ crowdsourced mapping and transparent driving policy – all powered by the EyeQ™ system-on-chip - enables Mobileye to offer scalable, adaptable autonomous driving for robotaxis and Mobility-as-a-Service (MaaS) providers. The big benefits of Mobileye Drive are that it can be deployed in a wide range of geographic locations, on many different road types; that it can drive under varying weather conditions; and that it can adapt itself to local driving styles, all of which are crucial for Project 3 Mobility’s service scalability. \u003C\u002Fp>\n\u003Cp>P3 has already signed agreements with 9 cities across the EU, UK and GCC to provide its urban autonomous service, and 30 more cities are planned to follow. Also, Project 3 Mobility is about to establish a production facility in Croatia for the large-scale production of autonomous vehicles that will be deployed worldwide.\u003C\u002Fp>\n\u003Cp>“We welcome this innovative collaboration with Project 3 Mobility to bring an exciting and promising new mobility service to life,” said Prof. Amnon Shashua, founder and CEO of Mobileye. “We share the vision of making urban mobility safer and more accessible, and with the flexibility of Mobileye Drive to adapt to different vehicle types, we’re excited to explore new frontiers in mobility services.”\u003C\u002Fp>\n\u003Cp>“We are committed to improving how people move in cities. Our collaboration with Mobileye is a cornerstone for achieving that vision. Mobileye has proved to be a great partner that has the right experience, the right technology, and the right team. Together we will make that vision of urban autonomous mobility a reality. I am very excited to share more details in the next few months”, said Marko Pejković, CEO of Project 3 Mobility.\u003C\u002Fp>\n\u003Cp>Project 3 Mobility’s planned Mobility-as-a-Service project aims to provide customers with more than just transportation from point A to point B. The goal is to give customers an improved user experience tailored to their needs, by giving back time spent in traffic, opening possibilities for leisure or work. The realization of P3‘s project aims to increase efficiency and safety in traffic and achieve a positive impact on the environment and city infrastructure. The project aims to create significant benefits for Zagreb and many other cities that will provide this service.\u003C\u002Fp>\n\u003Cp>Project 3 Mobility will share further details about its project and service in the months ahead.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Mobileye\u003C\u002Fstrong> \u003C\u002Fp>\n\u003Cp>Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety™ (RSS™). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, about 170 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye was listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit  \u003Ca href=\"https:\u002F\u002Fcts.businesswire.com\u002Fct\u002FCT?id=smartlink&url=https%3A%2F%2Fwww.mobileye.com&esheet=53539903&newsitemid=20230817465845&lan=en-US&anchor=https%3A%2F%2Fwww.mobileye.com&index=2&md5=dc09cc0681f253ba2b178bfdedda4ac0\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>. \u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Project 3 Mobility\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Project 3 Mobility is a Croatia-based company developing a new ecosystem for urban autonomous mobility. The innovative ecosystem consists of three key elements that P3 is creating: the urban autonomous vehicle, specialized infrastructure, and a complete service platform. By focusing on a safe, effortless, and premium user experience, the P3 service will significantly improve transportation in urban areas and revolutionize the way we move in our cities. Given the cutting-edge solution, the project has attracted multiple experts from all around the world. Currently, Project 3 Mobility has a team of more than 240 people with experts from more than 20 different industries and nationalities in two offices – in Croatia and the UK.\u003C\u002Fp>\n\u003Cp>The company was founded in 2019 by Croatian innovator and entrepreneur Mate Rimac, Marko Pejković, CEO of Project 3 Mobility, and Adriano Mudri, CDO at Project 3 Mobility. \u003C\u002Fp>\n\u003Cp>For more information, visit \u003Ca href=\"https:\u002F\u002Fp3m.com\u002F\">https:\u002F\u002Fp3m.com\u002F\u003C\u002Fa>\u003C\u002Fp>","2024-02-13T08:00:00.000Z",[21,49,34,99],{"id":382,"type":141,"url":383,"title":384,"description":385,"primary_tag":63,"author_name":136,"is_hidden":96,"lang":132,"meta_description":385,"image":386,"img_alt":387,"content":388,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":389,"tags":390},252,"mobileye-ces-2024","Mobileye闪耀CES 2024  ","本届CES, 我们推出了Mobileye DXP -全新驾驶体验平台","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc30e532299c9f589ff8c9dd811c038ec_1705931822539.jpg","Entering CES 2024 at the Las Vegas Convention Center.","\u003Cp>\u003Cspan data-contrast=\"auto\">It was all about experiencing brand-new technologies at CES 2024, and, just as in previous years, Mobileye was a main attraction on the show floor in Las Vegas, giving visitors an opportunity to witness our vision of an autonomous future.  \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">New collaborations and a new platform took center stage as Mobileye presented its latest developments at the biggest in-person tech event in the world, with over 135,000 people in attendance. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">From first glimpses of vehicles equipped with our cutting-edge technologies to the unveiling of our latest breakthroughs, here is a quick recap of all the action in and around Mobileye at CES 2024.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FhrEpvBG4u14?si=aLA9H38kj7bsQgb6\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan data-contrast=\"auto\">Professor Amnon Shashua at CES 2024: Now. Next. Beyond. \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fh3>\n\u003Cp>\u003Cspan data-contrast=\"auto\">On the first day of CES, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Famnon-shashua\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye's CEO\u003C\u002Fa> \u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">delivered his much-anticipated \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fprof-amnon-shashua-at-ces-2024\u002F\" target=\"_blank\" rel=\"noopener\">annual press conference\u003C\u002Fa>\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">. Prof. Shashua analyzed the present and future of Mobileye’s assisted and autonomous driving systems. \u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">He also elaborated on our recent announcements that Mobileye has been awarded \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-reveals-new-wins-for-key-tech-platforms-with-large-global-automaker\u002F\" target=\"_blank\" rel=\"noopener\">production design wins\u003C\u002Fa> \u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">by a major Western automaker.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">In addition, Prof. Shashua \u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">introduced Mobileye DXP, a new platform that offers automakers the ability to customize the driving experience, preserving their brand and style.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\">\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fuco1z54FAdA?si=g8QYKWHglkow14Lv\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan data-contrast=\"auto\">Stealing the show\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fh3>\n\u003Cp>\u003Cspan data-contrast=\"auto\">The new DXP platform was at the fore in Mobileye's booth as well, which drew thousands of attendees who were wowed by everything on display. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">With an assist in the form of a \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=Aw_R7zqs6Sk\" target=\"_blank\" rel=\"noopener\">presentation\u003C\u002Fa> by our \u003C\u002Fspan>\u003Cspan data-contrast=\"none\">Executive VP of Strategy & Business Development, Nimrod Nehushtan\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">, our main show took the audience on a journey, through Mobileye’s history, by way of its here and now, all the way to what is to come ahead.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\">\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FIBXl4kJ2mfQ?si=0dNe5SfIGgoQjKwz\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cspan data-contrast=\"auto\">A deep dive into Mobileye DXP \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fh3>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Our new Driving Experience Platform was also the subject of Mobileye CTO Prof. Shai Shalev-Shwartz's CES 2024 presentation. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Explaining where the idea behind the system came from and how it balances safety and scale, Prof. Shalev-Shwartz highlighted the platform's ability to provide automakers with AI tools to program the vehicle’s functionality, allowing them to customize the driving experience of their vehicles to their preferences. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\">\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F_z3qBZ6vQL8?si=QQ96oUSBpsUyVzJr\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\">\u003Cspan class=\"TextRun SCXW192484678 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\">\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">Mobileye’s \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">yearly \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">visit \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">to\u003C\u002Fspan> \u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">CES was thrilli\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">ng and inspiring. Al\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">though \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">the big event has powered down\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">,\u003C\u002Fspan> \u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">rest \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">as\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">sure\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">d\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\"> that plans for \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">next year are \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">already\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\"> underway, as we continue to work \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">toward\u003C\u002Fspan> \u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">creating \u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\">a\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\"> bright\u003C\u002Fspan>\u003Cspan class=\"NormalTextRun SCXW192484678 BCX0\"> autonomous future.\u003C\u002Fspan>\u003C\u002Fspan>\u003Cspan class=\"EOP SCXW192484678 BCX0\" data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>","2024-01-22T08:00:00.000Z",[99,21,64,84,78],{"id":392,"type":100,"url":393,"title":394,"description":395,"primary_tag":5,"author_name":136,"is_hidden":96,"lang":132,"meta_description":395,"image":396,"img_alt":397,"content":398,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":399,"tags":400},250,"prof-amnon-shashua-at-ces-2024","Amnon Shashua 教授 CES 2024: Now. Next. Beyond 新闻发布会","CES 2024首日，Mobileye首席执行官Amnon Shashua教授主持了备受瞩目的年度新闻发布会，分析了Mobileye辅助驾驶和自动驾驶系统的现状与未来","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F62e61593274d34538d7719105558a450_1705490954008.jpg","Mobileye CEO Prof. Amnon Shashua speaking at his annual CES press conference.","\u003Cp>Mobileye’s annual CES press conference was again an industry focal point, with Mobileye CEO Professor Amnon Shashua presenting his insights into key issues.\u003C\u002Fp>\n\u003Cp>During his presentation, Prof. Shashua discussed the current state of self-driving car technologies and future possibilities for the industry, zeroing in on two main issues: (1) creating a safer eyes-off system, and (2) providing a platform for carmakers that allows them to customize their driving experience, which was unveiled as Mobileye’s new DXP platform.\u003C\u002Fp>\n\u003Cp>Prof. Shashua also introduced new and exciting collaborations between Mobileye and several OEMs, including Mobileye securing a series of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-reveals-new-wins-for-key-tech-platforms-with-large-global-automaker\u002F\">production design wins\u003C\u002Fa> from a major Western automaker, Chery's approaching launch of Mobileye’s Cloud-Enhanced ADAS on its Exeed VX model.\u003C\u002Fp>\n\u003Cp>During the event, held in Las Vegas, Prof. Shashua highlighted breakthroughs in AI and the opportunities to apply them to autonomous driving. He also updated the expected timeline for Mobileye’s EyeQ™ 6H SoC and noted the next generation of Mobileye's imaging radars.\u003C\u002Fp>\n\u003Cp>Watch the video below to see the full press conference and learn about Mobileye's bridge from hands-on to no-driver systems.\u003C\u002Fp>\n\u003Cp>\u003Ciframe src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fuco1z54FAdA?si=CaV3jgH9LqWAiXUT&amp\" width=\"560\" height=\"314\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>","2024-01-17T08:00:00.000Z",[84,6,99,21,13],{"id":402,"type":100,"url":403,"title":404,"description":405,"primary_tag":136,"author_name":136,"is_hidden":96,"lang":132,"meta_description":405,"image":406,"img_alt":407,"content":408,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":409,"tags":410},247,"mobileye-reveals-new-wins-for-key-tech-platforms-with-large-global-automaker","Mobileye 披露与国际汽车制造商巨头基于核心技术平台的最新合作","自 2026年起，Mobileye 自动驾驶技术将应用于多个全球品牌的17款新车型。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F66263c67cd7ee9163cb270e6fdeee5e4_1704644722450.jpg","At CES 2024, Mobileye revealed new wins for its three key platforms – Mobileye SuperVision™, Mobileye Chauffeur™ and Mobileye Drive™.","\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"auto\">LAS VEGAS, JAN 8, 2024 – \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-contrast=\"auto\">Mobileye (Nasdaq: MBLY) announced today that it has been awarded a series of production design wins by a major Western automaker. Under these design wins, multiple global brands are expected to implement new automated driving solutions using Mobileye’s three key platforms – Mobileye SuperVision\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">, Mobileye Chauffeur\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\"> and Mobileye Drive\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\"> – for 17 internal combustion and electric vehicle models, which are set to begin rolling out in 2026.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">The extensive set of awards includes Mobileye's unique and innovative software tool that will ensure each brand can maintain the utmost level of customization and personalization in their driving experiences. The premium ADAS and automated solutions are expected to be offered on multiple vehicle platforms across a broad range of geographies and various powertrain types, and can be easily expanded to additional models based on demand. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">“These design wins represent an historic milestone in the development of automated driving, and will greatly increase its availability to customers globally,” said Mobileye CEO Prof. Amnon Shashua. “Execution of these production programs will set the standard for software-driven intelligent driving, leveraging the expertise of both companies at volume to serve customers around the world.”  \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Mobileye will work with the various brands as a Tier 1 to develop new services for hands-off, eyes-on driving on the Mobileye SuperVision platform, leveraging AI-powered surround computer vision and radar that enable navigate-on-pilot functions for highway, rural and urban roads in defined operational domains. These services are currently expected to begin rolling out across multiple markets and regions in 2026.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Mobileye will also work with these automotive brands to implement the Mobileye Chauffeur platform to select models, offering eyes-off, hands-off advanced driving solutions in specified operating design domains. Mobileye enables Chauffeur by adding a second, independent perception system leveraging radar and lidar sensor outputs, as well as additional computing power as needed, to the SuperVision platform, creating a naturally scalable upgrade path for automakers.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">The two companies also agreed to bring fully autonomous vehicles into series production. Powered by the Mobileye Drive platform, this program is designed to produce purpose-built vehicles utilized in robotaxi and mobility-as-a-service operations. The Drive-enabled vehicles leverage computer vision, lidar and Mobileye imaging radar, with initial driverless deployments targeted for 2026. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">All systems will use the Mobileye EyeQ\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"auto\">6H systems-on-chip designed for powerful but efficient computing to integrate all sensing and REM crowdsourced mapping with safe driving policy. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">“Since our founding, we have focused on delivering the safety and convenience benefits of advanced computer vision technology around the world,” said Shashua. “The pace of innovation has undoubtedly increased and the breadth of this agreement serves as a blueprint for the scalability and customizability of our technology stack, with SuperVision serving as a bridge to eyes-off systems for both consumer-owned vehicle and mobility-as-a-service markets.”\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>","2024-01-08T08:00:00.000Z",[13,21],{"id":412,"type":92,"url":413,"title":414,"description":415,"primary_tag":90,"author_name":136,"is_hidden":96,"lang":132,"meta_description":415,"image":416,"img_alt":417,"content":418,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":419,"tags":420},243,"mobileye-at-ces-2024","Mobileye 闪耀 CES 2024","浏览我们的展会新闻工具包，了解我们的最新信息、视频、照片等。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3b11d58d5ed1e6627e8ae0adb746a603_1703018865471.jpg","Mobileye: Now. Next. Beyond. with President & CEO Prof. Amnon Shashua will be Presented on January 9, 2024, at 11:00 a.m. PT. ","\u003Cp>Mobileye returns to Las Vegas for CES 2024, demonstrating progress and innovation on our path to delivering an evolutionary vision of autonomy.\u003C\u002Fp>\n\u003Cp>Visit \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\" target=\"_blank\" rel=\"noopener\">mobileye.com\u002Fces-2024\u003C\u002Fa> for complete information on all of our CES activities.\u003C\u002Fp>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\"> \u003C\u002Fh3>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\">\u003Cstrong>Mobileye CES 2024 News\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-announces-ces-2024-press-conference-with-prof-amnon-shashua\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye Announces CES 2024 Press Conference with Prof. Amnon Shashua\u003C\u002Fa> (Press Release, December 20, 2023)\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-reveals-new-wins-for-key-tech-platforms-with-large-global-automaker\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye Reveals New Wins for Key Tech Platforms With Large Global Automaker\u003C\u002Fa> (Press Release, January 8, 2024)\u003C\u002Fp>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\"> \u003C\u002Fh3>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\">Presentations\u003C\u002Fh3>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcorporate\u002Fdocs\u002Fproduct_portfolio_2024.pdf\" target=\"_blank\" rel=\"noopener\">The full spectrum of Mobileye solutions, from driver assistance to autonomous driving.\u003C\u002Fa> (Product Brief)\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcorporate\u002Fces-2024\u002FCES_2024_Now._Next._Beyond.pdf\" target=\"_blank\" rel=\"noopener\">Mobileye: Now. Next. Beyond. CES 2024 Press Conference with Prof. Amnon Shashua\u003C\u002Fa> (Presentation)\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcorporate\u002Fces-2024\u002FMobileye_DXP_Prof._Shai_Shalev-Shwartz.pdf\" target=\"_blank\" rel=\"noopener\">Mobileye's Driving Experience Platform: Architecture, Abstractions, and APIs, presented by Mobileye CTO Prof. Shai Shalev-Shwartz\u003C\u002Fa> (Presentation)\u003C\u002Fp>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\"> \u003C\u002Fh3>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\">Photos\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>Mobileye at CES 2024\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:ces-2024-updated[**]\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cstrong>Mobileye's Advanced Platforms in the Driver's Seat\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>[**]gallery:mobileyes-advanced-platforms-in-the-drivers-seat[**]\u003C\u002Fp>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\"> \u003C\u002Fh3>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\">Videos\u003C\u002Fh3>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fvimeo.com\u002F901092712\u002F422cd0f7d0?share=copy\" target=\"_blank\" rel=\"noopener\">Mobileye 2024 Broll\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fvimeo.com\u002F901109646\u002Fb688a364d8?share=copy\" target=\"_blank\" rel=\"noopener\">Introducing Mobileye DXP\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fvimeo.com\u002F901643395?share=copy\" target=\"_blank\" rel=\"noopener\">Mobileye: Now. Next. Beyond. CES 2024 Press Conference with Prof. Amnon Shashua\u003C\u002Fa> (Replay)\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fvimeo.com\u002F902025604\" target=\"_blank\" rel=\"noopener\">Mobileye's Driving Experience Platform: Architecture, Abstractions, and APIs.\u003C\u002Fa> (Replay)\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch3 style=\"font-size: 21px; font-weight: bold;\">Mobileye Brand\u003C\u002Fh3>\n\u003Cp>[**]gallery:mobileye's-logo[**]\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-01-02T08:00:00.000Z",[21,91,78,13,99,64],{"id":422,"type":100,"url":423,"title":424,"description":425,"primary_tag":136,"author_name":136,"is_hidden":96,"lang":132,"meta_description":425,"image":426,"img_alt":427,"content":428,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":429,"tags":430},244,"mobileye-announces-ces-2024-press-conference-with-prof-amnon-shashua","Mobileye Announces CES 2024 Press Conference with Prof. Amnon Shashua  ","Mobileye: Now. Next. Beyond. and additional events presented live from Las Vegas  ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F70e29fa9085f2151107ae35044c5a59b_1703020097934.jpg","President & CEO Prof. Amnon Shashua will deliver his annual CES address on January 9, 2024, at 11:00 a.m. PT.","\u003Cp>\u003Cspan data-contrast=\"none\">Mobileye (Nasdaq: MBLY) will present its 2024 CES Press Conference, \u003C\u002Fspan>\u003Cem>\u003Cspan data-contrast=\"none\">Mobileye: \u003C\u002Fspan>\u003C\u002Fem>\u003Cem>\u003Cspan data-contrast=\"none\">Now. Next. Beyond. \u003C\u002Fspan>\u003C\u002Fem>\u003Cspan data-contrast=\"none\">with President & CEO Prof. Amnon Shashua, on January 9, 2024, at 11:00 a.m. PT.  \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">The annual CES address will explore the state of self-driving, highlighting Mobileye’s advancements in delivering an evolutionary vision of autonomy, including a spectrum of scalable solutions from hands-off\u002Feyes-on ADAS to eyes-off autonomous vehicles. Prof. Shashua will also introduce a new technological breakthrough that unlocks automakers’ ability to configure the driving experience in ways that align with their brand and consumer tastes.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">As a follow up to\u003C\u002Fspan>\u003Cem>\u003Cspan data-contrast=\"none\"> Now. Next. Beyond., \u003C\u002Fspan>\u003C\u002Fem>\u003Cspan data-contrast=\"none\">Mobileye CTO Prof. Shai Shalev-Shwartz will present \u003C\u002Fspan>\u003Cem>\u003Cspan data-contrast=\"none\">Mobileye's Driving Experience Platform: Architecture, Abstractions, and APIs \u003C\u002Fspan>\u003C\u002Fem>\u003Cspan data-contrast=\"none\">on Wednesday, January 10 at 1:00 p.m. PT.\u003C\u002Fspan> \u003Cspan data-contrast=\"none\">Autonomous driving demands weaving a complex AI tapestry with the precision vital for safety-focused systems. This talk will delve into Mobileye's specialized programming platform engineered specifically to meet this challenge. Prof. Shalev-Shwartz will showcase how the platform's APIs provide automakers with the tools to program the AI's functionality to the unique desired driver characteristics of each car model.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Also on Wednesday, January 10, Mobileye Senior Vice President of AV Johann “JJ” Jungwirth will appear on the CES-presented Conference Session panel titled \u003C\u002Fspan>\u003Cem>\u003Cspan data-contrast=\"none\">The Middle Lane: Self-Driving Cars Today \u003C\u002Fspan>\u003C\u002Fem>\u003Cspan data-contrast=\"none\">at 9:00 a.m. PT.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">For updated information on Mobileye’s CES news and events, visit: \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\">www.mobileye.com\u002Fces-2024\u002F\u003C\u002Fa>\u003Cspan data-contrast=\"none\">. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">\u003Cu>Mobileye CES 2024 Events\u003C\u002Fu>\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">CES 2024 Press Conference, \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">Mobileye: \u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">Now. Next. Beyond. \u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cspan data-contrast=\"none\">w\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cstrong>\u003Cspan data-contrast=\"none\">ith Prof. Amnon Shashua\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Tuesday, January 9, 2024, 11:00 a.m. PT\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\">Visit here for registration and livestream details\u003C\u002Fa>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">M\u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">obileye's Driving\u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem> \u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">Experience\u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem> \u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">Platform: Architecture, Abstractions, and \u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"none\">APIs \u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cstrong>\u003Cspan data-contrast=\"none\">with CTO Shai Shalev-Shwartz\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Wednesday, Jan 10, 2024: 1:00-1:40 p.m. PT\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\">Visit here for registration and livestream details\u003C\u002Fa>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"auto\">CES Session \u003C\u002Fspan>\u003C\u002Fstrong>\u003Cstrong>\u003Cem>\u003Cspan data-contrast=\"auto\">The Middle Lane: Self-Driving Cars\u003C\u002Fspan>\u003C\u002Fem>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Featuring Mobileye’s JJ Jungwirth\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Wednesday, January 10, 9:00-9:40 a.m. PT\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.ces.tech\u002Fsessions-events\u002Fauto\u002Fauto01.aspx\">Visit here for more information\u003C\u002Fa>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">+++\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335551550":2,"335551620":2,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">Contacts\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-contrast=\"none\"> \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Dan Galves \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Investor Relations \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"mailto:investors@mobileye.com\">\u003Cspan data-contrast=\"none\">investors@mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Justin Hyde \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Media Relations \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"mailto:justin.hyde@mobileye.com\">\u003Cspan data-contrast=\"none\">justin.hyde@mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559737":-6,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">About Mobileye\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-ccp-props=\"{"201341983":0,"335559737":-6,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 150 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002F\">\u003Cspan data-contrast=\"none\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\">.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559737":-6,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>","2023-12-20T08:00:00.000Z",[21,6,13,27,78,99],{"id":432,"type":141,"url":433,"title":434,"description":435,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":435,"image":436,"img_alt":437,"content":438,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":439,"tags":440},238,"mobileye-supervision-zeekr-19th-asian-games-china","Mobileye SuperVision™ performs at 19th Asian Games in China","Zeekr vehicles equipped with Mobileye hands-off\u002Feyes-on automated driving technology shuttled visitors around Hangzhou during the international sporting event.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F664ad7038fb5e45b46ed745347d29b7e_1699532117828.jpg","Zeekr 001 with Mobileye SuperVision™ at the 19th Asian Games in Hangzhou, China.","\u003Cp>Last month the 19\u003Csup>th\u003C\u002Fsup> Asian Games concluded in Hangzhou, China, bringing together some 12,000 athletes from 45 countries to compete in 481 events across 40 different sports. While the athletes competed in the stadiums and sports complexes across the city, Mobileye technology performed impressively on the surrounding roadways.\u003C\u002Fp>\n\u003Cp>Mobilized in support of the games was a fleet of Zeekr 001 and 009 vehicles equipped with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\">Mobileye SuperVision™\u003C\u002Fa>. The vehicles shuttled athletes, organizers, and media between the athletes' village on the east bank of the Qiantang River and the organizing committee headquarters on the west. The 30-minute route covered 12.6 kilometers (7.8 miles) of hands-off\u002Feyes-on urban driving, including tunnels, intersections, and traffic lights.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe7686af3910f797ec580f1bdcb0fb486_1699532858781.jpg\" alt=\"Mobileye SuperVision™ enables hands-off\u002Feyes-on driving capabilities in vehicles like the Zeekr 001.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fp>\n\u003Cp>The demo drives were conducted by Zeekr with support from Mobileye's AV team on the ground in China. The Zeekrs were among some \u003Ca href=\"https:\u002F\u002Fzgh.com\u002Fmedia-center\u002Fnews\u002F2023-09-03\u002F?lang=en\">2,000 vehicles dedicated for use during the games\u003C\u002Fa> by parent company Geely, which served as Official Mobility Partner for the 19\u003Csup>th\u003C\u002Fsup> Asian Games in Hangzhou. The Asian Games are regarded as the second largest multi-sport event in the world after the Olympics.\u003C\u002Fp>\n\u003Cp>The event followed just weeks after \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-supervision-pilot-functions-added-to-110000-zeekr-vehicles\u002F\">Zeekr over-the-air updated 110,000 of its vehicles\u003C\u002Fa> already in the hands of customers with a major upgrade to their Navigation Zeekr Pilot (NZP) assisted driving system. The upgraded system, based on Mobileye SuperVision, enables point-to-point automated highway navigation, lane changes, on\u002Foff-ramp assist, and intelligent traffic safety functions within identified operational design domains. The Asian Games' host city Hangzhou was among the first locations (alongside Shanghai) in which the feature was unlocked.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff161e816b30baa702b80ffbb10cbefcb_1699532917658.jpg\" alt=\"The Zeekr 001 and 009 were the first vehicles to reach the market with Mobileye SuperVision™.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fsuper-vision\u002F\">Mobileye SuperVision\u003C\u002Fa> is the most advanced of our solutions currently on the market, bridging from today's driver-assistance systems to the self-driving vehicles of tomorrow. It's designed to enable the hands-off driving capabilities of an autonomous vehicle while under the driver's watchful eye. The system incorporates dual EyeQ™ systems-on-chips and 11 cameras for 360-degree computer vision coverage, along with our REM™-generated maps and RSS™-based driving policy.\u003C\u002Fp>\n\u003Cp>The \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-zeekr-ota-update\u002F\">Zeekr 001\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fzeekr-mobileye-supervision\u002F\">Zeekr 009\u003C\u002Fa> were the first vehicles with Mobileye SuperVision to reach the market. The technology has since been announced for integration into future models from \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fporsche-mobileye-supervision-collaboration\u002F\">Porsche\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fpolestar-selects-mobileye-to-bring-autonomous-technology-to-polestar-4\u002F\" target=\"_blank\" rel=\"noopener\">Polestar\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fsmart-chooses-mobileye-supervision-for-advanced-driving-automation\u002F\">Smart\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Ffaw-group-and-mobileye-forge-strategic-alliance-in-autonomous-driving\u002F\">FAW Group\u003C\u002Fa>.\u003C\u002Fp>","2023-11-20T08:00:00.000Z",[21,13],{"id":442,"type":100,"url":443,"title":444,"description":445,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":445,"image":446,"img_alt":447,"content":448,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":449,"tags":450},239,"polestar-4-to-integrate-luminar-lidar-with-mobileye-chauffeur","Polestar 4 to integrate Luminar lidar with Mobileye Chauffeur","A future version of the Polestar 4 will feature Mobileye Chauffeur eyes-off, hands-off technology using Luminar lidar.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fae921496490c0c06f0fe706d2806110b_1699555981959.jpg","The Polestar 4, which will feature Mobileye technology inside","\u003Cp>GOTHENBURG, SWEDEN –\u003Cstrong> \u003C\u002Fstrong>Polestar is working with Luminar, a leading automotive technology company, and Mobileye, a global leader in autonomous driving solutions, to enhance safety and the future autonomous driving capabilities of Polestar 4 with the integration of Luminar’s next-generation LiDAR technology with Mobileye's Chauffeur platform.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fmedia.polestar.com\u002Fglobal\u002Fen\u002Fmedia\u002Fpressreleases\u002F673327\">Announced in August\u003C\u002Fa>, Polestar 4 is planned to be the first production car to feature Mobileye Chauffeur, now with Luminar LiDAR, which builds upon the full-surround camera-based SuperVision platform available in Polestar 4 from launch. Together, the three companies aim to offer eyes-off, point-to-point autonomous driving on highways, as well as eyes-on hands off driving for other environments.\u003C\u002Fp>\n\u003Cp>With Mobileye Chauffeur, Polestar 4 is set to feature three Mobileye EyeQ6 processors, a front-facing LiDAR from Luminar, and Mobileye’s front-facing imaging radar to provide the extra layer of sensing and artificial intelligence needed to enable eyes-off, hands-off driving.\u003C\u002Fp>\n\u003Cp>LiDAR (Light Detection and Ranging) uses lasers to create a highly detailed 3D map of the surrounding environment. Luminar’s LiDAR is uniquely engineered from chip-level up and with a higher wavelength, enabling the greatest level of performance and safety capabilities for production cars. When coupled with Mobileye’s Chauffeur platform, the result will be a turnkey, safer and high-performing automated system.\u003C\u002Fp>\n\u003Cp>Building on the existing relationship between Luminar and Mobileye, the integration of Luminar LiDAR into Polestar 4 also expands the \u003Ca href=\"https:\u002F\u002Fmedia.polestar.com\u002Fglobal\u002Fen\u002Fmedia\u002Fpressreleases\u002F663533\">partnership between Luminar and Polestar\u003C\u002Fa> which was announced in January 2023.\u003C\u002Fp>\n\u003Cp>Thomas Ingenlath, Polestar CEO, says: “Polestar 4 comes with the highly advanced Mobileye SuperVision ADAS from the start, and we look forward to expanding that with Mobileye Chauffeur in the future. Being able to add Luminar’s industry-leading LiDAR to the platform’s development increases the strong link between our companies and brings even more world-class technology to Polestar 4.”\u003C\u002Fp>\n\u003Cp>Prof. Amnon Shashua, CEO of Mobileye, says: “Combining our base SuperVision with an independent second redundant perception system – consisting of Luminar LiDAR, radars and an imaging radar – enables true redundancy and a level of accuracy that lays the foundation for fully autonomous driving.”\u003C\u002Fp>\n\u003Cp>Austin Russell, founder and CEO of Luminar, says: “After collaborating with Mobileye on a solution since 2019, the true fruits of our labour are being realised for the first time by transitioning out of R&D and into a production vehicle with Polestar. Together, we look forward to raising the benchmark in the industry for what a safe and autonomous future can look like.”\u003C\u002Fp>","2023-11-09T08:00:00.000Z",[64,99,21],{"id":452,"type":141,"url":453,"title":454,"description":455,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":455,"image":456,"img_alt":457,"content":458,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":459,"tags":460},229,"volkswagen-id-buzz-mobileye-drive-iaa-mobility-2023","Volkswagen ID. Buzz showcases Mobileye Drive™ at IAA 2023","Electric passenger van on display in Munich incorporates Mobileye's turnkey self-driving solution for autonomous mobility-as-a-service.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F28dd1409e7c45b5d99ee67e3544ceeac_1695134996240.jpg","Showcased at IAA 2023, the VW ID. Buzz with Mobileye Drive™ is testing in Germany and the US. (Photo courtesy of Volkswagen.) ","\u003Cp>The Volkswagen ID. Buzz was one of the stars of this year's IAA Mobility show. On VW's show stand sat a bright yellow camper-van conversion for visitors to explore, while directly across the aisle at our booth, and in the test-drive area outside, appeared the self-driving version you see here.\u003C\u002Fp>\n\u003Cp>The ID. Buzz showcased by \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fdriving-evolution-autonomous-mobility-iaa-2023-munich\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye at the IAA\u003C\u002Fa> is one of the latest vehicles to incorporate Mobileye Drive™, our turnkey self-driving system, and it is \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fvolkswagen-commercial-vehicles-begins-av-testing-with-mobileye-drive\u002F\" target=\"_blank\" rel=\"noopener\">currently undergoing testing\u003C\u002Fa> on both sides of the Atlantic.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FDtM1ahkoR4A?si=45tNQ_Vomzo5XsI8\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>To deliver its autonomous driving capabilities, the vehicle features an array of sensors – including nine high-resolution cameras, four parking cameras, three long-range lidars, and six short-range lidars. To operate safely and effectively, it encompasses Mobileye’s unique tech innovations: True Redundancy™ sensing systems, REM™ crowdsourced AV maps, and the RSS™-based driving policy. \u003Cspan class=\"ui-provider ec bpo bpp bpq bpr bps bpt bpu bpv bpw bpx bpy bpz bqa bqb bqc bqd bqe bqf bqg bqh bqi bqj bqk bql bqm bqn bqo bqp bqq bqr bqs bqt bqu bqv\" dir=\"ltr\">For efficient processing power, it utilizes four EyeQ™6 High systems-on-chips. Future versions are slated to upgrade the EyeQ chips and augment their sensing suite with \u003Ca class=\"fui-Link ___10kug0w f3rmtva f1ewtqcl fyind8e f1k6fduh f1w7gpdv fk6fouc fjoy568 figsok6 f1hu3pq6 f11qmguv f19f4twv f1tyq0we f1g0x7ka fhxju0i f1qch9an f1cnd47f fqv5qza f1vmzxwi f1o700av f13mvf36 f1cmlufx f9n3di6 f1ids18y f1tx3yz7 f1deo86v f1eh06m1 f1iescvh fhgqx19 f1olyrje f1p93eir f1nev41a f1h8hb77 f1lqvz6u f10aw75t fsle3fq f17ae5zn\" title=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-and-valeo-launch-partnership-for-world-class-imaging-radars\u002F\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-and-valeo-launch-partnership-for-world-class-imaging-radars\u002F\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"Link our new imaging radars\">our new imaging radars\u003C\u002Fa>.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>The scope of the technologies on board and the autonomous driving capabilities they deliver make this one of the most advanced in a long line of projects Mobileye has undertaken with the Volkswagen Group to date. Previously announced collaborations include the industry's first camera-only Automatic Emergency Braking system with Audi, the first \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcloud-enhanced-driver-assist\u002F\">Cloud-Enhanced Driver-Assist™\u003C\u002Fa> application with Volkswagen, and integrating the eyes-on\u002Fhands-off driving capabilities of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fporsche-mobileye-supervision-collaboration\u002F\">Mobileye SuperVision™ into new Porsche models\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>This latest project has Volkswagen Commercial Vehicles \u003Ca href=\"https:\u002F\u002Fwww.vwpress.co.uk\u002Fen-gb\u002Freleases\u002F4984\" target=\"_blank\" rel=\"noopener\">testing ID. Buzz autonomous vehicles in Munich\u003C\u002Fa>, Germany, and Volkswagen Group of America \u003Ca href=\"https:\u002F\u002Fmedia.vw.com\u002Fen-us\u002Freleases\u002F1750\" target=\"_blank\" rel=\"noopener\">testing in Austin\u003C\u002Fa>, Texas. Once the vehicle is ready for widespread deployment, VW aims to commence autonomous ridesharing services through its own MOIA division in Europe, and with independent transport operators in the North America.\u003C\u002Fp>\n\u003Cp>The ID. Buzz was one of several autonomous vehicles driven by Mobileye on display at IAA this year. It was joined there by driverless shuttles from \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fholon-mover-ces-mobileye-drive\u002F\">HOLON\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.schaeffler.com\u002Fen\u002Fmedia\u002Fpress-releases\u002Fpress-releases-detail.jsp?id=87942401\">Schaeffler\u003C\u002Fa> – both of which are also enabled by \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fdrive\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye Drive\u003C\u002Fa>, the self-driving solution that's leading the industry towards the future of autonomous mobility.\u003C\u002Fp>\n\u003Cp>[**]gallery:volkswagen-id-buzz-at-iaa-2023[**]\u003C\u002Fp>","2023-09-28T07:00:00.000Z",[78,21,34,84],{"id":462,"type":100,"url":463,"title":464,"description":465,"primary_tag":136,"author_name":136,"is_hidden":96,"lang":132,"meta_description":465,"image":466,"img_alt":467,"content":468,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":469,"tags":470},232,"faw-group-and-mobileye-forge-strategic-alliance-in-autonomous-driving","FAW Group and Mobileye Forge Strategic Alliance in Autonomous Driving","FAW Group aims to initially equip FAW Hongqi vehicles with Mobileye SuperVision™ and Mobileye Chauffeur™ technology, and build a deeper technological alliance.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa046fddaac665842923777c85e3987a5_1694684898541.png","Logos of FAW Group and Mobileye","\u003Cp>CHANGCHUN AND JERUSALEM — FAW Group, one of the largest Chinese automotive groups, and Mobileye (Nasdaq: MBLY), a global leader in autonomous driving solutions, have announced a new strategic partnership leveraging their respective industry advantages in software, hardware and technology products. The two sides will work together to create new products based on Mobileye SuperVision™ and Mobileye Chauffeur™ platforms, to empower customers with safe, enjoyable driving experiences.\u003C\u002Fp>\n\u003Cp>Mr. Qiu Xian Dong, chairman of BOD & secretary of the CPC FAW Group Committee , and Professor Amnon Shashua, President and CEO of Mobileye, held the signing ceremony on September 13, in Changchun. The two companies will start working together on FAW Hongqi brand vehicles, bringing the Mobileye SuperVision highly advanced automated driving assist platform to key models of the Hongqi brand. That will be followed closely by work toward integrating the Mobileye Chauffeur “eyes-off, hands-off\" driving technology for specified domains into the much-anticipated E701 vehicle. The Mobileye SuperVision projects are expected to be deployed by end of 2024, with the Mobileye Chauffeur projects targeted for launch by the end of 2025.\u003C\u002Fp>\n\u003Cp>Meanwhile, other brands of FAW Group are in line to gradually follow, using Mobileye’s platform solutions. In addition, the parties will conduct comprehensive discussions on feasible plans to further deepen their cooperation. \u003C\u002Fp>\n\u003Cp>As a pioneer of China's automotive industry, FAW Group has always been committed to building a world-class, green and intelligent mobility service company that consumers love. Throughout its 70 years of development, FAW Group has been constantly refreshing the user experience through technological innovation and service upgrades.\u003C\u002Fp>\n\u003Cp>Mobileye SuperVision will be an integral part of FAW's advanced driver assistance systems, promising an unparalleled driving experience in its category. Upon its integration Mobileye Chauffeur can provide “hands-off, eyes-off\" autonomy on specified operational domains, with adaptive eyes-on driving in other settings, using the Mobileye SuperVision cameras paired with a front-facing lidar and Mobileye imaging radar. Both systems will utilize Mobileye’s EyeQ™6 SoC, RSS™-based driving policy, a comprehensive 360-degree camera system, and precision mapping.\u003C\u002Fp>\n\u003Cp>“The target of the cooperation between FAW Group and Mobileye, both leaders in their respective fields, is to provide cutting edge ADAS and AV solutions in the Chinese market. This cooperation will deepen the partnership and alliance between the companies. Mobileye’s products will be first equipped on the Hongqi brand, and later expand to the other brands within the FAW Group,” said Mr. Qiu Xian Dong, Chairman of BOD & secretary of the CPC FAW Group Committee.\u003C\u002Fp>\n\u003Cp>“FAW's selection of Mobileye for this venture underscores the magnitude of this collaboration,” said Prof. Amnon Shashua, President and CEO of Mobileye. “Between the scale and expertise FAW has built over the past seven decades and our world-class technology, this alliance could shape the future of autonomous driving in the region and beyond. Drawing from our extensive experience of delivering our technology to more than 150 million vehicles globally, we see a future where autonomous driving improves transportation safety, convenience and accessibility for millions.”\u003C\u002Fp>\n\u003Cp>More details about the projects will be shared in the months ahead.\u003C\u002Fp>","2023-09-14T07:00:00.000Z",[13,99,21,64],{"id":472,"type":57,"url":473,"title":474,"description":475,"primary_tag":5,"author_name":476,"is_hidden":96,"lang":132,"meta_description":475,"image":477,"img_alt":478,"content":479,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":469,"tags":480},233,"are-we-on-the-edge-of-a-chat-gpt-moment-for-autonomous-driving","Are we on the edge of a “ChatGPT moment” for autonomous driving?","Prof. Shai Shalev-Shwartz and Prof. Amnon Shashua discuss the end-to-end approach for solving self-driving vehicle problems, asking if it is both sufficient and necessary.","Prof. Shai Shalev-Shwartz and Prof. Amnon Shashua ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff25b156deca6571a0ee6b607a893ba29_1694719403818.jpg","     ","\u003Cp>Large Language Models (LLMs) such as ChatGPT have revolutionized the world of natural language understanding and generation. Building such models generally has two stages: a general unsupervised pre-training step, and a specific Reinforcement Learning from Human Feedback (RLHF) step. In the pre-training phase, the system “reads” a large portion of the internet (trillions of words) and aims at predicting the next word given previous words, therefore learning the distribution of text over the internet. In the RLHF phase, humans are asked to rank the quality of different answers from the model to given questions, and the neural network is fine-tuned to prefer better answers.\u003C\u002Fp>\n\u003Cp>Recently, Tesla has \u003Ca href=\"https:\u002F\u002Fwww.cnbc.com\u002F2023\u002F09\u002F09\u002Fai-for-cars-walter-isaacson-biography-of-elon-musk-excerpt.html\" target=\"_blank\" rel=\"noopener\">indicated\u003C\u002Fa> they will adopt this approach for end-to-end solving of the self-driving problem. The premise is to switch from a well-engineered system comprised of data-driven components interconnected by many lines of codes to a pure data-driven approach comprised of a single end-to-end neural network. When examining a technological solution for a given problem, the two questions one should ask is whether the solution is \u003Cstrong>sufficient\u003C\u002Fstrong> and whether it is \u003Cstrong>necessary\u003C\u002Fstrong>:\u003C\u002Fp>\n\u003Cul style=\"padding-left: 43px;\">\n\u003Cli>Sufficiency: does this approach tackle all of the requirements of self-driving?\u003C\u002Fli>\n\u003Cli>Necessity: is this the best approach or is it an over-kill (trying to kill a fly with a rocket)?\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Some critical requirements of self-driving systems are transparency, controllability and performance:\u003C\u002Fp>\n\u003Col>\n\u003Cli>Transparency and Explainability: Driving systems must perceive and plan. Perception means creating a factual description of reality (the location of lanes, vehicles, pedestrians and so forth). Planning involves leveraging perception into driving decisions that must balance a tradeoff between usefulness and safety. For example, what speed should the car drive at a residential road with parked vehicles on its sides? Driving slower will be safer; say, in case a child runs into the street from between parked cars. But driving too slow will compromise the usefulness of the function and impede other vehicles. We believe how a self-driving vehicle balances such tradeoffs must be transparent so that society, through regulation, should have a say in decisions that affect all road users.\u003C\u002Fli>\n\u003Cli>Controllability: Reproducible system mistakes should be captured and fixed immediately, while not compromising the overall performance of the system. Furthermore, while human drivers take bad decisions from time to time, like not yielding properly or driving while impaired, society will not tolerate “lapses of judgement” of a self-driving system and every decision should be controllable.\u003C\u002Fli>\n\u003Cli>Performance: The Mean-Time-Between-Failures (MTBF) must be extremely high and non-reproducible errors (“black swans”) should be extremely rare.\u003C\u002Fli>\n\u003C\u002Fol>\n\u003Cp>Now, let us judge the end-to-end solution in light of the above requirements.\u003C\u002Fp>\n\u003Cp>For transparency, while it may be possible to steer an end-to-end system towards satisfying some regulatory rules, it is hard to see how to give regulators the option to dictate the exact behavior of the system in all situations. In fact, the most recent trend in LLMs is to combine them with symbolic reasoning elements – also known as good, old fashion coding. See for example \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2305.10601\" target=\"_blank\" rel=\"noopener\">Tree of Thoughts\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2308.09687\" target=\"_blank\" rel=\"noopener\">Graph-of-Thoughts\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2211.10435\" target=\"_blank\" rel=\"noopener\">PAL\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>For controllability, end-to-end approaches are an engineering nightmare. Evidence shows that the performance of GPT-4 over time \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.09009\" target=\"_blank\" rel=\"noopener\">deteriorates\u003C\u002Fa> as a result of attempts to keep improving the system. This can be attributed to phenomena like catastrophic forgetfulness and other \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2212.09251\" target=\"_blank\" rel=\"noopener\">artifacts of RLHF\u003C\u002Fa>. Moreover, there is no way to guarantee “no lapse of judgement” for a fully neuronal system. The trend in LLMs is to combine LLMs with external, code-based, tools in order to have guarantees on elements of the systems (e.g. “calculator” in \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2302.04761\" target=\"_blank\" rel=\"noopener\">Toolformer\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.ai21.com\u002Fblog\u002Fjurassic-x-crossing-the-neuro-symbolic-chasm-with-the-mrkl-system\" target=\"_blank\" rel=\"noopener\">Jurrasic-x neuro-symbolic system\u003C\u002Fa>).\u003C\u002Fp>\n\u003Cp>Regarding performance (i.e., the high MTBF requirement), while it may be possible that with massive amounts of data and compute an end-to-end approach will converge to a sufficiently high MTBF, the current evidence does not look promising. Even the most advanced LLMs make embarrassing mistakes quite often. Will we trust them for making safety critical decisions? It is well known to machine learning experts that the most difficult problem of statistical methods is the long tail. The end-to-end approach might look very promising to reach a mildly large MTBF (say, of a few hours), but this is orders of magnitude smaller than the requirement for safe deployment of a self-driving vehicle, and each increase of the MTBF by one order of magnitude becomes \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F1604.06915\" target=\"_blank\" rel=\"noopener\">harder and harder\u003C\u002Fa>. It is not surprising that the recent live demonstration of Tesla’s latest FSD by Elon Musk shows an \u003Ca href=\"https:\u002F\u002Fnypost.com\u002F2023\u002F08\u002F29\u002Felon-musk-almost-runs-red-light-livestreaming-tesla-software\u002F\" target=\"_blank\" rel=\"noopener\">MTBF of roughly one hour\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>Taken together, we see many concerns regarding the ability of an end-to-end approach to fully tackle the self-driving challenge. What we would further argue is that an end-to-end approach is an over-kill. The premise of a fully end-to-end approach is “no lines of code, everything should be done by a single gigantic neural network.” Such a system requires maintaining a huge model, with every single update carefully balanced - yet this approach goes against current trends in utilizing LLMs as components within real systems. One such trend is the neural-symbolic approach, in which the fully neuronal LLM is one component within a larger system that uses code-based tools (for example \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2302.04761\" target=\"_blank\" rel=\"noopener\">Toolformer\u003C\u002Fa>). Another trend is the expert approach, in which LLMs are fine tuned to specific, well defined tasks; and the evidence so far is that small dedicated models outperform significantly larger models (e.g. the \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2308.12950\" target=\"_blank\" rel=\"noopener\">code LLaMa project\u003C\u002Fa>). These trends have implications on the data and compute requirements, showing that quality of data, architecture, and system design may be far more important than sheer quantity.\u003C\u002Fp>\n\u003Cp>In summary, we argue that an end-to-end approach is neither necessary nor sufficient for self-driving systems. There is no argument that data-driven methods including convolutional networks and transformers are crucial elements of self-driving systems, however, they must be carefully embedded within a well-engineered architecture.\u003C\u002Fp>",[21,6],{"id":482,"type":141,"url":483,"title":484,"description":485,"primary_tag":77,"author_name":136,"is_hidden":96,"lang":132,"meta_description":485,"image":486,"img_alt":487,"content":488,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":489,"tags":490},230,"johann-jungwirth-the-road-to-self-driving-mobility-iaa-2023","Johann Jungwirth on the road to self-driving mobility","Watch the keynote presentation delivered by Mobileye's Senior Vice President of Autonomous Vehicles at the 2023 IAA Mobility show in Munich.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F321c6156a782b93b7bed223e1473d7ba_1694085306154.jpg","Johann \"JJ\" Jungwirth addressed the industry at IAA 2023 on the bridge we're building from assisted to autonomous driving.","\u003Cp>This week the automotive industry descended on the Bavarian capital of Munich, Germany, for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fiaa-2023\u002F\">IAA Mobility 2023\u003C\u002Fa> – one of the biggest automotive tech events of the year. Mobileye was there on the ground to showcase our latest technologies and solutions on the show floor, with demonstration vehicles on the surrounding roadways, and a keynote presentation delivered by Mobileye’s Senior Vice President of Autonomous Vehicles, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fjohann-jungwirth-driverless-tech-business-faz-podcast\u002F\">Johann \"JJ\" Jungwirth\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>JJ is a 25-year veteran of the industry and a leading authority on self-driving cars and the technological advancements required to make autonomous mobility a reality. In his keynote, entitled \"The Road to Self-Driving Mobility,\" JJ outlined Mobileye's established leadership in driver-assistance technologies and the bridge we're building to autonomous vehicles – from hands-off through eyes-off to completely driverless solutions.\u003C\u002Fp>\n\u003Cp>\"We take an incremental approach\" to autonomous mobility, \"looking at how these products can build on top of each other,\" JJ outlined in his presentation. \"We have solved the hard problems with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fsuper-vision\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye SuperVision™\u003C\u002Fa>, our hands-off product. And that's the baseline for our eyes-off and driverless solutions\" – Mobileye Chauffeur™ and Mobileye Drive™.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fpolestar-selects-mobileye-to-bring-autonomous-technology-to-polestar-4\u002F\" target=\"_blank\" rel=\"noopener\">Vehicles equipped with Mobileye Chauffeur\u003C\u002Fa>, he projected, \"will be, probably for many of us, the first time we'll actually experience AV technology in consumer vehicles.\"\u003C\u002Fp>\n\u003Cp>Watch the full recording in the video below, and watch this space for more from IAA Mobility 2023.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FUdQo7oncZbY?si=O-XtenmqSrnl2eME\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>","2023-09-07T07:00:00.000Z",[21,84,78],{"id":492,"type":100,"url":493,"title":494,"description":495,"primary_tag":136,"author_name":136,"is_hidden":96,"lang":132,"meta_description":495,"image":496,"img_alt":497,"content":498,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":499,"tags":500},231,"smart-chooses-mobileye-supervision-for-advanced-driving-automation","smart chooses Mobileye SuperVision™ for advanced driving automation","Special edition model to feature SuperVision-based features for point-to-point automatic navigation on highways and urban expressways","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb276d53cdcc31545018c4b49dc242be4_1693990413776.png","Smart and Mobileye join forces for SuperVision","\u003Cp>\u003Cem>\u003Cspan data-contrast=\"none\">HANGZHOU AND JERUSALEM, 6 September 2023 — \u003C\u002Fspan>\u003C\u002Fem>\u003Cspan data-contrast=\"none\">smart, the new-premium intelligent all-electric auto brand, announced today a special upcoming model will feature Navigation smart Pilot (NSP) and a series of highly advanced driver-assistance features built upon the Mobileye SuperVision™ system. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">The special edition EV will offer smart Pilot Assist 2.0 version, which will be designed to gradually enable point-to-point automatic navigation on highways and urban expressways, automated lane changes, automated on\u002Foff-ramp assist and intelligent traffic safety functions within identified operational design domains, building off the existing strong safety performance in the smart #1. This special edition will also highlight smart’s global ambitions.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Mr. Yang Jun, Vice President of Global Research and Development at smart Automobile, said: \"Since the birth of the brand, smart has always been led by the vision of exploring the best solutions for future urban mobility. We believe that the smarter ADAS technology, will further enhance the competitiveness of the new generation of smart all-electric product family. Leveraging the R&D capability and the collaboration with industry leading partners, such as Mobileye, smart will continue elevating the brand’s technology label, providing more intelligent, safer urban mobility experience to the users.”\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">The SuperVision-based system leverages 11 cameras – including seven 8-megapixel cameras – and radar, along with a robust driving policy. \u003C\u002Fspan>\u003Cspan data-contrast=\"none\">The system runs on two Mobileye EyeQ5™ system-on-chips, an advanced custom 7-nanometer ADAS chipset, building on Mobileye’s two decades of experience in applied AI and machine learning to handle AI tasks with high energy efficiency, a key consideration for electric vehicles.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">“We’re excited to launch this new era of collaboration with the smart brand, offering new capabilities built from the foundation of our SuperVision technology,” said Johann Jungwirth, senior vice president of autonomous driving at Mobileye. “SuperVision complements smart’s commitment to offering the future of urban mobility globally.” \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">With today’s announcement, smart joins ZEEKR and Polestar in offering SuperVision-based services to customers. More details about the model will be released soon in the fourth quarter of 2023.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":240}\"> \u003C\u002Fspan>\u003C\u002Fp>","2023-09-06T07:00:00.000Z",[99,64,21,13],{"id":502,"type":100,"url":503,"title":504,"description":505,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":505,"image":506,"img_alt":507,"content":508,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":509,"tags":510},227,"mobileye-supervision-pilot-functions-added-to-110000-zeekr-vehicles","Mobileye SuperVision™ Pilot functions added to 110,000 ZEEKR vehicles","OTA update brings innovative, point-to-point automated driving features to customers in China, and has already generated strong word-of-mouth reviews","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fzeekr_3054.jpg","ZEEKR 001 in Shanghai","\u003Cp>Jerusalem, 4 September 2023 — Global mobility technology brand ZEEKR has launched a major over-the-air update for 110,000 owners of the ZEEKR 001 electric vehicle with the global debut of new, highly automated driving assistance features built on the Mobileye SuperVision™ platform. The upgraded Navigation ZEEKR Pilot (NZP) driving assistant system has already received strong reviews from over 1,000 beta users, with class-leading performance.\u003C\u002Fp>\n\u003Cp>NZP leverages SuperVision’s 11 cameras – including seven 8-megapixel cameras – and surround fisheye cameras, along with a front radar and robust driving policy. Key features of NZP include point-to-point automated highway navigation, lane changes, automated on\u002Foff-ramp assist and intelligent traffic safety functions in identified operational design domains.\u003C\u002Fp>\n\u003Cp>The system runs on two Mobileye EyeQ™5 systems-on-chip, an advanced custom 7-nanometer ADAS chipset, building on Mobileye’s two decades of experience in applied AI and machine learning to handle AI tasks with high energy efficiency, a key factor for electric vehicles.\u003C\u002Fp>\n\u003Cp>Thanks to these enabling technologies, NZP can react similarly as a human driver might to everyday driving scenarios within its operational design domains. It can sense speed limit changes, merge into or overtake traffic, and navigate with an appropriate safety margin for construction zones, pedestrians and other road hazards, even in low-light conditions. It also reacts smartly to the other drivers on the road, understanding their behavior, using human-like motions to efficiently merge and mimicking how drivers tend to negotiate key road features. The functions are well recognized by leading industry media for its safety and efficiency performance.\u003C\u002Fp>\n\u003Cp>The system will first be available in the cities of Shanghai and Hangzhou, with multiple cities being added over the next few months. ZEEKR 009 multi-purpose vehicle owners are expected to receive a similar OTA update later this year.\u003C\u002Fp>\n\u003Cp>“We’re proud of the work we’ve done with ZEEKR to launch this successful update of NZP built on the Mobileye SuperVision™ platform,” said Prof. Amnon Shashua, President and CEO of Mobileye. “This jump forward points toward the full power of SuperVision that will enable ZEEKR to provide a seamless and reliable highly assisted driving experience in highway and urban settings. From what we’ve seen, NZP powered by SuperVision has become a market leader, raising the bar not only in China but worldwide.”\u003C\u002Fp>\n\u003Cp>“As a strategic partner of Mobileye, ZEEKR is pleased to provide the industry-leading NZP solution to users to make travel safer and more efficient,” said Andy An, CEO of ZEEKR. “We will continue to further advance technologies to maintain our industry leadership globally.”\u003C\u002Fp>\n\u003Cp>The SuperVision platform enables advanced driver-assist features at up to 130 kilometers per hour, on all road types, as monitored by the driver. It builds on Mobileye’s heritage for automotive safety features and driver assist technologies like automatic emergency braking, and lays the pathway towards fully autonomous consumer vehicles and robotaxis in the near future.\u003C\u002Fp>\n\u003Cp>Under the expanded collaboration with Geely Group, three additional brands under Geely Group’s umbrella are due to leverage Mobileye SuperVision for advanced ADAS, including Polestar. ZEEKR’s new ZEEKR 001 FR quad-motor sports car, which can accelerate from 0 to 100 kph with just 2.08 seconds with rolling start, is the latest model launched to be equipped with Mobileye SuperVision™ platform.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Media Contact: \u003C\u002Fstrong>Justin Hyde, \u003Ca href=\"mailto:Justin.hyde@mobileye.com\">Justin.hyde@mobileye.com\u003C\u002Fa>\u003C\u002Fp>","2023-09-04T07:00:00.000Z",[64,21,99],{"id":512,"type":100,"url":513,"title":514,"description":515,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":515,"image":516,"img_alt":517,"content":518,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":509,"tags":519},228,"mobileye-and-valeo-launch-partnership-for-world-class-imaging-radars","Mobileye and Valeo Launch Partnership for World-Class Imaging Radars","Valeo and Mobileye will work together to bring high-definition imaging radars to production for global automakers.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1a4350d1a77e6c5a7d503dc7fdd64728_1693574090523.png","Bounding boxes illustrate how imaging radar helps AV sensing","\u003Cp>At IAA Mobility 2023 in Munich today, Mobileye and Valeo announced a new partnership to deliver software-defined, best-in-class imaging radars for next-generation driver assist and automated driving features.\u003C\u002Fp>\n\u003Cp>By joining forces, Mobileye and Valeo can quickly bring a promising new technology to automakers worldwide that enables more intelligent vehicles. As a key part of sensing systems for automated driving, imaging radar will be an enabling element for more advanced hands-off ADAS solutions and eyes-off automated driving features on highways and urban streets.\u003C\u002Fp>\n\u003Cp>“Mobileye and Valeo’s Imaging radar collaboration significantly advances a new and exciting phase in automotive safety and performance,” said Nimrod Nehushtan, Mobileye’s Executive Vice President of Business Development and Strategy. “In this collaboration, automakers gain access to the latest cutting edge technology from Mobileye that they can trust will exceed industry expectations as we have proven before, while benefiting from the customization, industrialization, testing and support capabilities brought by Valeo. Our collaboration to deliver imaging radar to automakers benefits the industry, and ultimately, drivers globally.”\u003C\u002Fp>\n\u003Cp>Marc Vrecko, President of Valeo’s Comfort and Driving Assistance Systems Business Group, said:\u003Cem> \u003C\u002Fem>“This partnership reinforces the strong relationship between Valeo and Mobileye. We are proud to collaborate together on Imaging radar technology, which will be essential in the future of autonomous mobility. This is a great illustration of Valeo’s technological leadership in ADAS and of its capability to produce innovative technologies at scale. This collaboration will contribute to Valeo’s commitment to offer affordable, smarter and safer mobility.“\u003C\u002Fp>\n\u003Cp>Mobileye’s imaging radars use advanced architecture, including Massive MIMO (multiple-input, multiple-output) antenna design, a high-end radio frequency design developed in-house, and high-fidelity sampling – all enabling accurate object detection and higher dynamic range. Thanks to an integrated system-on-chip design that maximizes processor efficiency, and world-leading algorithms for interpreting radar data, the imaging radar delivers a detailed, four-dimensional image of surroundings up to 300 meters away and beyond. With a 140-degree field-of-view at medium range and 170-degree field-of-view in close range, the radar enables more accurate detection of pedestrians, vehicles or obstructions that other sensors might miss – even on crowded urban streets.\u003C\u002Fp>\n\u003Cp>Mobileye has already seen high market interest for its Imaging radar from the industry as automakers look to expand the operational design domains of their automated driving features. Valeo has simultaneously received indications of strong demand from the market for imaging radar that achieves optimal performance.\u003C\u002Fp>\n\u003Cp>Valeo, world leader in Advanced Driver Assistance Systems (ADAS), has been developing and mass-producing radar technologies since 2006. Valeo will lead the system design of the new imaging radar product by integrating Mobileye’s groundbreaking imaging radar technology and corresponding software and algorithms embedded in the Mobileye Radar chipset into Valeo’s automotive software and hardware radar solutions. Valeo will meet and adapt to the latest and most stringent software and hardware requirements from automotive players, including functional safety, cybersecurity, fast communication protocols with vehicle networks, electromagnetic robustness, and validation of overall system performance and endurance during vehicle lifetime. Leveraging Valeo’s expertise in producing the latest automotive technologies at scale and its global industrial footprint, the complete Imaging radar solution will be produced by Valeo\u003C\u002Fp>\n\u003Cp>This new partnership expands Mobileye and Valeo successful collaboration on front-facing cameras and other driver assist solutions. Since 2015, the partners have delivered more than 15 million Smart Front Cameras worldwide.\u003C\u002Fp>",[64,49,21,13,99],{"id":521,"type":100,"url":522,"title":523,"description":524,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":524,"image":525,"img_alt":526,"content":527,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":528,"tags":529},226,"ecarx-announces-mobileye-collaboration-for-polestar-future-products","ECARX announces Mobileye collaboration for Polestar, future products ","ECARX Holdings plans to integrate Mobileye Chauffeur™ in the Polestar 4","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa8a3701e248dd7d6cc1e7981ddee5bfc_1693230024446.png","The Polestar 4","\u003Cp>Today, ECARX Holdings announced a collaboration with Mobileye for future autonomous and advanced driver-assist technology. ECARX plans to serve as the integrator for the Mobileye Chauffeur™ platform in the Polestar 4 that will offer hands-off, eyes-off autonomous driving on controlled-access highways in operational-defined domains. ECARX and Mobileye also intend to collaborate on a EyeQ6L-based driver-assist solution, using the latest EyeQ™6 automotive-grade system-on-chip, to serve the diverse needs of the Chinese market.\u003C\u002Fp>\n\u003Cp>Mobileye’s Chauffeur adds a layer of active radar and lidar sensor to Mobileye’s class-leading computer vision perception to create two subsystems working separately and in parallel to ensure redundancy. It also includes Mobileye’s proprietary driving policy platform that can be customized by the automaker. All these elements are designed to run on the ultra-efficient EyeQ6® SoC.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fir.ecarxgroup.com\u002Fnews-releases\u002Fnews-release-details\u002Fecarx-collaborate-mobileye-build-integrated-driver-assist\" target=\"_blank\" rel=\"noopener\">Read more about the announcement here\u003C\u002Fa>.\u003C\u002Fp>","2023-08-28T07:00:00.000Z",[64,99,21,13],{"id":531,"type":100,"url":532,"title":533,"description":534,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":534,"image":535,"img_alt":536,"content":537,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":5,"publish_date":538,"tags":539},224,"polestar-selects-mobileye-to-bring-autonomous-technology-to-polestar-4","Polestar selects Mobileye to bring autonomous technology to Polestar 4","Mobileye Chauffeur™ technology platform to be integrated into Polestar 4","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9c648af2ec5ed4a529249523564dbc08_1692898654016.png","The Polestar 4 electric SUV Coupe. ","\u003Cp>HONG KONG AND JERUSALEM, 25 August 2023 — Polestar and Mobileye (Nasdaq: MBLY and PSNY) are to collaborate to bring autonomous technology to Polestar 4 with potential for other vehicles, using the Mobileye Chauffeur™ AV platform that will be manufactured and integrated by ECARX.\u003C\u002Fp>\n\u003Cp>The intended collaboration reflects Polestar’s mission to not only deliver world-class design and sustainability in its cars, but cutting-edge innovation as well. Mobileye Chauffeur will add an extra layer of on-demand convenience to Polestar’s performance electric vehicles that are primarily designed for driver engagement and exciting dynamics.\u003C\u002Fp>\n\u003Cp>Polestar 4, which goes on sale in China today and globally in 2024, lays the foundation for this technology by featuring a Mobileye SuperVision™-based advanced driver assistance system from the start.\u003C\u002Fp>\n\u003Cp>At launch, Chauffeur will offer hands-off and eyes-off, point-to-point autonomous driving on highways , as well as eyes-on automated driving for other environments, in identified operational design domains.\u003C\u002Fp>\n\u003Cp>Thomas Ingenlath, Polestar CEO, comments: “We are very keen to push innovation in our performance electric vehicles together with Mobileye. We know that driving yourself is not always fun and exciting – this technology means our customers could enable autonomous driving when they want, making all future journeys enjoyable.”\u003C\u002Fp>\n\u003Cp>Both SuperVision and Chauffeur feature Mobileye’s EyeQ™ systems-on-chip, RSS™-based driving policy, 360-degree surround camera system, and REM™-powered Mobileye Roadbook™ map. Chauffeur upgrades SuperVision with the newest EyeQ6 system-on-chip along with next-generation active radar and lidar sensors, providing the additional sensing layer needed for eyes-off autonomous operation – demonstrating how existing eyes-on systems build a bridge to fully autonomous driving.\u003C\u002Fp>\n\u003Cp>“We congratulate Polestar on innovating in consumer vehicles through this program and are proud of our continuing work with the Geely Group in adopting our technology portfolio,” said Prof. Amnon Shashua, President and CEO of Mobileye. “Mobileye Chauffeur will offer consumers a safer, accessible way to enjoy autonomous vehicles as the next revolution in personal transportation. It’s the pinnacle of two decades of our experience applying AI in more than 150 million vehicles worldwide.”\u003C\u002Fp>\n\u003Cp>More details about the integration will be released closer to production launch.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 150 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003Ca href=\"https:\u002F\u002Fcts.businesswire.com\u002Fct\u002FCT?id=smartlink&url=https%3A%2F%2Fwww.mobileye.com&esheet=53539903&newsitemid=20230817465845&lan=en-US&anchor=https%3A%2F%2Fwww.mobileye.com&index=2&md5=dc09cc0681f253ba2b178bfdedda4ac0\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Polestar\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Polestar (Nasdaq: PSNY) is the Swedish electric performance car brand determined to improve society by using design and technology to accelerate the shift to sustainable mobility. Headquartered in Gothenburg, Sweden, its cars are available online in 27 markets globally across North America, Europe and Asia Pacific.\u003C\u002Fp>\n\u003Cp>Polestar plans to have a line-up of five performance EVs by 2026. Polestar 2, the electric performance fastback, launched in 2019. Polestar 3, the SUV for the electric age, launched in late 2022. Polestar 4, the SUV coupé transformed, is launching in phases through 2023 and into 2024. Polestar 5, an electric four-door GT and Polestar 6, an electric roadster, are coming soon.\u003C\u002Fp>\n\u003Cp>The Polestar 0 project is the company’s ambitious goal of creating a truly climate-neutral production car by 2030. The research initiative also aims to create a sense of urgency to act on the climate crisis, by challenging employees, suppliers and the wider automotive industry, to drive towards zero.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Media Contact: \u003C\u002Fstrong>Justin Hyde, \u003Ca href=\"mailto:justin.hyde@mobileye.com\">justin.hyde@mobileye.com\u003C\u002Fa>, +01 202-656-6749\u003C\u002Fp>","2023-08-25T07:00:00.000Z",[21,99,64],{"id":541,"type":100,"url":542,"title":543,"description":544,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":544,"image":545,"img_alt":546,"content":547,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":548,"tags":549},220,"volkswagen-commercial-vehicles-begins-av-testing-with-mobileye-drive","Volkswagen Commercial Vehicles Begins AV Testing with Mobileye Drive™️ ","New VW Pilots Kick Off in Munich, Germany and Austin, Texas","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F487800bab83702bc31049912c78a3e01_1690726252678.png","An all-electric Volkswagen ID. Buzz equipped with Mobileye Drive™️ self-driving technology in Munich, Germany","\u003Cp>Volkswagen Commercial Vehicles has begun testing a self-driving version of the ID. Buzz electric vehicle with Mobileye Drive technology on two continents. In Munich, Germany, and Austin, Texas, Volkswagen will validate the Mobileye Drive-equipped ID. Buzz vehicles with safety drivers on public roads, towards a goal of series production. \u003C\u002Fp>\n\u003Cp>Mobileye Drive incorporates advanced EyeQ™️ Systems-on-Chip (SoCs), as well as Mobileye’s sensing, mapping, and driving policy technologies, to create a unique, full-stack autonomous driving system that can adapt to new locations.  \u003Cbr \u002F> \u003Cbr \u002F>You can read more about Volkswagen's testing in Austin \u003Ca href=\"https:\u002F\u002Fmedia.vw.com\u002Fen-us\u002Freleases\u002F1750\">here\u003C\u002Fa> and Munich \u003Ca href=\"https:\u002F\u002Fwww.vwpress.co.uk\u002Fen-gb\u002Freleases\u002F4984\">here\u003C\u002Fa>.   \u003C\u002Fp>","2023-07-31T07:00:00.000Z",[21,99],{"id":551,"type":141,"url":552,"title":553,"description":554,"primary_tag":41,"author_name":136,"is_hidden":96,"lang":132,"meta_description":554,"image":555,"img_alt":556,"content":557,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":5,"publish_date":558,"tags":559},219,"nimrod-nehushtan-rem-cloud-enhanced-adas-autotech-detroit","The Road to the Future of Mobility is Being Mapped by REM™","\"REM crowdsourced mapping is the foundation on which all our advanced products are built,\" Mobileye SVP Nimrod Nehushtan outlined at AutoTech: Detroit 2023.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F27128f45322c483eaa0cad2e9774c409_1690275739608.jpg","Road Experience Management™ harnesses the power of the crowd to enhance a range of assisted and autonomous driving solutions.","\u003Cp>For more than two decades, Mobileye has been providing the automotive industry with computer-vision technology for advanced driver-assistance systems (ADAS). Today, we offer a full range of mobility solutions, from enhanced ADAS to turnkey self-driving systems. The unique element enabling that expansion and paving the road to the future of mobility, arguably more than any other, is REM™.\u003C\u002Fp>\n\u003Cp>Short for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\">Road Experience Management™\u003C\u002Fa>, REM is Mobileye's proprietary crowdsourced, cloud-connected mapping technology. Nimrod Nehushtan, Mobileye's Senior Vice President of Business Development & Strategy and co-General Manager of REM, spoke at \u003Ca href=\"https:\u002F\u002Fwardsauto.informa.com\u002Fautotech-detroit-agenda\u002F\">AutoTech: Detroit 2023\u003C\u002Fa> about this pivotal technology – which we believe is not only essential to tomorrow's autonomous vehicles, but game-changing for today's driver-assistance systems as well.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Question: Why do vehicles need maps?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Answer: \"A safe and comfortable driving experience relies on a correct and consistent understanding of a lot of different features and attributes of the road,\" Nehushtan explains – from lane marks and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fintelligent-speed-assist-general-safety-regulation\u002F\">traffic signs\u003C\u002Fa> to the curvature of the road. \"There is a lot of variation between geographies, between cities – even within the same country. And different conventions of how traffic lights, for example, are positioned, where they are positioned, how they are associated to driving lanes, and so on. And understanding this through onboard sensors alone [in real time] is a very complicated task.\"\u003C\u002Fp>\n\u003Cp>That's fundamentally why autonomous (among other) vehicles need maps, which provide the vehicle with such information ahead of time. But REM goes beyond the details of the road itself to encompass knowledge of how those roads are used.\u003C\u002Fp>\n\u003Cp>\"When you drive from home to work, you're familiar with the road. You can anticipate what's coming, so you're much less likely to do something dangerous. On the other hand, if you're driving in a new place you've never been before, you're much more likely to do something dangerous, because you don't even understand the rules of the game\" as they're applied in the local driving culture.\u003C\u002Fp>\n\u003Cp>\"That preexisting memory is very useful when driving. And it is very important for us to understand properly, to conceive the driving rules, the driving structure of the road, the dos and don'ts for each and every road in order to drive safely and comfortably everywhere.\" REM is engineered to provide both autonomous vehicles and (through our Cloud-Enhanced Driver-Assist™ solution detailed below) human drivers as well with that familiarity of any road they might drive on… as if they’ve driven there before, even if they haven’t.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9c7590a4ad84a17d7eba1ad576af71d1_1690276739495.jpg\" alt=\"REM aggregates data from millions of vehicles on the road equipped with Mobileye technology.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Q: How does REM crowdsourced mapping work?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>A: \"The common approach today to building high-definition maps is to build a survey fleet that has a lot of different sensors – like lidars and inertial navigation systems and so on. You build this fleet that is relatively expensive and you operate this fleet in areas you want to map,\" explains Nehushtan. \"The problem with this approach is that it is very, very hard to scale\" to cover areas large enough to be useful. In addition, \"without an inherent capability to update the maps and keep them fresh, the product itself will maybe be useful on day one, but as time goes by, it will start to deteriorate.\"\u003C\u002Fp>\n\u003Cp>Mobileye takes a decidedly more efficient and scalable approach to mapping that builds upon our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002F100-million-eyeq-chips\u002F\">established leadership in driver-assistance technology\u003C\u002Fa>. \"We have been delivering safety products in the automotive industry for over two decades now.\" In 2022 alone, \"we delivered more than 33 million products, 33 million \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Feyeq6-system-on-chip\u002F\">chips\u003C\u002Fa>, which means 33 million cars\" driving around with our computer vision technology on board, monitoring and detecting the parameters of their surroundings.\u003C\u002Fp>\n\u003Cp>\"Our idea was to leverage this capability and to simply upload data from these systems to a cloud. It's like uploading a lot of pieces of a puzzle to a cloud,\" where the pieces are put together to create a complete picture of the driving environment. Running all this data through a complex array of proprietary algorithms renders a detailed map of roadways around the world that can be used in \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">a range of ADAS and AV applications\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7806008bec15a0ea019257cf57e32a53_1690276876264.jpg\" alt=\"Information like lane-level traffic-light relevancy helps REM enhanced driver-assistance systems with crowdsourced data.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Q: What kinds of mobility solutions benefit from REM?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>A: \"Having all this history and all this knowledge of how hundreds and thousands of different people drove on [a given] road over a long period of time allows us to give a kind of ‘superpower’ to the system using this map,\" says Nehushtan. \"This database can be used for whatever features we want to offer, whether it's autonomous driving or enhanced driver-assist features.\"\u003C\u002Fp>\n\u003Cp>That starts with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcloud-enhanced-driver-assist\u002F\">Cloud-Enhanced Driver-Assist\u003C\u002Fa>, which marries our proven experience in ADAS tech with the benefits of REM.\u003C\u002Fp>\n\u003Cp>Take, for example, alerting a driver that they're approaching a red light. What might seem like a relatively straightforward function is anything but simple to implement in practice, due especially to the complexity and local variability of traffic-light placement.\u003C\u002Fp>\n\u003Cp>\"You cannot think of a car [today] that offers a safety solution for red light crossing, like emergency braking or alerting when you are about to enter a junction [through] a red light,\" notes Nehushtan. \"Understanding which traffic light is relevant to the lane you're in is a complicated problem. Now, having this database in the cloud allows us to solve this problem by simply connecting the system today to a cloud.\" Armed with the knowledge of which traffic signals are relevant to the lane it's in, the system can alert the driver if they're about to run a red light, helping to avoid potential collisions with cross-traffic, pedestrians, and other road users.\u003C\u002Fp>\n\u003Cp>With Cloud-Enhanced Driver-Assist, several automakers are already using REM to enhance the ADAS in their vehicles. And we're building an array of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fhands-off-eyes-off-taxonomy-for-automated-driving\u002F\">increasingly automated solutions\u003C\u002Fa> incorporating the technology. As Nehushtan points out, \"REM crowdsourced mapping is the foundation on which all of these products are built.\"\u003C\u002Fp>\n\u003Cp>Watch the full presentation below.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F3ldGty5Uz0k\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>","2023-07-25T07:00:00.000Z",[84,21,13,42],{"id":561,"type":141,"url":562,"title":563,"description":564,"primary_tag":58,"author_name":136,"is_hidden":96,"lang":132,"meta_description":564,"image":565,"img_alt":566,"content":567,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":568,"tags":569},217,"see-supervision-handle-difficult-real-world-driving-scenarios","#SeeSuperVision Handle Difficult Real-World Driving Scenarios","In these short videos, see how Mobileye SuperVision™ negotiates some of the most challenging driving scenarios – with eyes on the road but hands off the wheel.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F827744854229a167094fe4b022a01141_1688558391555.jpg","Mobileye SuperVision is engineered to handle difficult maneuvers in real-world driving environments.","\u003Cp>We've written a lot about Mobileye SuperVision™ on these pages. But we also know that a picture can be worth a thousand words, and a moving picture that much more.\u003C\u002Fp>\n\u003Cp>That's why we've been releasing a series of short videos showing SuperVision in action, handling a series of challenging driving maneuvers – on real roads, in actual traffic. And you can find them all in the playlist below.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fvideoseries?list=PLWCfS_Yhbvs5O_PHbKZwHDEib3-ALxs9N\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>When the Going Gets Tough\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>In these videos, you can see how a vehicle equipped with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\">Mobileye SuperVision\u003C\u002Fa> handles a variety of precarious situations, such as suddenly obstructed roadways, busy roundabouts, unprotected left turns, slow-moving trucks, constructions zones, and pedestrian crosswalks.\u003C\u002Fp>\n\u003Cp>These are all difficult situations that drivers regularly encounter on the road – situations we've all had to learn how to negotiate when driving. And much like the instructors who taught us these vital skills, we've trained our hands-off\u002Feyes-on solution to handle them safely and effectively – so you won't have to.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Tech to Enable Eyes-On\u002FHands-Off Driving\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Mobileye SuperVision is capable of handling these situations thanks to years of development and decades of expertise in assisted and autonomous driving technologies. SuperVision incorporates our 360-degree surround \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcamera-first-approach-for-assisted-autonomous-driving\u002F\">camera system\u003C\u002Fa>, along with our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frem-mapping-avs\u002F\">REM™\u003C\u002Fa>-generated maps and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fresponsibility-sensitive-safety-unwritten-rules-of-the-road\u002F\">RSS™\u003C\u002Fa>-based driving policy – all running on a pair of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Feyeq6-system-on-chip\u002F\">our latest EyeQ™ systems-on-chip\u003C\u002Fa>.\u003Cbr \u002F>\u003Ciframe src=\"https:\u002F\u002Fplayer.vimeo.com\u002Fvideo\u002F842482816?h=6f8c5805f0&autoplay=1&loop=1&title=0&byline=0&portrait=0\" width=\"640\" height=\"360\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003Cbr \u002F>These highly advanced technological building blocks enable a vehicle equipped with SuperVision to change lanes, cruise on the highway, move through traffic jams, track other road users, and avoid collisions… even where, as the videos above demonstrate, driving gets tricky.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Coming to a Road Near You\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Mobileye SuperVision is already on the road in more than 100,000 vehicles from our launch partner \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-zeekr-expand-future-cars-partnership\u002F\">Zeekr\u003C\u002Fa>. And with further collaborations already in place with automakers like \u003Ca href=\"https:\u002F\u002Fnewsroom.porsche.com\u002Fen\u002F2023\u002Fcompany\u002Fporsche-mobileye-collaboration-automated-driver-assistance-functions-32250.html\">Porsche\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fmedia.polestar.com\u002Fglobal\u002Fen\u002Fmedia\u002Fpressreleases\u002F666140\">Polestar\u003C\u002Fa>, it's slated to be integrated into even more. So, before long, you might find yourself riding in a vehicle equipped with SuperVision. And when you do, we hope you'll feel that you're in good hands – so you can comfortably take yours off the wheel.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F96280afd0d2a4408149cedc1455fbb81_1688558449454.jpg\" alt=\"The Zeekr 001 is the first vehicle on the market to incorporate the hands-off\u002Feyes-on capabilities of Mobileye SuperVision.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fstrong>\u003C\u002Fp>","2023-07-10T07:00:00.000Z",[13,84,21],{"id":571,"type":141,"url":572,"title":573,"description":574,"primary_tag":58,"author_name":136,"is_hidden":96,"lang":132,"meta_description":574,"image":575,"img_alt":576,"content":577,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":578,"tags":579},215,"mobileye-cto-prof-shai-shalev-shwartz-ecomotion-2023","Mobileye CTO: “AVs Are Part of the Future and Are Here to Stay”","Speaking at EcoMotion 2023, Prof. Shai Shalev-Shwartz outlined two obstacles on the road to the autonomous future – and Mobileye’s approach to overcoming both.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F48ab1e7f7ac60427ac8b776d8d2a6f60_1687166825763.jpg","Mobileye CTO Prof. Shai Shalev-Shwartz spoke about the autonomous future at EcoMotion 2023. (Photos: Noga Shadmi van de Reep)","\u003Cp>Are autonomous vehicles “dead or inevitable?” That’s one question which the \u003Ca href=\"https:\u002F\u002Fwww.ecomotionweek.com\u002F\">EcoMotion\u003C\u002Fa> conference sought to tackle this year. And to answer, they brought in our Chief Technology Officer, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-cto-wins-prestigious-michael-bruno-award\u002F\">Prof. Shai Shalev-Shwartz\u003C\u002Fa>, who spoke on a panel together with former Florida state senator Jeff Brandes, moderated by \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Finterview\u002Fautonocast-prof-amnon-shashua-taxonomy\u002F\">\u003Cem>Autonocast\u003C\u002Fem>\u003C\u002Fa> co-host Alex Roy.\u003C\u002Fp>\n\u003Cp>“By now there is evidence that self-driving is possible,” said Prof. Shalev-Shwartz. “We see self-driving cars in the streets of San Francisco and Austin. So I think that we are beyond this obstacle. The problems are different.”\u003C\u002Fp>\n\u003Cp>Those problems are the same that Shalev-Shwartz and his colleagues \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F1708.06374\">laid out in a research paper six years ago\u003C\u002Fa>, namely: safety and scalability.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff844b86f4334aff4258d9ddaf01125d6_1687181105168.jpg\" alt=\"EcoMotion 2023 featured a panel discussion between Prof. Shai Shalev-Shwartz, Jeff Brandes, and Alex Roy.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fp>\n\u003Cp>To tackle the former, Mobileye formulated the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fresponsibility-sensitive-safety-unwritten-rules-of-the-road\u002F\">Responsibility-Sensitive Safety™\u003C\u002Fa> model (RSS™). As Shalev-Shwartz put it: “There is no way to guarantee absolute safety. So the question is, if we cannot guarantee absolute safety, what can we guarantee? And how can we have a language that enables us to talk about exactly what is ‘safe’ and what is ‘not safe’?” That’s what RSS seeks to define, he noted. “If everybody would act according to RSS, then there would be no accidents at all.”\u003C\u002Fp>\n\u003Cp>The key to scalability and economic viability, according to Shalev-Shwartz, is to take a long view towards the autonomous future, maintain the profitability needed to stay the course, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fhands-off-eyes-off-taxonomy-for-automated-driving\u002F\">clearly and honestly communicate the technology’s capabilities\u003C\u002Fa> along the way. “We view AVs as a marathon and not a short sprint. We are trying to be very honest about what the technology is capable of, and what the technology is not capable of.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F75355ee65bca48eafa0fb8514c373ae0_1687181324356.jpg\" alt=\"Mobileye Chief Technology Officer Prof. Shai Shalev-Shwartz speaks about autonomous vehicles at EcoMotion Week 2023.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fp>\n\u003Cp>“We believe that the right way to win a marathon is to start with the foundations and then make incremental changes, incremental improvements, while having a solid business all the time, rather than trying to make promises or to go all the way to something that you cannot hold your breath for long enough,” said Shalev-Shwartz. “This was Mobileye’s approach from day one. We have a solid ADAS business, we are profitable all the time. We're developing autonomous vehicles and we are profitable all the time. Then we make the next step to \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\">SuperVision\u003C\u002Fa>,” Mobileye’s hands-off\u002Feyes-on solution and a vital step along the path to \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fwhen-will-self-driving-cars-be-available\u002F\">the incremental deployment of autonomous-driving technologies\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>“This is the approach. No hype – just be honest about what you're giving and do useful products that people can enjoy today, have a solid business, and make progress.”\u003C\u002Fp>\n\u003Cp>Ultimately, Prof. Shalev-Shwartz concluded, “I think the future is going to be very, very interesting. And I think AVs are part of the future and are here to stay, and we will all enjoy them in the future.”\u003C\u002Fp>\n\u003Cp>Watch the full session in the video below.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FZdWne6VnCyw\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>","2023-06-20T07:00:00.000Z",[21,84],{"id":581,"type":141,"url":582,"title":583,"description":584,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":584,"image":585,"img_alt":586,"content":587,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":5,"publish_date":588,"tags":589},213,"autonomous-vehicle-day-the-self-driving-stack","How Autonomous Vehicles Work: the Self-Driving Stack","To celebrate Autonomous Vehicle Day, we’re going back to basics and looking at the foundational technology that makes autonomous driving possible.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff136d554be484a39fc8e368eccfc090e_1685551843254.png","Mobileye develops a full range of technologies to enable autonomous driving on all road types, from highways to city streets.","\u003Cp>In one of the most popular of our \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=pDyMzz8HMIc&t=13s\">unedited self-driving videos\u003C\u002Fa>, an autonomous vehicle (AV) takes on the task of driving through one of the most challenging urban driving environments for any driver—human or otherwise: Jerusalem.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\" target=\"_blank\" rel=\"noopener\">Jerusalem\u003C\u002Fa> is a 5,000-year-old labyrinth of unplanned ancient pathways that have transformed into modern roadways. Traffic can be unpredictable and intense, presenting a completely different driving experience from the planned organization of a modern city.\u003C\u002Fp>\n\u003Cp>Autonomous Vehicle Day offers a perfect occasion to both appreciate and examine the enormity of the technological achievement involved in driving autonomously in such a difficult environment.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The “Brain” of a Self-Driving Car\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>“A self-driving car must work flawlessly and be able to navigate through obstacles and other road users. To do that, it needs a very smart brain,” explains Mobileye’s Chief Technology Officer, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-cto-wins-prestigious-michael-bruno-award\u002F\" target=\"_blank\" rel=\"noopener\">Prof. Shai Shalev-Shwartz\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>That “smart brain” in an AV, consisting of software running on \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" target=\"_blank\" rel=\"noopener\">powerful microprocessors\u003C\u002Fa>, is called the “self-driving stack”. This is what allows an AV to successfully complete such delicate maneuvers as making natural unprotected left turns and veering slightly to avoid an open door (to name just a couple).\u003C\u002Fp>\n\u003Cp>Just as we can divide the human brain into various functional layers, we can also divide the brain of a self-driving car into the following functional layers: \u003Cbr \u002F>- Sensing\u003Cbr \u002F>- Perception\u003Cbr \u002F>- Localization\u003Cbr \u002F>- Planning\u003Cbr \u002F>- Control\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>How a Self-Driving Car Senses\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F5a9d96f8400e0c5f402a91106d4b1985_1685610377231.jpg\" alt=\"Active radar and lidar sensors compliment cameras to complete the sensing state in Mobileye’s autonomous-driving solutions.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Ch4>\u003Cstrong>It Starts with a Camera\u003C\u002Fstrong>\u003C\u002Fh4>\n\u003Cp>Self-driving cars are equipped with a variety of sensors that serve as the “eyes” of the vehicle and comprise the sensing layer. Not surprisingly, the main sensors that AVs use are the sensors that are most similar to the eyes of a human driver—\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcamera-first-approach-for-assisted-autonomous-driving\u002F\">cameras\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>Cameras of various resolutions, sizes, and angles are typically mounted on the windshield, bumpers, and side mirrors. Working together, the cameras are able to capture a 360° surround view of the vehicle.\u003C\u002Fp>\n\u003Cp>Cameras are superior to other sensors in detecting colors and shapes, so they are good at detecting lane markers, road signs, other vehicles, and various other objects in the driving environment.\u003C\u002Fp>\n\u003Ch4>\u003Cstrong>Another Layer of Accuracy\u003C\u002Fstrong>\u003C\u002Fh4>\n\u003Cp>Of course, cameras have their limitations—especially in poor lighting or weather conditions. That’s why the cameras in AVs are supplemented with inputs from other sensors, such as \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fradar-lidar-next-generation-active-sensors\u002F\">radar and lidar\u003C\u002Fa>, to provide a more comprehensive view of the vehicle’s surroundings.\u003C\u002Fp>\n\u003Cp>Compared to camera sensors, radar works reliably well in low-visibility conditions such as rain, snow, and fog. However, unlike cameras, radar is not good at modeling the precise shape of an object.\u003C\u002Fp>\n\u003Cp>Lidar, an acronym for Light Detection and Ranging, is a technology that is similar to radar, but uses laser light pulses instead of radio waves to measure distance and create a 3D map of its environment.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Putting it All Together\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F97d05301af3b438b972736b0c2bac5c7_1685552940517.jpg\" alt=\"Through our True Redundancy™ approach to sensing, Mobileye utilizes a variety of sensors to enable autonomous driving.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Cp>The process of combining inputs from all sensors (cameras, radar, and lidar) to create an image of the world is called “sensor fusion”.\u003C\u002Fp>\n\u003Cp>There are two main types of sensor fusion, called early and late sensor fusion, which indicate at what point data received from the various sensors is combined. In early sensor fusion, raw data is fused and then object detection algorithms are applied. In late sensor fusion, object detection algorithms are applied to the data before fusing the resulting 3D maps.\u003C\u002Fp>\n\u003Cp>While early sensor fusion is the industry standard, Mobileye’s self-driving system uses late sensor fusion. We also employ \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\">sensor redundancy\u003C\u002Fa> to create independent models of the road environment that can each provide the perceptual information needed to drive the AV if one system fails.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Making Sense of it All \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Once sensor data has been received, the car’s onboard computer needs to make meaning of it. Is that a billboard or a truck? Where is the edge of the road?\u003C\u002Fp>\n\u003Cp>A whole subfield of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fceo-amnon-shashua-on-the-technological-megashifts-impacting-our-world\u002F\" target=\"_blank\" rel=\"noopener\">artificial intelligence\u003C\u002Fa>, called \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcomputer-vision-eccv-2022\u002F\" target=\"_blank\" rel=\"noopener\">computer vision\u003C\u002Fa>, is dedicated to this task. This has been one of the main areas of focus at Mobileye for over two decades.\u003C\u002Fp>\n\u003Cp>Computer vision algorithms—which include \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=GjmZyMWo7YY\">object recognition\u003C\u002Fa>, pattern recognition, clustering algorithms, and more—are applied to the data, allowing the car to detect lane markings, street signs, traffic lights, and other objects in the environment.\u003C\u002Fp>\n\u003Cp>Custom algorithms are even developed to detect such situations as open car doors and the hand signals of traffic police.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ffe4450c54de59cab0969905a1f71a6b2_1685552815408.jpg\" alt=\"Mobileye employs proprietary computer-vision algorithms to identify objects and other road users in its driving environment.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Ch3>\u003Cstrong>Precisely Locating Itself on a Map\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Localization, another essential layer of the self-driving stack, is the process of determining a vehicle's precise location relative to its surroundings, which is essential to enabling the car to make informed driving decisions and plan a trip.\u003C\u002Fp>\n\u003Cp>GPS is commonly used for initial localization, but it has limitations in terms of accuracy, especially in urban environments with tall buildings that can interfere with satellite signals. When safety is critical, localization has to be accurate within centimeters, not meters and inertial sensors, cameras, lidar, and radar provide more precise location information.\u003C\u002Fp>\n\u003Cp>The use of high-definition maps is another important step in the process of localization because they contain exact information about the location of static features of the road such as curbs and pedestrian crossings. This allows the vehicle to more accurately determine its position relative to the road and “fill in the gaps” where sensor data may be incomplete.\u003C\u002Fp>\n\u003Cp>Once it obtains an accurate map of the road environment, the AV uses various algorithms to determine its exact location and orientation. The algorithms take into account factors such as the car's velocity, steering angle, and other sensor readings to calculate the vehicle's precise location.\u003C\u002Fp>\n\u003Cp>Mobileye’s approach to mapping, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\">Road Experience Management™\u003C\u002Fa> (or REM™), rather than using a static HD map, uses anonymous data crowdsourced from around the world, resulting in dynamic, continuously updated maps.\u003C\u002Fp>\n\u003Cp>The maps generated by Mobileye’s REM technology provide a richness of map semantics, which means that our mapping technology goes an important step further than most mapping technologies–it also captures how drivers use roads and the environment around them. For example, using REM, a vehicle is not only able to perceive a traffic light, but “understands” which lane (or lanes) is associated with it.  \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Planning Layer of Autonomous Driving\u003C\u002Fstrong>           \u003C\u002Fh3>\n\u003Cp>If you are a self-driving car and you know what the world looks like and where you are exactly, you’ve come a long way. Now, you just need to make decisions based on this world model and create a plan to get to your destination. That’s where the next layer of the self-driving stack comes in.\u003C\u002Fp>\n\u003Cp>When planning a trip, the AV needs to plan a route to get from point A to point B. However, in AVs, the planning layer consists of many types of planning—including motion planning, decision-making, collision avoidance, and behavioral planning.\u003C\u002Fp>\n\u003Cp>For instance, collision avoidance algorithms ensure the vehicle avoids moving and static objects on the roadway to keep everyone safe. Other algorithms that are part of the planning layer ensure that occupants perceive the trip as safe and comfortable (i.e., no sudden accelerations or braking) and that the car drives according to traffic laws.\u003C\u002Fp>\n\u003Cp>Motion planning algorithms make decisions about such maneuvers as lane changes and merges. The AV also needs to take into account what objects in the roadway might do, which is referred to as behavioral planning.\u003C\u002Fp>\n\u003Cp>Mobileye has added an extra layer of safety to the planning process with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fresponsibility-sensitive-safety-unwritten-rules-of-the-road\u002F\">Responsibility-Sensitive Safety™\u003C\u002Fa> (or RSS™).  Our open mathematical model for AV safety and the basis for our driving policy, RSS is based on transparent and verifiable rules for balancing cautious and assertive driving.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Controlling the Car\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Once the car’s computer has determined how to safely move based on sensor information, perception, and planning, it now needs to control the vehicle in the same way that a human driver would. Just as a human brain controls the movements of our limbs to allow us to navigate our world, an AV’s computer also controls the brakes, steering wheel, accelerator, and other components.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>In celebration of AV Day, we've delved into some of the inner workings of this life-changing technology. From sensors and algorithms to crowd-sourced mapping and behavioral planning, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fhistory-autonomous-vehicles-renaissance-to-reality\u002F\">self-driving cars have come a long way\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>Imagine a future where road accidents are a thing of the past and time spent driving is transformed into productivity, leisure, and family time.  \u003C\u002Fp>\n\u003Cp>At Mobileye, this vision is fast becoming reality, and we’re excited about what that means for the future of mobility.\u003C\u002Fp>","2023-05-31T07:00:00.000Z",[21],{"id":591,"type":141,"url":592,"title":593,"description":594,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":594,"image":595,"img_alt":596,"content":597,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":598,"tags":599},197,"hands-off-eyes-off-taxonomy-for-automated-driving","Hands Off, Eyes Off: A New Taxonomy for Automated Driving","Instead of autonomous driving levels, our new taxonomy defines assisted and autonomous driving systems by degree of driver involvement.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3409a38e85102714bbffb31a0475ca85_1675343297877.png","Mobileye formulated a new framework for assisted and autonomous driving to be understandable by everyone.","\u003Cp>Language matters. Words have power. They help us to define things properly, to understand them, and to understand one another. So, when the existing lexicon leaves too much room for confusion, we need new terminology that clarifies and simplifies the subject matter. And that is precisely what we outlined \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fces-2023-recap\u002F\">at CES\u003C\u002Fa> earlier this year: a \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fdefining-a-new-taxonomy-for-consumer-autonomous-vehicles\u002F\">new taxonomy\u003C\u002Fa> for assisted and autonomous driving that’s both accurate and easy to understand.\u003C\u002Fp>\n\u003Cp>“The discourse today is Level 2, Level 3, Level 4.... This taxonomy is good for engineers,” Mobileye CEO & founder \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Famnon-shashua\u002F\">Prof. Amnon Shashua\u003C\u002Fa> said at CES 2023. But what we really need is “a product-oriented language. So, we created our own language which says that there is eyes-on\u002Feyes-off, there is hands-on\u002Fhands-off, there is a driver or no driver. That’s it.”\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FUCBlR4QFQCA?clip=UgkxB-CV4Be0J8rQHU7cOTxW7dY_KUTn5y5e&clipt=EJCfKRjbwSs\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>Here’s the logic behind this new taxonomy, and how it applies to \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">various types of driving systems\u003C\u002Fa>.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Simplifying the Relationship Between Driver and Vehicle\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Until now, the capabilities of assisted and autonomous driving technologies have been categorized into six levels of driving automation. That taxonomy was first defined in 2014 under \u003Ca href=\"https:\u002F\u002Fwww.sae.org\u002Fblog\u002Fsae-j3016-update\">SAE J3016\u003C\u002Fa>, a standard issued by SAE International (formerly known as the Society of Automotive Engineers). At one end of the spectrum sits Level 0, with no significant form of driver assistance whatsoever. At the other end, Level 5 autonomous driving describes vehicles capable of operating autonomously anywhere and everywhere. Everything else falls into one of the levels in between.\u003C\u002Fp>\n\u003Cp>The SAE levels of automation have been adopted widely across the industry, and arguably represent the most useful taxonomy we’ve had until now. But does these autonomous driving levels clearly and effectively convey a vehicle’s capabilities? Will the layperson understand where their responsibilities as a driver end and where the vehicle’s begin (without either a chart or an in-depth understanding of the technology)?\u003C\u002Fp>\n\u003Cp>As the technologies have developed and evolved, the autonomous driving levels are no longer the most effective way of characterizing a vehicle’s automation – particularly with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Funderstanding-l2-in-five-questions\u002F\">the emergence of L2+\u003C\u002Fa>, the lack of clarity regarding the man\u002Fmachine interaction under L3, and the practical differences between L4 and L5 having been diminished by \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frem-mapping-avs\u002F\">widespread mapping\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>So instead of levels of automation defined by engineers for engineers, we set out to characterize the relationship between human and machine based on the simple questions that matter most to drivers (among others), namely:\u003Cbr \u002F>1. Does the driver need to keep hands on the wheel? \u003Cbr \u002F>2. Does the driver need to keep a watchful eye on the road? \u003Cbr \u002F>3. Does the vehicle even need a driver at all?\u003C\u002Fp>\n\u003Cp>The answers to these questions clearly define which responsibilities rest with the driver and which with the vehicle, and in what types of driving environments.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F4b7e967e74b128bff373a8c1847d7c2f_1675343014441.png\" alt=\"One of our most advanced solutions, Mobileye SuperVision is a hands-off\u002Feyes-on driver-assistance system.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Terminology in Action\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The baseline assumption governing automobile operation over most of its history has been that a human driver is solely responsible for controlling the vehicle and watching the road at all times – hands-on, eyes-on. But that’s begun to change with the advancement of driver-assistance systems and the development of autonomous vehicles.\u003C\u002Fp>\n\u003Cp>With a solution like \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fsuper-vision\u002F\">Mobileye SuperVision™\u003C\u002Fa>, for example, the driver can take hands off the wheel and let the vehicle operate itself on all regular road types. But responsibility and overall control still rest with the driver, who must supervise the vehicle’s operation at all times. Mobileye SuperVision, then, is a hands-off\u002Feyes-on system.\u003C\u002Fp>\n\u003Cp>For Mobileye Chauffeur™, we add \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fradar-lidar-next-generation-active-sensors\u002F\">active sensors\u003C\u002Fa> (such as radar and lidar) to the computer vision, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\">specialized crowdsourced maps\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\">lean driving policy\u003C\u002Fa> that go into Mobileye SuperVision. These \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\">redundant\u003C\u002Fa> active sensors will allow drivers to take not only take their hands off the wheel, but their eyes off the road as well – within specific driving environments, or what engineers call Operational Design Domains. (Like a vacuum cleaner may be designed to work indoors and a lawnmower outdoors, a system might be restricted to driving autonomously only on certain road types as its Operational Design Domain expands.)\u003C\u002Fp>\n\u003Cp>Mobileye Drive™, meanwhile, further builds upon the capabilities of Mobileye Chauffeur with the addition of a tele-operation system. That added capability is incorporated to handle the few remaining rare cases where human involvement may be required, allowing for the removal of the driver from the equation entirely.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff0360b340e9082d4e3e79c4e9760f080_1675342547123.png\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff0360b340e9082d4e3e79c4e9760f080_1675342547123.png\" alt=\"Classifying the capabilities of Mobileye's advanced solutions according to our new taxonomy for automated driving technologies.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>Sounds simple enough, right? We certainly hope so. Because while the technologies that go into these systems are highly complex, we believe their capabilities need to be expressed as simply and clearly as possible – not just for the benefit of those developing the technologies, but for the general public who will be using them as well.\u003C\u002Fp>","2023-05-22T07:00:00.000Z",[13,21],{"id":601,"type":100,"url":602,"title":603,"description":604,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":604,"image":605,"img_alt":606,"content":607,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":608,"tags":609},212,"mobileye-and-man-truck-bus-launch-collaboration-for-av-city-buses"," Mobileye and MAN Truck & Bus launch collaboration for AV city buses  ","Together, we're launching a multi-level cooperation to expand Mobileye Drive™ into city buses  ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe82f7961494b551f4dbdb22ab063a582_1687163362038.png","MAN Truck & Bus and Mobileye collaborate on autonomy in public transit","\u003Cp>\u003Cspan data-contrast=\"auto\">Mobileye and MAN Truck & Bus today announced a collaboration to explore autonomy in public transit, integrating state-of-the-art autonomous vehicle technology into the award-winning city buses of MAN. This builds on Mobileye’s strategy of working closely with vehicle manufacturers to integrate autonomous technology seamlessly across platforms.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">This new collaboration is a milestone for MAN to further the path to urban bus automation. AVs will be able to significantly improve the total cost of ownership and lower the impact of expected driver shortages.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">“We are excited to work with MAN Truck & Bus to demonstrate the benefits of self-driving buses. Our Mobileye Drive™ system offers a flexible and scalable AV solution that can be used in various purpose-built vehicle platforms,” said Johann Jungwirth, Senior Vice President, Autonomous Vehicles at Mobileye.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Mobileye Drive envisions a cutting-edge, comprehensive self-driving solution for commercial use by vehicle manufacturers. It includes Mobileye's advanced EyeQ™ systems-on-chip, as well as sensing, mapping, and driving policy technologies to build a full-stack autonomous driving system for designated design domains. Mobileye Drive's sensor configuration consists of an array of cameras, radars, and lidars that can be adapted to a variety of vehicle platforms – with MAN as its first application in bus transit.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">Mobileye will utilize the knowledge gained through first test operations with Mobileye Drive in Germany to implement into the MAN city bus. The program’s first milestone will be to integrate Drive into a MAN Lion’s City E bus with a safety driver as part of a larger research project in Munich, Germany, targeted for 2025. Following that trial, further test projects would be launched, building toward a goal of series production by the end of the decade.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":160,"335559740":259}\"> \u003C\u002Fspan>\u003C\u002Fp>","2023-05-17T07:00:00.000Z",[21,99,34],{"id":611,"type":141,"url":612,"title":613,"description":614,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":614,"image":615,"img_alt":616,"content":617,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":618,"tags":619},205,"autonomous-vehicle-frequently-asked-questions-faq-answers","Autonomous Vehicle Questions Get the Answers They Deserve ","Today we’re answering some of your most pressing questions on our self-driving technology, as we advance towards the future of autonomous vehicles.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ffd47f7ecb883325f8839a342e42e6215_1679308858729.jpg","Though highly complex, Mobileye develops the advanced technologies for autonomous vehicles to be as transparent as possible.","\u003Cp>Mobileye periodically releases \u003Ca href=\"https:\u002F\u002Fyoutube.com\u002Fplaylist?list=PLWCfS_Yhbvs5MtQIjNfN-xLU30mc1qjEc\">footage of our autonomous vehicles (AVs) out testing around the world\u003C\u002Fa>. We’ve published numerous videos of our camera-only developmental AVs driving in locations across Asia, Europe, and North America, and most recently released another showing our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-detroit-united-states\u002F?trk=organization_guest_main-feed-card_feed-article-content\">Mobileye Drive™ test vehicle\u003C\u002Fa> (with cameras, radars, and lidars) navigating the complex streets of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\">Jerusalem at night\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>The videos show vehicles equipped with our self-driving technologies maneuvering in real-world conditions, alongside actual traffic, in densely packed city centers, tackling the same challenges a human driver would face. The unvarnished glimpse they provide into our technologies at work have made them some our most popular videos. They’ve also sparked some excellent questions across various online platforms, and today we’re answering some of them.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb768f774a0b45beb1b29d3d6a018426d_1679309792882.jpg\" alt=\"\" width=\"1650\" height=\"930\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Question: In what locations and under what conditions is Mobileye testing its autonomous-vehicle technologies?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Answer: Our testing of autonomous vehicles began (and continues) in our hometown of Jerusalem, Israel. The city presents a particularly challenging set of driving conditions, including narrow streets, heavy stop-and-go traffic, a large volume of pedestrians (including lots of baby strollers), frequent jaywalking, ongoing roadworks, and often-aggressive, hurried drivers.\u003C\u002Fp>\n\u003Cp>These conditions make Jerusalem an excellent testing environment, but we’re not limiting ourselves to the one location; rather, over the past few years, we’ve expanded testing to other environments around the world, including Tokyo, Shanghai, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fparis-ratp-autonomous-vehicle-testing-pilot\u002F\">Paris\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmunich-av-video\u002F\">Munich\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-testing-miami-stuttgart\u002F\">Stuttgart\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-detroit-united-states\u002F\">Detroit\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fpress-kit\u002Fpress-kit-mobileye-new-york-city\u002F\">New York\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-testing-miami-stuttgart\u002F\">Miami\u003C\u002Fa>. We’re testing on a variety of road types, both day and at night, and in a multitude of driving conditions.\u003C\u002Fp>\n\u003Cp>\u003Cem>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F254e2f53ba72e83e2d6dd10d414e4d96_1681912999070.jpg\" alt=\"A Mobileye autonomous development vehicle opposite the Eifel Tower, pictured while undergoing testing in Paris.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>Key to our geographic scalability is our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\">Road Experience Management™ (REM™)\u003C\u002Fa> technology. REM crowdsources data from millions of vehicles around the globe equipped with Mobileye technology, and creates a map of all the roads they’re traveling to inform the AV about what to “expect” on those roads.\u003C\u002Fp>\n\u003Cp>By undertaking such rigorous testing, we aim to better prepare our self-driving solutions to handle whatever conditions they may face out there on the road – regardless of the location, driving environment, weather, or other conditions in which they’re operating.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F768d83e49473ade5f08e00cfdda052f2_1679309854709.jpg\" alt=\"\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Q: \u003C\u002Fstrong>\u003Cstrong>How does the autonomous vehicle handle narrow streets where visibility may be limited?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>A: Just as a human driver would instinctively drive more cautiously on a narrow urban street where pedestrians might suddenly jump onto the road, so must an AV make similar assumptions and be cautious in such areas.\u003C\u002Fp>\n\u003Cp>As you can see in the video below, the AV is following the fourth rule of our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\">Responsibility-Sensitive Safety™\u003C\u002Fa> model (RSS™) – the framework on which its driving policy is based. RSS rule #4 instructs the vehicle to always be cautious in areas of limited visibility.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FpDyMzz8HMIc?clip=Ugkx_DSY31Bw2Y-spgfTV2rDS4xRN8XOalmc&clipt=EJD2GBj9xRs\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Q: H\u003C\u002Fstrong>\u003Cstrong>ow does the AV handle inclement weather conditions?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>A: Visibility on the road can be compromised by a long list of weather events, including heavy rain, snow, fog, strong crosswinds, and more. We prepare our autonomous vehicles for such conditions by equipping them with a full array of sensor types so that they’ll be able to detect and handle whatever weather they encounter. The sensor inputs allow an AV to determine, for example, whether it should reduce speed and proceed with greater caution due to weather conditions.\u003C\u002Fp>\n\u003Cp>Importantly, our AV featured in the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\">night-drive video in Jerusalem\u003C\u002Fa> incorporates a radar\u002Flidar subsystem (in addition to a camera-based subsystem). We call this approach to sensing \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\">True Redundancy™\u003C\u002Fa>, which specifically provides for incorporation of both subsystems operating independently of one another. So, if bad weather limits the cameras’ visibility, the vehicle will still be able to operate safely and effectively on radar and lidar alone (since these active sensors are not impeded in the same way by bad weather as cameras are).\u003C\u002Fp>\n\u003Cp>A compressed-air system also keeps the lenses on our AV’s cameras clean from dirt, grime, rain, snow, and ice it might pick up from the driving environment.\u003C\u002Fp>\n\u003Cp>\u003Cem>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F05e667c8b18ab869fd7d7f0a8e986c97_1681913091101.jpg\" alt=\"A Zeekr 001 with Mobileye SuperVision testing our camera-only self-driving system in the snow in Detroit.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>In addition, the REM maps mentioned earlier provide an additional rich layer of information on the driving environment, supplementing what the vehicle’s onboard sensors pick up, which is especially useful if any of the sensors are impaired by reduced visibility conditions.\u003C\u002Fp>\n\u003Cp>In the unlikely event that the AV determines for any reason that it cannot proceed safely, it’s programmed to either pull over to the side of the road and stop (if equipped with an eyes-off\u002Fhands-off or driverless system), or slow down and remain within its lane (in a camera-only, eyes-on\u002Fhands-off system).\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>These are some of the excellent questions we’ve received, and we hope the answers we’ve provided here have helped you better understand how our self-driving technologies work. For a closer look at each of the unedited autonomous drive videos captured in locations around the world, watch the videos in the playlist below.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fvideoseries?list=PLWCfS_Yhbvs5MtQIjNfN-xLU30mc1qjEc\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>","2023-04-24T07:00:00.000Z",[84,21],{"id":621,"type":141,"url":622,"title":623,"description":624,"primary_tag":12,"author_name":136,"is_hidden":96,"lang":132,"meta_description":624,"image":625,"img_alt":626,"content":627,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":628,"tags":629},208,"camera-first-approach-for-assisted-autonomous-driving","Our Camera-First Approach to Enhancing Mobility","For capability and cost, cameras can’t be beat. That’s why Mobileye embraces a camera-first approach towards sensing for both assisted and autonomous driving.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fca2e5c9e96edcd608dd05b9deb731679_1680467545684.jpg","Mobileye pioneered the use of a single camera to enable advanced driver-assistance systems.","\u003Cp>There are many things we take for granted, but when it comes to cars at least, things weren’t that way until someone made them so.\u003C\u002Fp>\n\u003Cp>Cars today are a fact of life, for example, but they didn’t exist before Gottlieb Daimler and Carl Benz effectively invented them. By now we see cars everywhere, but they weren’t mass-produced until Henry Ford came up with the assembly line. These days almost all cars come with some degree of advanced driver-assistance system, and most such systems are based on cameras... but that too wasn’t the case until Mobileye pioneered the concept. And that camera-first approach remains at the heart of everything we do.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Historical Vision\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>When Mobileye began nearly a quarter-century ago, driver-assistance technology was still in its infancy (and autonomous driving, by extension, was little more than a pipe dream). Some automakers were starting to introduce basic ADAS features, but the industry had yet to settle on what type of sensors to use for them.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3a4d7c7e97f877e6d44c955b38e2dbec_1680467160654.jpg\" alt=\"Mobileye CEO & founder Professor Amnon Shashua pioneered computer vision technology for advanced driver-assistance systems.\" width=\"1650\" height=\"789\" \u002F>\u003C\u002Fp>\n\u003Cp>One major manufacturer was working on a camera system for measuring the distance to the vehicle ahead, and invited a computer science professor named \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Famnon-shashua\u002F\">Amnon Shashua\u003C\u002Fa> to provide his input. Shashua showed that he could do with just one camera what they were trying to do with two. That successful demonstration led to his founding Mobileye and paved the way for advanced driver-assistance systems that could (and indeed would) be deployed at a scale great enough to revolutionize automotive safety.\u003C\u002Fp>\n\u003Cp>The reason why that automaker called upon Shashua was due to the expertise for which he was already becoming known in the emerging field of \u003Ca href=\"https:\u002F\u002Fwww.intel.com\u002Fcontent\u002Fwww\u002Fus\u002Fen\u002Finternet-of-things\u002Fcomputer-vision\u002Foverview.html\">computer vision\u003C\u002Fa>. This form of artificial intelligence employs highly sophisticated algorithms to interpret the inputs from simple cameras in order to understand their surroundings.\u003C\u002Fp>\n\u003Cp>To this day, that same core competence \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcomputer-vision-eccv-2022\u002F\">still drives us here at Mobileye\u003C\u002Fa>, where teams of engineers and developers are constantly \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fenhanced-computer-vision-driver-assistance\u002F\">honing our computer vision algorithms\u003C\u002Fa> to better identify a wider range of parameters in the driving environment, and developing \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\">the chips to put that technology into cars and out on the road\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>So why do we still embrace a camera-first approach above all other types of sensors? For two main reasons, as our CTO \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-cto-wins-prestigious-michael-bruno-award\u002F\">Prof. Shai Shalev-Shwartz\u003C\u002Fa> outlines in the video below.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F9yfuOlEyJyk\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Driving by Vision\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>As drivers, we make use of nearly all our senses when behind the wheel. We feel how the car interacts with the road, hear other cars coming and horns honking, and can even smell if something has gone wrong (like an engine overheating). But no sense is as essential to us as sight, and cameras are the sensors that function most like the human eye.\u003C\u002Fp>\n\u003Cp>Cameras can “see” the parameters of the road surface and the various obstacles, hazards, and other users on and around us – including other cars, trucks, bikes, and pedestrians. Cameras also provide rich semantic understanding of key details in the driving environment – such as identifying lane markings, recognizing colors on traffic lights, and even reading the text on two-dimensional traffic signs. \u003C\u002Fp>\n\u003Cp>For their part, radar and lidar deliver certain key advantages over cameras, such as detecting objects beyond line of sight and in lower-lighting or bad weather conditions. But they cannot replace the essential functions that cameras perform.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff2f6ccbbb100c4704eb8a448100e2ffd_1680467003332.jpg\" alt=\"Mobileye's surround-view camera array provides 360-degree computer-vision capabilities for advanced mobility solutions.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Made to Scale\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>There’s a huge range in the prices of different types of sensors. Lidars, for example, are expensive, but cameras are relatively affordable. Building our technology around low-cost cameras affords us the rare simultaneous opportunity to increase both the availability and the performance of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">our solutions\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>For the mass market, the low cost of camera sensors enables integration of our driver-assistance technology into more vehicles (without disproportionately affecting their purchase prices). Indeed, to date, more than 135 million vehicles have been equipped with our technologies, and that number is growing at a quickening pace.\u003C\u002Fp>\n\u003Cp>For higher-end vehicles, the low cost of camera sensors means that more of them can be cost-effectively integrated into advanced solutions. For example, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\">Mobileye SuperVision™\u003C\u002Fa> (our eyes-on\u002Fhands-off solution) incorporates 11 cameras to provide 360-degree surround coverage.\u003C\u002Fp>\n\u003Cp>Mobileye Chauffeur™ (our eyes-off\u002Fhands-off solution for consumer autonomous vehicles) and Mobileye Drive™ (our driverless solution for autonomous commercial vehicles) are similarly being developed under our camera-first approach. Only these solutions also feature a secondary, independent \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fradar-lidar-next-generation-active-sensors\u002F\">radar\u002Flidar\u003C\u002Fa> suite to back up the cameras (under our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fav-safety-demands-true-redundancy\u002F\">True Redundancy™\u003C\u002Fa> approach to sensing).\u003C\u002Fp>\n\u003Cp>Even our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\">REM™ mapping technology\u003C\u002Fa> owes its crowdsourcing capabilities to the proliferation of our camera-based solutions. And that mapping data is itself being implemented into a range of applications, from our turnkey systems for self-driving vehicles through to human-driven cars augmented by our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcloud-enhanced-driver-assist\u002F\">Cloud-Enhanced Driver-Assistance™\u003C\u002Fa> solution.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>Mobileye will, of course, continue developing additional inputs like the maps and active sensors mentioned above. And there’s no telling what novel developments might emerge in the future. But between their inherent capability and the scale afforded by their low cost, cameras have always been – and remain still – at the heart of everything we do.\u003C\u002Fp>","2023-04-16T07:00:00.000Z",[13,84,42,21],{"id":631,"type":141,"url":632,"title":633,"description":634,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":634,"image":635,"img_alt":636,"content":637,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":638,"tags":639},207,"when-will-self-driving-cars-be-available","The Multiple Lanes on the Road to the Autonomous Future","When will self-driving cars be available? Mobileye has more than one answer, from hands-off to eyes-off and even completely driverless solutions.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff9f2700e1135d9967437197a1ec011bf_1681140041144.jpg","Mobileye is developing a broad spectrum of advanced solutions to put our self-driving technologies on the road.","\u003Cp>Let’s cut to the chase here for a moment. You’ve been hearing about self-driving vehicles for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fhistory-autonomous-vehicles-renaissance-to-reality\u002F\">a long time now\u003C\u002Fa>, and you want to know where they are already. Reasonable enough, considering how much time and money have already gone into pursuing them. Yet even with some vehicles incorporating varying degrees of autonomous features, the dream of fully autonomous vehicles often seems just out of reach – tantalizingly close, but always a few years away.\u003C\u002Fp>\n\u003Cp>Well, we’re here to tell you that self-driving technology is coming, and it’s coming soon. Just when, exactly, is a matter of the degree of autonomy you’re looking for, and what form you want it to take.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Multiple Technologies, Multiple Solutions\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F83877fdae92f3ea904afe246cb12429b_1679908831728.jpg\" alt=\"Mobileye's vision for what self-driving vehicles will look like and how they will function has evolved and expanded.\" width=\"1650\" height=\"777\" \u002F>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>The trouble with self-driving vehicle technology is that it’s not monolithic, however it might seem from the outside. In order for self-driving vehicles to function safely and effectively, they’ll require a wide array of technologies working in unison – including various sensors, maps, processors, and software... all of which we’re hard at work perfecting here at Mobileye.\u003C\u002Fp>\n\u003Cp>The upside to that complexity, however, is that we can put those building blocks out on the road in a variety of configurations to incrementally deliver a \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">broad range of solutions\u003C\u002Fa>.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Increasing Capabilities of Driver Assistance\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0ab72e520b424eb08286c8ba872014a8_1679908953250.jpg\" alt=\"Mobileye SuperVision is an eyes-on\u002Fhands-off solution derived directly from our self-driving development program.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Under Mobileye’s approach, the first step in rolling out the benefits of self-driving technology is to enable drivers to take their hands off the wheel (while keeping their eyes on the road).\u003C\u002Fp>\n\u003Cp>Some automakers have already begun offering this kind of functionality with increasingly sophisticated driver-assist feature sets – carrying names like Highway Pilot and Traffic-Jam Assist – many of which are enabled by our technology.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\">Mobileye SuperVision™\u003C\u002Fa> takes those capabilities to the next level. It is derived directly from our self-driving development program and enables a vehicle to function almost like a fully autonomous vehicle: cruise on the highway, inch along through traffic, change lanes, overtake slower-moving vehicles, navigate around obstacles on the shoulder, and more – all by itself, while the driver supervises.\u003C\u002Fp>\n\u003Cp>This highly advanced eyes-on\u002Fhands-off solution is already on the road in China inside a \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002FR8qTOPpQ2-I\">growing variety of vehicles\u003C\u002Fa> from our launch partner Zeekr, whose parent company \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fgeely-holding-group-expands-mobileye-collaboration\u002F\">Geely is slated to expand Mobileye SuperVision\u003C\u002Fa> to additional markets and further models from other brands under its vast umbrella. And other automakers are due soon to follow. To date, there are already more than 90,000 vehicles equipped with Mobileye SuperVision on the road – a number we expect to reach 150,000 by the end of 2023, and to top 1.2 million by 2026.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Coming Wave of Consumer AVs\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F079309dc521e94e5b734c26d89dbbd59_1679909463586.jpg\" alt=\"Mobileye Chauffeur is our eyes-off\u002Fhands-off solution for the coming wave of consumer autonomous vehicles.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Cp>The next step will be to allow drivers to take not only their hands off the wheel, but their \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fdefining-a-new-taxonomy-for-consumer-autonomous-vehicles\u002F\">eyes off the road\u003C\u002Fa> as well.\u003C\u002Fp>\n\u003Cp>Fortunately, the bulk of the technology required for this high degree of autonomy is in fact already present in Mobileye SuperVision – including the computer-vision system, maps, driving policy, and processors. To take the next step up to Mobileye Chauffeur™ (our eyes-off\u002Fhands-off solution), we will replace the driver’s guidance with redundant processors and active sensors. This will allow consumer passenger vehicles to operate autonomously in a variety of (but not all) situations. And we’re glad to report that development and integration of these components is already well underway.\u003C\u002Fp>\n\u003Cp>Mobileye Chauffeur is slated to go into production in 2026. Based on the progress we’ve made to date and the path we’ve charted forward, automakers are already lining up to implement it in cars they’ll sell to the public. Once you get your hands on (or off) one of these vehicles, you’ll be able to sit back and enjoy the ride as the vehicle handles all the driving for you – first on highways, then on arterial and rural roads, and ultimately in the city as well.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Autonomous Mobility on Demand\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cstrong>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F979ae3214eadc09d897ae657815d8248_1679909488138.jpg\" alt=\"Mobileye Drive is our completely driverless solution for a full range of autonomous Mobility-as-a-Service applications.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Suppose you don’t need your own car, though, or don’t want to be saddled with the burdens of vehicle ownership. What if all you want is to be able to order a ride in a self-driving vehicle that will take you where you need to go?\u003C\u002Fp>\n\u003Cp>That’s what’s known as \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fdrive\u002F\">autonomous mobility-as-a-service (MaaS)\u003C\u002Fa>. We’re already seeing small fleets of robotaxis operating on limited bases in parts of the United States and China. With \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-drive-self-driving-system\u002F\">Mobileye Drive™\u003C\u002Fa>, we aim to take autonomous MaaS even further.\u003C\u002Fp>\n\u003Cp>Mobileye Drive incorporates everything found in Mobileye SuperVision and Mobileye Chauffeur. Only here, the circumstances under which it’s capable of operating autonomously are defined by geographic area, not by road type. And with a built-in teleoperation system (in case, say, the vehicle gets a flat tire or is pulled over by police), vehicles equipped with this solution won’t need a driver on board at all – and in some cases won’t even have a steering wheel. All you’ll need to do is open up an app (like \u003Ca href=\"https:\u002F\u002Fmoovit.com\u002F\">Moovit\u003C\u002Fa>) and order a ride – like you would with any taxi or ride-hailing service, but without a driver.\u003C\u002Fp>\n\u003Cp>We’ve already begun testing our robotaxis in multiple locations around the world. In the future, Mobileye Drive will be optimized for use in robotaxis, ride-pooling, public transport, and goods delivery, empowering manufacturers and transport operators to offer a variety of autonomous vehicles incorporating our reliable and road-tested self-driving technology.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FGZ9Dsm-oqi8\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>In short, there’s still a few steps left ahead of us on the road to the future of completely autonomous vehicles, and we can’t skip any of them. But we can enjoy the benefits of their ongoing development along the way as we incrementally transfer the responsibility of driving from the hands of humans to the advancing capabilities of self-driving technology.\u003C\u002Fp>","2023-03-30T07:00:00.000Z",[21],{"id":641,"type":141,"url":642,"title":643,"description":644,"primary_tag":33,"author_name":136,"is_hidden":96,"lang":132,"meta_description":644,"image":645,"img_alt":646,"content":647,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":648,"tags":649},204,"johann-jungwirth-driverless-tech-business-faz-podcast","Mobileye’s SVP of AVs on Driverless Tech & Business","Explore the latest developments in autonomous driving technology and business models with insights from Mobileye's Senior VP of AV, Johann “JJ” Jungwirth. ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F56029497307b31e319f9a42612fd2a6d_1678708468949.png","Johann “JJ” Jungwirth, Senior Vice President of Autonomous Vehicles at Mobileye.","\u003Cp>Mobileye's Senior Vice President of AV Johann “JJ” Jungwirth recently appeared on the Frankfurter Allgemeine Zeitung (FAZ) podcast to discuss the state of self-driving development and what’s still needed to put autonomous vehicles on the road.\u003C\u002Fp>\n\u003Cp>In the interview, JJ details the level of AI required to support the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\">camera, radar, and lidar sensors\u003C\u002Fa> that are needed to model the driving environment, classify detected objects, and aid in \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\">decision-making for autonomous driving\u003C\u002Fa>. But he also points out that autonomous driving has already begun to hit the streets with ride-hailing services in several cities.\u003C\u002Fp>\n\u003Cp>As part of the episode, JJ also discusses the business models for autonomous driving and driverless services – such as \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\">robotaxis\u003C\u002Fa>, which will be the first to adopt the technology, before private vehicles. JJ believes that OEMs will most likely adapt the systems that fit the driving styles of their customers to deliver a unique autonomous driving experience. He also discusses the issue of liability, and notes that insurers have signaled their readiness to provide coverage for vehicles and service providers.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.faz.net\u002Fpodcasts\u002Ff-a-z-kuenstliche-intelligenz-podcast\u002Fautonomes-fahren-und-robo-taxis-von-2025-an-auf-deutschen-strassen-18730179.html\" target=\"_blank\" rel=\"noopener\">Click here\u003C\u002Fa> to listen to the full interview (in German).\u003C\u002Fp>","2023-03-15T07:00:00.000Z",[21,34],{"id":651,"type":141,"url":652,"title":653,"description":654,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":654,"image":655,"img_alt":656,"content":657,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":658,"tags":659},202,"autonomous-vehicle-test-drivers-pioneers-mobility","Autonomous Vehicle Test Drivers: Pioneers of the Future of Mobility","A glimpse into the life of our test drivers, who are ensuring that the self-driving cars of the future are safe, reliable, and comfortable. ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F6a89554e4d540da12aa463c684695806_1678182142326.jpg","Mobileye’s autonomous-vehicle test drivers are professional driving instructors who test our technologies in real-world traffic.","\u003Cp>\"I love being in the AV workshop. I feel like I am an astronaut working at NASA.”\u003Cbr \u002F>– Tomer Horoszowski, Mobileye AV Test Driver\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>The average American or European spends at least \u003Ca href=\"https:\u002F\u002Fhbr.org\u002F2021\u002F05\u002Fthat-dreaded-commute-is-actually-good-for-your-health\">300 hours a year\u003C\u002Fa> in a car. But as progress in autonomous vehicle technology advances, we’re moving into a new era of mobility, in which that time behind a steering wheel will be completely transformed.\u003C\u002Fp>\n\u003Cp>Without the burden of driving a car, drivers will have new options for how to spend their commuting time. They might attend a virtual meeting with colleagues halfway across the world, play a game of chess, eat their lunch in a mobile restaurant, or take a much-needed nap. The possibilities are endless.\u003C\u002Fp>\n\u003Cp>As more and more people come to enjoy the benefits of autonomous technology, few will know about the pioneers who had a special role in ensuring that these vehicles were safe, reliable, and ready for widespread consumer adoption. \u003C\u002Fp>\n\u003Cp>At Mobileye, those pioneers are called our AV Test Driver Team.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Pioneers of the Future \u003C\u002Fstrong>\u003Cstrong>of Mobility\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Mobileye’s autonomous-vehicle (AV) test drivers are an elite group of professional drivers who are playing an essential role in making Mobileye’s “\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fdefining-a-new-taxonomy-for-consumer-autonomous-vehicles\u002F\">eyes-off\u002Fhand-off\u003C\u002Fa>” vision a reality.\u003C\u002Fp>\n\u003Cp>“We’re all race-car driving instructors,” Horoszowski points out. “It’s something that makes us the best AV test drivers.”\u003C\u002Fp>\n\u003Cp>Like the pilots who graduated from the U.S. Air Force Academy in the 1950s to become the first American astronauts at the dawn of the Space Age, the race car driving instructors who make up Mobileye’s AV testing team have found that their driving expertise provides them with the unique set of skills required for honing one of the greatest technological advancements of our time—self-driving cars.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Safety \u003C\u002Fstrong>\u003Cstrong>First\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Gilad Galili, our head test driver, explains that as a \u003Ca href=\"https:\u002F\u002Fwww.cnbc.com\u002F2017\u002F11\u002F24\u002Fadvanced-driving-lessons-why-you-should-take-them.html\">driving instructor\u003C\u002Fa>, your first priority is safety—and that the same principle applies to testing autonomous vehicles.\u003C\u002Fp>\n\u003Cp>“Safety is number one and we don’t take chances,” says Galili. “A good test driver is able to perceive all drivers around the vehicle and understand their intentions,” he adds. “He should be able to ‘read the street’ and always be several steps ahead of all the other drivers in the environment.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3763e4946b13323b7b41f1fec08bb5d7_1677677131497.jpg\" alt=\"Mobileye test drivers in the autonomous-vehicle workshop at our headquarters in Jerusalem, Israel.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Cp>Racing drivers possess excellent hand-eye coordination, car control, and situational awareness, allowing them to respond to changes in a split second. And race car driving also requires them to acquire expert skills in navigating challenging racetracks and making critical decisions under pressure. \u003C\u002Fp>\n\u003Cp>The AV test drivers of Mobileye emphasize that the art of car racing is what has taught them to drive at a level of safety that is much higher than most drivers.  \u003C\u002Fp>\n\u003Cp>“As a race-car driving instructor,” says Horoszowski, “you learn in-depth about how the elements of driving come together—for example, you must know precisely how to use the gas pedal and the brake to control the handling of the car. Racing also teaches you to plan. You are always planning your race and thinking about possible moves of other cars. The distances are very close—most of the race, you might be less than a meter from another car. So, you have to be very aware of other cars and know how to prevent an accident.”  \u003C\u002Fp>\n\u003Cp>\u003Cspan class=\"ui-provider xf b c d e f g h i j k l m n o p q r s t u v w x y z ab ac ae af ag ah ai aj ak\" dir=\"ltr\">\"It’s important to understand that we have to have very high-level driving skills,” adds AV test driver David Polak. “And not only advanced technical driving skills, but we actually have to understand the physics of driving as well.”\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>A More Comfort\u003C\u002Fstrong>\u003Cstrong>able Ride\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Besides their main focus on safety, Mobileye’s AV test drivers also ensure that AVs using Mobileye technology feel comfortable and natural. For example, passengers should feel no difference between how an AV drives and how a human-driven vehicle drives.   \u003C\u002Fp>\n\u003Cp>“Because we train them on the streets of \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=pDyMzz8HMIc\">Jerusalem\u003C\u002Fa>, which are challenging due to the mix of different types of drivers, our cars drive very naturally and are able to adapt easily to other cities around the world,” says Galili. In fact, Mobileye AV testing has taken place—successfully—in some of the most challenging urban driving environments in the world, like \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=2H0UIkur1K0&t=74s\">Tokyo\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=Q69tBNCVJa0&t=16s\">Paris\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=50NPqEla0CQ&t=1415s\">New York\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fff9893bac05bf161ea530ee4caa5e11f_1677749158035.jpg\" alt=\"A Mobileye self-driving vehicle operates autonomously while testing on the Champs-Élysées in Paris, France.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Cp>This aspect of driving is so important that Mobileye has also created another dedicated team that focuses exclusively on refining the comfort and natural feeling of the self-driving driving experience.  \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>To the Limit\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Veteran race-car drivers have years of experience handling a vehicle under pressure and know how to push their vehicles’ limits to achieve their goal of winning races.\u003C\u002Fp>\n\u003Cp>When the goal is to make autonomous driving far safer than human driving, Mobileye AV drivers face a different challenge: to understand and test the limits of an autonomous vehicle in a public environment while protecting pedestrians, passengers, other drivers, and themselves.\u003C\u002Fp>\n\u003Cp>“They have a really intense job,” says Kevin Rosenblum, Mobileye’s vice-president of AV sensing and one of the developers who works closely with the AV test team. “They have to have incredible focus during the whole ride. I admire them.”  \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Valuable Feedback\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>After every drive, the AV test drivers upload data, their notes, and video footage from the drive to the issue-tracking system. Years of advanced driving in challenging situations as professional racing drivers have helped the AV test drivers to become sensitive to all aspects of driving a vehicle, a skill which helps them provide valuable feedback to the development team.\u003C\u002Fp>\n\u003Cp>“I feel I am very sensitive to how the car drives—you could say I am ‘one’ with it,” says Gilad Heskia, another racing instructor who joined Mobileye as an AV test driver. This valuable feedback enables Mobileye’s development team to consistently improve the technology, making it essential to getting Mobileye’s technology ready for market. \u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc16abc73ab89975ee93af3f8407d4d88_1677677205203.png\" alt=\"Inside one of Mobileye’s developmental autonomous vehicles as it operates hands-free in a real-world driving situation.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Connecting to the Big Picture\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>“Being an AV test driver is a dream come true,” adds Polak. “I’ve always been in love with cars, since I was a kid. I’ve always loved reading about concept cars. And now, I am actually driving the \u003Ca href=\"https:\u002F\u002Fwww.bbc.com\u002Fnews\u002Fbusiness-45900484\">concept cars\u003C\u002Fa> that will one day become the standard cars of the future. It’s amazing.”  \u003C\u002Fp>\n\u003Cp>“I think that having AVs on the road is the most effective way to reduce accidents,” says Heskia. That’s because self-driving cars, unlike humans, never get drowsy, drunk, or distracted. In fact, Mobileye’s aim is for its \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\">redundant sensor subsystems\u003C\u002Fa> to ensure a level of safety that is one full order of magnitude higher than human drivers.\u003C\u002Fp>\n\u003Cp>“Having them on the road will also help \u003Ca href=\"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11116-021-10241-0\">traffic flow\u003C\u002Fa> and minimize traffic jams” adds Heskia. “With \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fdrive\u002F\">MaaS\u003C\u002Fa> (Mobility-as-a-Service), if you need a car, you order one. Commutes will become much easier—no one likes to be stuck in traffic.”   \u003C\u002Fp>\n\u003Cp>But the ease and safety of the daily commute is not the only factor driving the AV test drivers.\u003C\u002Fp>\n\u003Cp>“AVs will save everyone a lot of energy and reduce emissions—they will have a big positive impact on the environment,” comments Polak.  \u003C\u002Fp>\n\u003Cp>With improved traffic flow and fewer cars on the road (since each car will carry more occupants than currently), AVs should reduce not only traffic congestion but also air pollution. And since self-driving cars will almost universally be electric and use smart technology to optimize their energy consumption, they will help to even further reduce greenhouse gas emissions.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>At Mobileye, our vision of a future with smarter automobiles has been evolving since 1999. And with every day that passes, we’re moving closer to that vision.\u003C\u002Fp>\n\u003Cp>Our trailblazing AV test drivers play an instrumental role in realizing that vision, ensuring that when our autonomous driving technology is rolled out, it’s safe and reliable for everyone.\u003C\u002Fp>","2023-03-07T08:00:00.000Z",[21],{"id":661,"type":100,"url":662,"title":663,"description":664,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":664,"image":665,"img_alt":666,"content":667,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":668,"tags":669},203,"mobileye-named-av-leader-by-two-industry-research-groups","Research Groups Name Mobileye AV Leader","Guidehouse Insights & ABI Research both placed Mobileye in number one position across categories in recent competitive assessments of AV technology suppliers.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb45a2e3d4810325ca074f6c0751cec09_1677702040136.png","A NIO ES8 equipped with Mobileye’s self-driving hardware and software. ","\u003Cp>\u003Cstrong>\u003Cspan data-contrast=\"none\">JERUSALEM, March 2, 2023\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan data-contrast=\"none\"> — Mobileye has been recognized as the leader in the development of autonomous vehicle technology by two leading research groups, Guidehouse Insights and ABI Research. In assessing several technology companies pursuing the AV market, both the \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fguidehouseinsights.com\u002Freports\u002Fguidehouse-insights-leaderboard-automated-driving-systems\">Guidehouse Insights Leaderboard: Automated Driving Systems\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> and the inaugural \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.abiresearch.com\u002Fmarket-research\u002Fproduct\u002F7780562-autonomous-vehicle-platforms\u002F\">ABI Research Autonomous Vehicle Platforms\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> reports concluded that Mobileye deserved the top score.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Mobileye achieved the top spot in both rankings within frameworks that assessed multiple companies both quantitatively and qualitatively across a broad range of criteria covering technology, innovation, strategy, implementation, customer bases and more. In the Guidehouse Leaderboard, Mobileye moved forward six positions since the last report published in 2021, an accomplishment that reflects the significant strides Mobileye has made in recent years demonstrating and delivering on its autonomous vision. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F82455a5ee279086d58a1cc050edd01e8_1677773046696.png\" alt=\"Graphic of ABI Autonomous Vehicle Platform rankings chart\" width=\"600\" height=\"600\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Each report highlighted four companies leading the AV space, and Mobileye was the only company to appear in both lists.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">“We appreciate the independent recognition of our tech leadership from these two leading analytical firms,” said Mobileye President and CEO Prof. Amnon Shashua. “It’s a testament to the hard work of thousands of Mobileye employees who are developing the future of transportation every day. It’s also a reminder that this industry continues to develop quickly, and we should never take our success for granted.”\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">\u003Cimg style=\"display: block; margin-left: auto; margin-right: auto;\" src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F275a9574c58e1af9a90b4bda35dd5590_1677773156031.png\" alt=\"Graphic of Guidehouse Insights Autonomous Platforms ranking\" width=\"600\" height=\"600\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">With AV research and development having matured in recent years, both research groups emphasized the importance of companies having viable business models for future AV deployment. Each report recognized that Mobileye’s established leading position and long track-record of execution in the vision-based ADAS market supports a strong path to realizing automated driving of increasing capabilities in both the consumer and mobility-as-a-service markets. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Another key advantage in both reports was Mobileye’s approach to scalable, deployable AV tech through its Mobileye SuperVision\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"none\"> eyes-on, hands-off technology which is already in production, along with the Mobileye Drive\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"none\"> robotaxi solution and Mobileye Chauffeur\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">™\u003C\u002Fspan>\u003Cspan data-contrast=\"none\"> consumer AV offering; all built on nearly two decades of success in camera-based safety and driver-assist systems installed in more than 135 million vehicles globally. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Media Contact: Justin Hyde\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003Cbr \u002F>\u003C\u002Fspan>\u003Ca href=\"mailto:Justin.Hyde@Mobileye.com\">\u003Cspan data-contrast=\"none\">Justin.Hyde@Mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003Cbr \u002F>\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">+1 202-656-6749\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Analyst Relations: Luca Gervasoni\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003Cbr \u002F>\u003C\u002Fspan>\u003Ca href=\"mailto:Luca.Gervasoni@mobileye.com\">\u003Cspan data-contrast=\"none\">Luca.Gervasoni@mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\"> \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003Cbr \u002F>\u003C\u002Fspan>\u003Cspan data-contrast=\"none\">+ 1 954-600-3373\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">___________________________________\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 135 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002F\">\u003Cspan data-contrast=\"none\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fspan>\u003C\u002Fa>\u003Cspan data-contrast=\"none\">. \u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"none\">“Mobileye,” the Mobileye logo and Mobileye product names are registered trademarks of Mobileye in various jurisdictions. All other marks are the property of their respective owners.\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>","2023-03-02T08:00:00.000Z",[64,21,34,42,99,70],{"id":671,"type":141,"url":672,"title":673,"description":674,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":674,"image":675,"img_alt":676,"content":677,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":678,"tags":679},187,"history-autonomous-vehicles-renaissance-to-reality","A Brief History of Autonomous Vehicles – from Renaissance to Reality","Mankind has been dreaming of self-driving vehicles for decades – even centuries. Mobileye is proud to be driving those dreams across the finish line.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Ff451465cac4b08769db2c21cefb6d700_1676211731836.png","Automobiles, and autonomous vehicles especially, have evolved significantly from da Vinci's initial design to today's robotaxis.","\u003Cp>Someday, when historians look back at this point in history, how will they characterize it? If we at Mobileye have anything to say on the matter, they’ll reflect on this as the turning point just before the dawn of self-driving vehicles. A time before anyone could order a ride in a robotaxi or purchase a fully autonomous vehicle of their own. A time when automobiles were still driven by humans, parked by humans, goods delivered by humans, and commutes endured by humans for long hours spent behind the wheel... but a time when great strides were being made to translate the long-held dream of autonomous mobility into reality.\u003C\u002Fp>\n\u003Cp>That places us today at the precipice of a new era in automotive history. But just how long, exactly, have people been dreaming of autonomous vehicles? And what are the events that have brought us to where we are today, at this potential turning point in the evolution of human mobility?\u003C\u002Fp>\n\u003Cp>Keep reading for a brief history of the evolution of autonomous vehicles, and the part that Mobileye has come to play in ushering in their arrival.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>An Early Dreamer\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd658353fa03e68f11f9f535d10c72486_1677404199034.jpg\" alt=\"This rendering depicts a self-driving, self-propelled cart designed by Leonardo da Vinci in the 16th century.\" width=\"1604\" height=\"1070\" \u002F>\u003C\u002Fp>\n\u003Cp>The concept of an autonomous vehicle (AV) dates back to long before the advent of the automobile itself – to the 16\u003Csup>th\u003C\u002Fsup> century, if you can believe it. That’s when \u003Ca href=\"https:\u002F\u002Fwww.museogalileo.it\u002Fen\u002Fmuseum\u002Fexplore\u002Ftemporary-exhibitions\u002F275-leonardo-s-automobile-en.html\" target=\"_blank\" rel=\"noopener noreferrer\">Leonardo da Vinci designed a small, three-wheeled, self-propelled cart\u003C\u002Fa> regarded as not only the first self-driving vehicle, but the first robot of any kind. More clockwork than motor vehicle, it incorporated a series of springs for propulsion, a pre-programmable steering system, and a parking brake released remotely by rope.\u003C\u002Fp>\n\u003Cp style=\"text-align: left;\">In 2016, historians in Florence built a prototype from da Vinci’s original sketches. Da Vinci himself surely would not have been surprised \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002FNLvoOkeCGrw\" target=\"_blank\" rel=\"noopener noreferrer\">to see it actually work\u003C\u002Fa> as it did. But we can only imagine what he would have thought if he’d seen \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-test-demo-road-trip\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">our AV recently driving itself through Milan\u003C\u002Fa>, where he spent part of his life and career.\u003C\u002Fp>\n\u003Ch3 style=\"text-align: left;\">\u003Cstrong>The Magnetism of the Future\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp style=\"text-align: left;\">It would take centuries for technology to catch up to where da Vinci left off. But when it did, the dream of autonomous vehicles rode along with it.\u003C\u002Fp>\n\u003Cp style=\"text-align: left;\">In 1925, electrical engineer \u003Ca href=\"https:\u002F\u002Fjalopnik.com\u002Fthe-man-who-tested-the-first-driverless-car-in-1925-had-1792312207\" target=\"_blank\" rel=\"noopener noreferrer\">Francis P. Houdina\u003C\u002Fa> radio-controlled a full-size automobile through the streets of New York. The car crashed and the project failed. But as automobiles proliferated in the decades that followed, so too did efforts to automate their operation.\u003C\u002Fp>\n\u003Cp style=\"text-align: left;\">At the 1939 New York World’s Fair, industrial designer Norman Bel Geddes showcased a \u003Ca href=\"https:\u002F\u002Fblog.mcny.org\u002F2013\u002F11\u002F26\u002Fi-have-seen-the-future-norman-bel-geddes-and-the-general-motors-futurama\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">dazzling array of visionary transportation concepts\u003C\u002Fa>. His “Futurama” exhibit featured rooftop helipads and interstate highways – as well as semi-autonomous vehicles to travel along them, using a combination of radio control and magnets embedded in the pavement.\u003C\u002Fp>\n\u003Ch5 style=\"text-align: left;\">\u003Ccode>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd4aec9c0fe628cf71bb3adb97f8f7251_1676214431534.jpg\" alt=\"Norman Bel Geddes' Futurama exhibit at the 1939 New York World's Fair.\" width=\"1604\" height=\"1070\" \u002F>\u003Cbr \u002F>\u003C\u002Fcode>\u003Cem>Norman Bel Geddes’ \"Magic Motorways\"\u003C\u002Fem>\u003C\u002Fh5>\n\u003Cp style=\"text-align: left;\">General Motors sponsored the exhibit and continued developing the idea over the following couple of decades with its \u003Ca href=\"https:\u002F\u002Fwww.gm.com\u002Fstories\u002Ffirebird\" target=\"_blank\" rel=\"noopener noreferrer\">Firebird series of concept cars\u003C\u002Fa>. Others experimented with magnetic guidance as well, but upgrading infrastructure proved too costly and restrictive to present a viable and scalable solution for autonomous mobility.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>An Academic Pursuit\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Academia led the next stage in AV development. In 1961, researchers at \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002F8Mxk2L3lu9Q\" target=\"_blank\" rel=\"noopener noreferrer\">Stanford University developed a small cart\u003C\u002Fa> to navigate on the surface of the moon using a basic form of computer vision. In 1977, mechanical engineers at the University of Tsukuba in Japan took the idea further with a passenger vehicle capable of driving autonomously at up to 20 miles per hour. Further progress was made in the mid-90s at the University of Parma in Italy – also not far from where da Vinci lived (and dreamed) centuries prior.\u003C\u002Fp>\n\u003Cp>One of the most significant efforts came under the aegis of the \u003Ca href=\"https:\u002F\u002Fwww.autonomousvehicleinternational.com\u002Ffeatures\u002Fthe-prometheus-project.html\" target=\"_blank\" rel=\"noopener\">Eureka PROMETHEUS Project\u003C\u002Fa>, which brought together a consortium of universities, automakers, and tech companies in the late 1980s and early ‘90s. Funded by (mostly European) governments to the tune of €749 million (roughly €1.3 billion in today’s money), the project culminated in 1994 with thousand-kilometer (~620-mile) drive on Parisian highways that included operating hands-free, in convoy, automatically changing lanes while tracking and passing other vehicles.\u003C\u002Fp>\n\u003Cp>Perhaps the greatest strides, however, were made once the Pentagon brought its enormous resources to bear.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Best Defense\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Through its Defense Advanced Research Projects Agency (DARPA), the U.S. Department of Defense began supporting autonomous-vehicle research in the 1980s. Its first major undertaking in the self-driving sphere saw it fund the Autonomous Land Vehicle (ALV) project, which employed an early form of lidar to navigate off-road.\u003C\u002Fp>\n\u003Ch5>\u003Cem>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9c88c92a3a8850ad15ad9aa385e12928_1676214226278.jpg\" alt=\"Stanford University's winning Volkswagen Touareg prototype at the DARPA Grand Challenge.\" width=\"1605\" height=\"1070\" \u002F>\u003Cbr \u002F>\u003C\u002Fem>\u003Cem>Photo courtesy of DARPA\u003C\u002Fem>\u003C\u002Fh5>\n\u003Cp>DARPA also supported \u003Ca href=\"https:\u002F\u002Fwww.cs.cmu.edu\u002Fafs\u002Fcs\u002Fproject\u002Falv\u002Fwww\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Carnegie Mellon University’s Navigation Laboratory\u003C\u002Fa> (or “Navlab”), which produced a series of experimental AVs. In 1986, Navlab 1 – a full-size van packed with computers, sensors, and cooling systems – drove itself (slowly) around suburban neighborhoods. In 1995, the Navlab 5 minivan drove from Pittsburgh all the way to San Diego under the banner of \"No Hands Across America.\" The onboard researchers handled the throtle and brakes while the vehicle steered itself for over 98% of the 2,850-mile (~4,600-kilometer) journey.\u003C\u002Fp>\n\u003Cp>The floodgates really opened, however, with the \u003Ca href=\"https:\u002F\u002Fwww.darpa.mil\u002Fabout-us\u002Ftimeline\u002F-grand-challenge-for-autonomous-vehicles\" target=\"_blank\" rel=\"noopener noreferrer\">DARPA Grand Challenge\u003C\u002Fa> – a series of competitions that saw Stanford and Carnegie Mellon (among others) sparring for AV leadership. None of the contestants finished the first desert competition in 2004, but five did the following year – led by Stanford’s Volkswagen Touareg (using Intel processors). Two years later, Carnegie Mellon won the urban competition with a specially equipped Humvee.\u003C\u002Fp>\n\u003Cp>DARPA’s competitions proved that self-driving technology could work. And that milestone in turn spurred a slew of startups, tech firms, and automakers to start their own AV development programs over the course of the following decade-plus – some of them employing former Grand Challenge contestants.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Building Blocks\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>While others were grappling with solving the AV question as a whole, Mobileye was already establishing itself as a leader in what would become the building blocks of self-driving technology.\u003C\u002Fp>\n\u003Ch5>\u003Ciframe src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FL1Bmc61l99A\" width=\"560\" height=\"314\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003Cbr \u002F>\u003Cem>Archival footage: Mobileye’s first developmental AV began testing in 2013.\u003C\u002Fem>\u003C\u002Fh5>\n\u003Cp>From our founding in 1999, Mobileye focused on developing and supplying computer-vision technology for advanced driver-assistance systems, and our experience and track record grew steadily from there. By 2013, our technology was already incorporated into more than a million vehicles, and the driver-assist features we were enabling kept getting more advanced. But as far as we’d come, we were convinced we could go even further.\u003C\u002Fp>\n\u003Cp>A self-driving system, we concluded, wasn’t really one system at all. It was a collection of individual functions working in unison – driver-assist functions like those our technology was already supporting. So we fitted an array of those systems to an Audi A7 and connected them to create our first self-driving car. It worked so well that our customers, who had already come to rely on us for increasingly sophisticated driver-assist technologies, begun asking us to furnish them with the hands-free driving features that our prototype demonstrated.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>From Vision to Reality\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>As demand grew, so too did our AV development program. Our test fleet expanded and evolved from the original internal-combustion Audis to Ford Fusion hybrid sedans and NIO ES8 electric crossovers – each with an ever-increasing range of autonomous capabilities. And we dispatched those vehicles for testing in a variety of challenging \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-testing-miami-stuttgart\u002F\" target=\"_blank\" rel=\"noopener\">locations around the world\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>\u003Ciframe title=\"YouTube video player\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F5obbgj5gIug\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>Along the way, we upgraded from a single forward-facing camera to surround vision. We added \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fradar-lidar-next-generation-active-sensors\u002F\" target=\"_blank\" rel=\"noopener\">radar and lidar sensors\u003C\u002Fa>, specialized \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frem-mapping-avs\u002F\" target=\"_blank\" rel=\"noopener\">AV maps\u003C\u002Fa>, and the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fresponsibility-sensitive-safety-unwritten-rules-of-the-road\u002F\" target=\"_blank\" rel=\"noopener\">driving policy\u003C\u002Fa> to share the road safely and effectively with other drivers. And we've applied the results of our ongoing AV development program to a \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">broad range of solutions\u003C\u002Fa> – from \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fcloud-enhanced-driver-assist\u002F\" target=\"_blank\" rel=\"noopener\">enhanced\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-supervision-bridge-to-consumer-autonomous-vehicles\u002F\" target=\"_blank\" rel=\"noopener\">premium driver-assist\u003C\u002Fa> to complete \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-drive-self-driving-system\u002F\" target=\"_blank\" rel=\"noopener\">self-driving systems\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>As far as we’ve come, however, we know there’s still so much more to come. The dream of truly autonomous vehicles, held for so long by so many, is on the verge of becoming reality. And we’re proud of the role we’re playing in driving it across the line – and in teaching it to drive itself even further.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Ch6>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fall_timeline_1676366973.png\" target=\"_blank\" rel=\"noopener\">\u003Cimg style=\"width: 100%;\" src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fall_timeline_1676366973.png\" alt=\"The timeline of autonomous-vehicle development, from Da Vinci to today\" width=\"423\" height=\"1070\" \u002F>\u003C\u002Fa>\u003C\u002Fh6>","2023-02-27T08:00:00.000Z",[21],{"id":681,"type":682,"url":683,"title":684,"description":685,"primary_tag":5,"author_name":136,"is_hidden":96,"lang":132,"meta_description":685,"image":686,"img_alt":687,"content":688,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":689,"tags":690},201,"interview","autonocast-prof-amnon-shashua-taxonomy","Prof. Amnon Shashua: Changing How We Talk About Automated Driving","On the latest episode of the Autonocast, Mobileye’s founder and CEO discussed our new taxonomy for highly automated and fully autonomous vehicles.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F212a38ecdfd1db6e1045804f68b7b143_1676988542835.jpg","Professor Amnon Shashua, founder and CEO, Mobileye","\u003Cp>In episode #273 of the popular podcast \u003Cem>Autonocast\u003C\u002Fem>, Mobileye founder and CEO \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Famnon-shashua\u002F\">Professor Amnon Shashua\u003C\u002Fa> explains how Mobileye’s \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fopinion\u002Fdefining-a-new-taxonomy-for-consumer-autonomous-vehicles\u002F\">new taxonomy for autonomous driving\u003C\u002Fa> creates a clearer picture as the automotive industry moves forward with the productization of autonomous and highly automated systems.\u003C\u002Fp>\n\u003Cp>In this episode he and co-hosts Alex Roy, Ed Niedermeyer, and Kirsten Korosec covered a broad range of subjects related to mobility, from validation and the role of the driver to the future of driver assistance.\u003C\u002Fp>\n\u003Cp>Listen to the full episode at \u003Ca href=\"http:\u002F\u002Fwww.autonocast.com\u002Fblog\u002F2023\u002F2\u002F16\u002F273-mobileye-ceo-amnon-shashua-on-changing-how-we-talk-about-automated-driving\">Autonocast.com\u003C\u002Fa>, on \u003Ca href=\"https:\u002F\u002Fopen.spotify.com\u002Fepisode\u002F2nbqhVVaQt60rfk8KL8Qva?si=cKI5JTnrQZyB3xe9_d3Lvg\">Spotify\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fpodcasts.apple.com\u002Fus\u002Fpodcast\u002F273-mobileye-ceo-amnon-shashua-on-changing-how-we-talk\u002Fid1168333433?i=1000600049822\">Apple Podcasts\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fpodcasts.google.com\u002Ffeed\u002FaHR0cDovL3d3dy5hdXRvbm9jYXN0LmNvbS9ibG9nP2Zvcm1hdD1yc3M\u002Fepisode\u002FNTgwOTEzZTZkNDgyZTlkMmRhMjk2NzAxOjU4MDkyN2NlZTU4YzYyZDQ4MDFkNWVlNjo2M2VlODY2ODQxZjcwNDRjNjdjYWQxZTg?sa=X&ved=0CAYQuIEEahcKEwiY8b-F3Kb9AhUAAAAAHQAAAAAQAQ\">Google Podcasts\u003C\u002Fa>, or your other favorite podcast platform.\u003C\u002Fp>","2023-02-21T08:00:00.000Z",[21,114],{"id":692,"type":57,"url":693,"title":694,"description":695,"primary_tag":5,"author_name":336,"is_hidden":96,"lang":132,"meta_description":695,"image":696,"img_alt":697,"content":698,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":699,"tags":700},199,"defining-a-new-taxonomy-for-consumer-autonomous-vehicles","Defining a New Taxonomy for Consumer Autonomous Vehicles","Mobileye’s CEO and CTO detail the new taxonomy revealed at CES 2023 for deploying eyes-off\u002Fhands-off self-driving consumer vehicles.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F848b0bf9c27dbd2df10eaa07a2a2c790_1675702827035.png","Mobileye's new taxonomy for autonomous vehicles is based on defining the interaction between man and machine.","\u003Cp>Tech and auto companies had a very turbulent 2022 in almost every aspect. In spite of great turmoil, the automobile industry has shifted gears in its pursuit to adopt and deploy consumer-level autonomy in the near future. A number of the industry conventions around autonomous driving have again become unclear and ambiguous as a result of this development. The confusion threatens to obscure the real benefits of autonomy in terms of safety, convenience, and efficiency.  \u003C\u002Fp>\n\u003Cp>We see a growing need for a new way of talking and thinking about consumer AVs (CAV) that recognizes how they will work in the real world, and ensures the usefulness, safety, and scalability of consumer-level AVs. To achieve that, Mobileye has laid down a new taxonomy alongside a set of basic requirements for CAV, which was presented in our yearly address at \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fces-2023-recap\u002F\">the last CES\u003C\u002Fa>.\u003C\u002Fp>\n\u003Ch3>The Need for Clarity\u003C\u002Fh3>\n\u003Cp>Autonomous driving is viewed mainly through the prism of SAE Levels of autonomy, also known as J3016, which is widely accepted as the industry standard. When introduced in 2014, the SAE J3016 provided a very good reference for AV development and regulation while everybody was still wrapping their minds around the question of “what is autonomous driving, exactly?”. However, as we move forward with the productization of autonomous and highly automated systems, it is evident that the current Level 1-5 taxonomy cannot form a basis for a product-oriented description that is clear for both the engineer and the end customer.\u003C\u002Fp>\n\u003Cp>When looking at the current industry discourse, we see two issues that need to be addressed. The first issue is vague and unclear definitions from an end-user perspective. Second and more important is the unnecessary distinction between Level 3 and Level 4. According to J3016, Level 3 and Level 4 differ in the Minimum Risk Maneuver (MRM) requirements and the vigilance level of the human driver. This may lead to “\u003Cem>failures by design\u003C\u002Fem>” of the autonomous system, as demonstrated in an \u003Ca href=\"https:\u002F\u002Famnon-shashua.medium.com\u002Fon-black-swans-failures-by-design-and-safety-of-automated-driving-systems-1401076e9027\">opinion paper\u003C\u002Fa> we published in 2021.\u003C\u002Fp>\n\u003Ch3>Simpler Language\u003C\u002Fh3>\n\u003Cp>To deal with the deficiencies depicted above, we propose a simplified language that defines the levels of autonomy based on four axes: (i) Eyes-on\u002FEyes-off, (ii) Hands-on\u002FHands-off, (iii) Driver versus No-driver, and (iv) MRM requirement. As seen in the chart below, this creates four product categories covering the entire spectrum of automated driving.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F84fb9e3a75b5cc9da909240510812dc9_1675683237023.png\" target=\"_blank\" rel=\"noopener\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F84fb9e3a75b5cc9da909240510812dc9_1675683237023.png\" alt=\"Mobileye's new taxonomy for driving automation, based on the respective roles of man and machine.\" width=\"1650\" height=\"928\" \u002F>\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>1) Eyes-on\u002FHands-on\u003C\u002Fstrong>: this category covers all the basic driver-assist functions, such as Autonomous Emergency Braking (AEB) and Lane Keep Assist (LKA). The driver is still responsible for the entire driving task while the system monitors the human driver (Level 1-2 according to SAE).\u003C\u002Fp>\n\u003Cp>\u003Cstrong>2) Eyes-on\u002FHands-off\u003C\u002Fstrong>: this is a driver-assistance function where the driver’s hands can be off the steering wheel while the system takes control of the driving and the driver supervises the system (hence, Eyes-on) within a specified Operational Design Domain (ODD). With a proper driving monitoring system (DMS), one can create a very useful human\u002Fmachine synergetic interaction (analogous to pilots supervising the auto-pilot system in an aircraft) and increase the overall safety of driving. This is usually referred to as Level 2+, a term that was first coined by Mobileye and not formally defined by SAE. Due to the absence of the Eyes-on\u002FHands-off category from the SAE taxonomy, it is usually wrongly classified as Level 3-4. It is important to emphasize that the role of the “supervisor” changes from (1) to (2): in an Eyes-on\u002FHands-on system it is the \u003Cem>system\u003C\u002Fem> that is supervising the driver and intervening (rarely) to avoid an accident (like applying the brakes to avoid collision). It is important that \u003Cem>interventions\u003C\u002Fem> by the system happen rarely and in emergency situations rather than a continuous interference with the human driver. In an Eyes-on\u002FHands-off system it is the \u003Cem>human driver\u003C\u002Fem> who is supervising the system. To be effective, the interventions should happen rarely, and in order to keep the human driver vigilant, a proper DMS should be in place. An Eyes-on\u002FHands-off setting increases safety since the failure modes of the human and the system are very different: human failures are mostly concentrated on lack of attention and distraction that can happen in good weather and mundane road conditions whereas system failures mostly occur in challenging environments (weather, road types, and traffic maneuvers).\u003C\u002Fp>\n\u003Cp>\u003Cstrong>3) Eyes-off\u002FHands-off\u003C\u002Fstrong>: the system controls the driving function within a specified ODD (say, highways with on\u002Foff ramp transitions) without the human driver needing to supervise the driving (hence, Eyes-off). Once the ODD comes to an end, and if the driver does not take back control, the system is able to conduct a full MRM and stop safely on the shoulder of the road. This category can be classified as either Level 3 or Level 4 according to SAE J3016. It is worth noting that J3016 exempts the Level 3 system from performing full MRM by allowing it to stop in-lane, but we argue that a \u003Ca href=\"https:\u002F\u002Ftheintercept.com\u002F2023\u002F01\u002F10\u002Ftesla-crash-footage-autopilot\u002F\">stop-in-lane emergency maneuver is not safe\u003C\u002Fa>. In addition, the Eyes-off\u002FHands-off system still requires a qualified driver sitting in the driver’s seat so he\u002Fshe will be able to take control in non-safety-related situations happening at zero velocity in order not to jeopardize the flow of traffic (e.g., deadlocks, policeman directing traffic, etc.).\u003C\u002Fp>\n\u003Cp>\u003Cstrong>4) No Driver\u003C\u002Fstrong>: when there is no human driver present, say in a Robotaxi, the role of the human driver is replaced by a \u003Cem>teleoperator\u003C\u002Fem> who can intervene to resolve non-safety situations like those mentioned above.\u003C\u002Fp>\n\u003Cp>In the simplified language we propose above, the requirements from the driver are well defined, so there are no ambiguities from the end-user perspective. The human driver is either supervised by the system or is supervising the system or is allowed to disconnect attention entirely without being bothered by the system. The Eyes-off category translates to a full MRM capability of safely stopping on the shoulder of the road without blocking traffic. The value proposition of an Eyes-off setting is \u003Cstrong>time\u003C\u002Fstrong>, i.e., the human in the driving seat can legally attend to non-driving matters, within the prescribed ODD, without the need to supervise the system.\u003C\u002Fp>\n\u003Ch3>Usefulness, Safety, Scalability\u003C\u002Fh3>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F4fae36a27d981a211498c92aaf56312a_1675683373282.png\" alt=\"The process of moving from human operation to autonomous driving in an ODD should be clear.\" width=\"1650\" height=\"704\" \u002F>\u003C\u002Fp>\n\u003Cp>We contend that an Eyes-off system should be governed by three principles: (i) usefulness, (ii) safety, and (iii) scalability.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Usefulness\u003C\u002Fstrong>: A good Eyes-off system should operate in an ODD that enables prolonged and continuous periods of use such that going in\u002Fout from an ODD does not happen frequently. As depicted in the figure below, if we look at the average person’s commute, going in\u002Fout the ODD should happen only once. According to this requirement, we set the minimum useful ODD threshold to be freeways up to 80 mph, including the ability to navigate on-ramps and off-ramps. Anything below that is considered not useful. For example, a system with an ODD of freeways up to 40 mph would require the driver to take control every time the lead vehicle exceeds 40 mph. This also poses a safety risk as it increases the friction between the human and the machine.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Safety\u003C\u002Fstrong>: A safe Eyes-off solution should have no systematic errors, i.e., an error that can be reproduced in a certain emergency situation that is within the system’s ODD. Trying to hide behind statistics that the particular scenario will only happen rarely leads to unacceptable compromises in system design. \u003C\u002Fp>\n\u003Cp>To better articulate the point, let's look at the ODD of current Level 3 systems coming to market – freeways-only up to 40 mph with no lane changes. Because of the low operating speed, the system should allegedly be able to cope with any in-lane emergency braking. However, out-of-lane emergency maneuvers – responding to dangerous cut-ins, for example – are considered rare and not supported by the sensor configuration, the sensing state, and driving policy algorithms. For example, a sensor configuration that does not include high-resolution 360-degree coverage cannot support a lane change under all traffic densities. Failing to do so creates a “reproducible error.”\u003C\u002Fp>\n\u003Cp>The result of our requirement for no reproducible errors is that the system ODD should be much larger than the customer ODD. In other words, it is possible to limit the ODD to the customer to not allow lane changes in a regular mode of operations, but still, the system needs to be able to change lanes in an emergency maneuver. This notion should translate directly to the system’s design –high-resolution surround sensors, driving policy, high-definition maps, controllability, and so forth.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Scalability\u003C\u002Fstrong>: We believe the operational domain of a full Eyes-off\u002FHands-off vehicle can best be thought of as a stack of ODDs – starting from highways, then adding arterial roads, signaled intersections, unprotected turns and so forth, that eventually add up to autonomy everywhere. We call those ODDs “autonomous blades,” and through this, we have built an evolutionary path of incremental steps in our products from Eyes-on\u002FHands-off systems to full AVs.\u003C\u002Fp>\n\u003Cp>Without this approach, AV development simply doesn’t scale. Every blade of operation requires a “moonshot” of validation and engineering, and if that moonshot is successful, it doesn’t guarantee success in the next blade. Just because a prototype AV can manage city streets in daylight hours doesn’t mean it can easily adapt to multilane highways at 80 mph at night, and vice versa. Instead, we have focused our “moonshot” efforts on the Eyes-on\u002FHands-off system with full ODD as a baseline for eyes-off blades.  \u003C\u002Fp>\n\u003Ch3>The Bridge to Consumer AVs\u003C\u002Fh3>\n\u003Cp>Our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fsuper-vision\u002F\">Mobileye SuperVision™\u003C\u002Fa> camera-only Eyes-on\u002FHands-off system already contains the entire technological backbone needed to enable hands-off driving, such that the transition to eyes-off blades only adds active sensors as redundant components to the perception system. All the heavy lifting of detailed sensing, the driving policy required to maneuver the car in any traffic scenario, and the requirement for HD maps covering all types of roads are all done in the SuperVision system. The redundancies to the perception system then become the only incremental work needed to make the leap from eyes-on to eyes-off.\u003C\u002Fp>\n\u003Cp>Today more than ever, we believe in the potential for autonomous technology to transform the world and how we travel daily. We at Mobileye know many share that belief, and as we put our technologies like SuperVision on the road, we will see those benefits come to life – especially if our industry can clearly share what that future looks like and disambiguate as many uncertainties as we can.\u003C\u002Fp>","2023-02-06T08:00:00.000Z",[64,21,56,114],{"id":702,"type":100,"url":703,"title":704,"description":705,"primary_tag":33,"author_name":136,"is_hidden":96,"lang":132,"meta_description":705,"image":706,"img_alt":707,"content":708,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":709,"tags":710},194,"holon-mover-ces-mobileye-drive","HOLON Mover Featuring Mobileye Drive™ at CES","The latest application for our turnkey self-driving system takes the futuristic form of an urban shuttle designed for autonomous Mobility-as-a-Service.\n\n","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fca7685f335a68afb05bb2ab5d1ebaf0a_1672941596222.jpg","The HOLON mover incorporates Mobileye Drive, our turnkey self-driving system, to deliver fully autonomous urban transportation. (Credit: HOLON)","\u003Cp>What will autonomous mobility look like? What form will self-driving vehicles take? There’s no single answer – but here’s one rather enticing proposition: \u003Ca href=\"https:\u002F\u002Fwww.benteler.com\u002Fen\u002Fpress-media\u002Fnews-and-press-releases\u002Fdetail\u002FThe%20autonomous%20mover%20for%20everyone:%20World%20premiere%20of%20HOLON%20vehicle%20at%20CES%202023\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">the new HOLON mover\u003C\u002Fa>, unveiled last week at CES 2023 in Las Vegas.\u003C\u002Fp>\n\u003Cp>The latest implementation of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-drive-self-driving-system\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Mobileye Drive™\u003C\u002Fa>, the HOLON mover is a shuttle bus designed for urban transportation. It’s all-electric, accessible, and fully autonomous, thanks to technology from Mobileye.\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Meet the HOLON Mover\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>HOLON is a new mobility brand from \u003Ca href=\"https:\u002F\u002Fwww.benteler.com\u002Fen\u002Fpress-media\u002Fnews-and-press-releases\u002Fdetail\u002FBENTELER%20establishes%20HOLON,%20a%20new%20brand%20for%20the%20autonomous%20mobility%20of%20the%20future\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">BENTELER\u003C\u002Fa>, a leading manufacturer and supplier of metal components to the automobile industry. The new company’s first product, the HOLON mover is an autonomous shuttle bus for use in a variety of urban transportation applications – including ride pooling, ride hailing, and scheduled service.\u003C\u002Fp>\n\u003Cp>The HOLON mover has room for up to 15 passengers on board. To optimize inclusivity, it features electric double-wing doors, photo-electric sensors, an accessibility ramp, automatic securing of wheelchairs, information presented in braille, and an audiovisual guide. It can travel autonomously around town at up to 60 km\u002Fh (37 mph), with an all-electric range estimated at 290 kilometers (180 miles) between charges.\u003C\u002Fp>\n\u003Cp>To make all that happen, HOLON brought together an impressive array of partners. BENTELER’s extensive experience in automotive component manufacturing means the vehicle will be built to automotive standards of safety and quality. The renowned Italian design house Pininfarina penned its stylish form. Cognizant Mobility furnishes the software. And Mobileye provides the autonomous driving system.\u003C\u002Fp>\n\u003Cp>[**]gallery:holon-mover[**]\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Driven by Mobileye™\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The HOLON mover is the latest in a string of implementations for Mobileye Drive – our comprehensive \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">self-driving solution\u003C\u002Fa> for commercial vehicles. Mobileye Drive incorporates multiple types of sensors, with its camera subsystem operating independently of its radar\u002Flidar subsystem to deliver \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">True Redundancy™\u003C\u002Fa>. It also utilizes Mobileye Roadbook™, our AV map generated and continually updated by our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Road Experience Management™ (REM™)\u003C\u002Fa> crowdsourced mapping technology. It operates under our lean driving policy based on RSS™: the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Responsibility-Sensitive Safety™\u003C\u002Fa> model. And the whole system runs on our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">EyeQ™ System-on-Chip\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>“The market needs vehicles that seamlessly work in any traffic environment – and that is exactly what HOLON and Mobileye plan to deliver,” Johann Jungwirth, Mobileye’s Senior Vice President of Autonomous Vehicles, said at CES. “I am confident that the HOLON mover will be a huge success. There are communities around the world that are searching for a mobility solution just like it.”\u003C\u002Fp>\n\u003Cp>The HOLON mover joins a list of applications for Mobileye Drive previously unveiled, including \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fself-driving-robotaxi-sixt-germany-iaa\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">our own Robotaxi\u003C\u002Fa>, the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fudelv-transporter-autonomous-delivery-vehicles-powered-by-mobileye\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Udelv Transporter\u003C\u002Fa>, the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-transdev-lohr-maas-i-cristal-shuttles-robotaxis\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Lohr i-Cristal\u003C\u002Fa>, and a self-driving shuttle platform from \u003Ca href=\"https:\u002F\u002Fwww.schaeffler.com\u002Fen\u002Fmedia\u002Fpress-releases\u002Fpress-releases-detail.jsp?id=87723393\" target=\"_blank\" rel=\"noopener noreferrer\">Schaeffler\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>[**]gallery:holon-mover-at-ces-2023[**]\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>When will these self-driving vehicles be available? \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>HOLON aims to begin producing the mover in the United States towards the end of 2025, and plans to expand production to sites in Europe and Asia in the following years. And it already has partnerships in place for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Fdrive\u002F\" target=\"_blank\" rel=\"noopener\">self-driving Mobility-as-a-Service\u003C\u002Fa> with Beep in the U.S. and with Hamburger Hochbahn in Germany.\u003C\u002Fp>\n\u003Cp>We look forward to seeing the HOLON mover hit the road in the near future to reach another milestone in our drive \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fautonomous-vehicle-technology-everywhere-in-every-way-for-everyone\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">to bring the benefits of autonomous mobility to everyone, everywhere, in every way\u003C\u002Fa>.\u003C\u002Fp>","2023-01-12T08:00:00.000Z",[21,34,99,78],{"id":712,"type":100,"url":713,"title":714,"description":715,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":715,"image":716,"img_alt":717,"content":718,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":719,"tags":720},193,"mobileye-growth-pipeline-fueled-with-supervision-and-future-av-wins","SuperVision and Future AV Wins Fuel Growth","Mobileye booked a record stream of design wins for our ADAS technologies in 2022 which are expected to yield a $17 billion revenue pipeline through 2030.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F697750f14adf441a4f4844d92237a124_1672880637316.jpg","The Zeekr 001 electric vehicle. Owners in China will soon get the latest over-the-air update of Mobileye’s SuperVision tech. ","\u003Cp>LAS VEGAS, January 5, 2023 — Today at CES 2023, Mobileye founder and CEO Prof. Amnon Shashua will illustrate the company’s global leadership in autonomous vehicle and advanced driver-assistance technology, providing new details on the company’s business for 2023 and beyond. In particular, Shashua will lay out how future consumer AVs will come to market at scale by harnessing Mobileye’s state-of-the-art driver assist system, Mobileye SuperVision™, as the baseline for higher levels of autonomy.   \u003C\u002Fp>\u003Cp>Mobileye now sees a revenue pipeline\u003Cspan style=\"color: rgb(64, 64, 64);\">[1]\u003C\u002Fspan> of ADAS business through 2030 of greater than $17 billion – including $3.5 billion of projected revenue from SuperVision alone, a product that was only launched in the fourth quarter of 2021. Thanks to other new products like EyeQ6™ system-on-chip, the pipeline grew impressively over the course of 2022 as Mobileye added $6.7 billion projected revenue in ADAS, across projected future volume of 63.6 million systems.\u003C\u002Fp>\u003Cp>In addition to ADAS, Mobileye announced an additional $3.5 billion in expected revenue from Autonomous Mobility-as-a-Service products through 2028, based on deals with three major partners, including a recently secured mobility-as-a-service AV program with a leading EU commercial vehicle builder. Mobileye also has a line of sight for $1.5 billion in revenue from a single consumer AV (Mobileye Chauffeur™) program through 2030.\u003C\u002Fp>\u003Cp>“In the short time since we went public in October, Mobileye’s business has accelerated substantially,” said Shashua. “We’ve seen strong positive response from our existing customers and new automakers as well who believe in our vision for building cloud-connected, AI-driven driver assist and autonomous technology that can scale globally and provide meaningful benefits to millions of drivers worldwide.”\u003C\u002Fp>\u003Ch2>\u003Cstrong>SuperVision leads the market\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Mobileye’s SuperVision “eyes-on, hands-off” system is seeing strong customer demand in China, where more than 70,000 Zeekr 001 EV owners will soon get an additional over-the-air update that unlocks key mapping-based features. SuperVision will also be included in the upcoming Zeekr 009, along with near-term global launches on models from three other brands under the Geely Group umbrella.\u003C\u002Fp>\u003Cp>By combining a camera-only sensing system with Mobileye’s key mapping and decision-making technology, SuperVision gives automakers an affordable, flexible platform for eyes-on, hands-off driving across a range of operational design domains.\u003C\u002Fp>\u003Cp>The system’s success and speed-to-market in China’s highly competitive automotive landscape has driven new business wins for SuperVision-based systems around the world. Mobileye has kicked off development work with a premium European automaker for programs targeting delivery in 2025, with other customers at advanced stages of development. Overall, Mobileye now expects volume of SuperVision based vehicles to reach about 1.2 million units in 2026.\u003C\u002Fp>\u003Cp>Just as importantly, OEM’s are showing strong desire to leverage investments in SuperVision as a bridge to enable eyes-off autonomous functions – comparable to SAE Level 3 and Level 4 -- across a variety of operational design domains. This can be done by simply adding additional sensing suites and computing power in a modular way to create a high-value, cost-efficient, eyes-off product for consumer-owned vehicles in the medium term.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Continued progress on Mobility-as-a-Service technology and validation\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Beyond SuperVision and consumer-owned AVs, Mobileye has continued to develop its Mobileye Drive mobility-as-a-service (MaaS) autonomous vehicle technology in 2022. We recently signed an MOU for several thousand units with a major global producer of light commercial vehicles. In 2023, Mobileye will continue testing its AV tech, with pilots of our latest vehicle technology hitting the road in Germany.\u003C\u002Fp>\u003Cp>While sentiment around AVs has swung widely over the past year, Mobileye has remained focused on delivering scalable, modular AV technology. Ensuring public and regulatory trust in autonomous vehicles before they hit the road will require robust, transparent validation. Today, Shashua will detail for the first time Mobileye’s three-layer validation approach to AV technology that leverages our unique assets (such as Road Experience Mapping data and True Redundancy™). This combination of real-world testing, simulation and hardware-in-the-loop validation allows Mobileye to marshal its massive road-test data towards solving AVs at scale.\u003C\u002Fp>\u003Cp>Our MaaS deployment partners also continue to make progress. At CES 2023, our AV collaborator Holon revealed a new autonomous people mover powered by Mobileye Drive, one of many such collaborations we have worldwide with companies exploring different AV business models. \u003C\u002Fp>\u003Cp>By approaching AV tech in the same way we popularized ADAS technology – focusing on solutions that can be built affordably, work globally and built flexibly for different types of vehicles – Mobileye sees a clear and financially sustainable path to developing both consumer-owned and fleet-deployed AVs.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Additional expansion in ADAS\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>All of these advancements build from our ongoing innovation in the ADAS market, where we continue to see strong demand and growth. Last year alone, some 233 models launched globally with Mobileye technology inside.\u003C\u002Fp>\u003Cp>Our innovation roadmap for the future includes key new technologies like imaging radar, a sensor that can provide the benefits of lidar at a fraction of the cost. After demonstrating the potential of imaging radar last year, Mobileye has begun collaborating with Wistron NeWeb, an experienced automotive radar supplier, to bring the technology to production two years from now. And our other advanced solutions, from cloud-enhanced services to intelligent speed assist, continue to make strong inroads among key global automakers.\u003C\u002Fp>\u003Cp>As a public company once again, Mobileye’s history as a pioneer in ADAS demonstrates how we’ve changed the world over the past 20 years, and how we will bring innovation to life at a global scale in the years ahead.\u003C\u002Fp>\u003Cp>[1] Mobileye’s revenue for the periods presented represent estimated volumes based on projections of future production volumes that were provided by our current and prospective OEMs at the time of sourcing the design wins for the models related to those design wins. See the disclaimer under the heading “Forward–Looking Statements” below for important limitations applicable to these estimates.\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp> \u003Cstrong>Media Contact: \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Justin Hyde\u003C\u002Fp>\u003Cp>\u003Ca href=\"mailto:Justin.Hyde@Mobileye.com\" rel=\"noopener noreferrer\" target=\"_blank\">Justin.Hyde@Mobileye.com\u003C\u002Fa>\u003C\u002Fp>\u003Cp>+1 202-656-6749 \u003C\u002Fp>\u003Cp>___________________________________\u003C\u002Fp>\u003Cp>Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 125 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>.\u003C\u002Fp>\u003Cp> “Mobileye,” the Mobileye logo and Mobileye product names are registered trademarks of Mobileye in various jurisdictions. All other marks are the property of their respective owners.\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-family: intelone-display-regular, Inter, sans-serif; color: rgb(64, 64, 64);\">Forward-Looking Statements \u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">Statements in this press release and the presentation referenced herein that are not statements of historical fact, including statements about our beliefs and expectations, are forward-looking statements and should be evaluated as such. Forward-looking statements include descriptions of our business plan and strategies. These statements often include words such as “anticipate,” “expect,” “suggests,” “plan,” “believe,” “intend,” “estimates,” “targets,” “projects,” “should,” “could,” “would,” “may,” “will,” “forecast,” or the negative of these terms, and other similar expressions, although not all forward-looking statements contain these words. We base these forward-looking statements or projections on our current expectations, plans and assumptions that we have made in light of our experience in the industry, as well as our perceptions of historical trends, current conditions, expected future developments and other factors we believe are appropriate under the circumstances and at such time. You should understand that these statements are not guarantees of performance or results. The forward-looking statements and projections are subject to and involve risks, uncertainties and assumptions and you should not place undue reliance on these forward-looking statements or projections. Although we believe that these forward-looking statements and projections are based on reasonable assumptions at the time they are made, you should be aware that many factors could cause actual results to differ materially from those expressed in the forward-looking statements and projections. Important factors that may materially affect such forward-looking statements and projections include the following: future business, social and environmental performance, goals and measures; our anticipated growth prospects and trends in markets and industries relevant to our business; business and investment plans; expectations about our ability to maintain or enhance our leadership position in the markets in which we participate; future consumer demand and behavior; future products and technology, and the expected availability and benefits of such products and technology; development of regulatory frameworks for current and future technology; ​projected cost and pricing trends; ​future production capacity and product supply; potential future benefits and competitive advantages associated with our technologies and architecture and the data we have accumulated; the future purchase, use and availability of products, components and services supplied by third parties, including third-party IP and manufacturing services; uncertain events or assumptions, including statements relating to our addressable markets, estimated vehicle production and market opportunity, potential production volumes associated with design wins and other characterizations of future events or circumstances; future responses to and effects of the COVID-19 pandemic; availability, uses, sufficiency and cost of capital and capital resources, including expected returns to stockholders such as dividends, and the expected timing of future dividends; tax- and accounting-related expectations. Detailed information regarding these and other factors that could affect Mobileye’s business and results is included in Mobileye’s SEC filings, including the company’s Registration Statement (No. 333-267685) on Form S-1, particularly in the section entitled the “Risk Factors”. Copies of these filings may be obtained by visiting our Investor Relations website at ir.mobileye.com or the SEC’s website at www.sec.gov. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">The estimates included herein are based on projections of future production volumes that were provided by our current and prospective OEMs at the time of sourcing the design wins for the models related to those design wins. For the purpose of these estimates we estimated sale prices based on our management’s estimates for the applicable product bundles and periods. Achieving design wins is not a guarantee of revenue, and our sales may not correlate with the achievement of additional design wins. Moreover, our pricing estimates are made at the time of a request for quotation by an OEM (in the case of estimates related to contracted customers), so that worsening market or other conditions between the time of a request for quotation and an order for our solutions may require us to sell our solutions for a lower price than we initially expected. These estimates may deviate from actual production volumes and sale prices (which may be higher or lower than the estimates) and the amounts included for prospective but uncontracted production volumes may never be achieved. Accordingly, these estimations are subject to and involve risks, uncertainties and assumptions and you should not place undue reliance on these forward-looking statements or projections. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">Mobileye does not intend to provide any updates to information concerning its actual or anticipated future results of operations, including 2022 results or guidance for fiscal year 2023, in this press release or the presentation referenced herein, and investors should not infer from any statement made in this release or the presentation referenced herein any implications relating to Mobileye’s results of operations or guidance for such periods. The estimates presented are just estimates and are not based on contracted orders. Mobileye’s actual revenue for the periods presented is likely to vary materially from the estimates. \u003C\u002Fspan>\u003C\u002Fp>","2023-01-05T00:00:00.000Z",[91,64,99,21,13,107],{"id":722,"type":100,"url":723,"title":724,"description":725,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":725,"image":726,"img_alt":727,"content":728,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":729,"tags":730},190,"mobileye-and-wnc-collaborate-on-imaging-radar-production","Mobileye & WNC collaborate on imaging radar","Mobileye is developing automotive-grade, software-defined, four-dimensional digital imaging radars in-house that are targeted for production in two years.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F989f7126b675ec5849735fffea8dd911_1672779722464.png","Mobileye’s imaging radar supports other key AV vision sensors, and can detect objects, vehicles and pedestrians at distances of up to 1,000 feet. Illustration: Mobileye. ","\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64); background-color: rgb(255, 255, 255);\">LAS VEGAS, January 4, 2023 — Over the past few years, Mobileye has been developing a new technology to help autonomous vehicles sense and understand their environment – regardless of weather, lighting or road types – in addition to the company’s renowned camera-based perception systems. Known as software-defined imaging radar, or 4D radar, the technology will play a key role in bringing autonomous vehicles and the most advanced forms of driver-assistance technology to life. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">Today, Mobileye announced a collaboration with Wistron NeWeb Corp. (WNC) for production of its software-defined imaging radars. WNC, based in Taiwan, works as a major electronics and radar supplier for automakers worldwide. This collaboration is expected to allow Mobileye and WNC to begin producing automotive-grade imaging radars two years from now, with strong initial interest in the technology from key automaker customers. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">“The imaging radars we have been developing over the past few years are uniquely designed to be an essential enabler of high autonomy levels in future vehicles, by delivering rich and reliable radar output, upgrading perception-by-radar capabilities, and reducing the need for multiple lidar sensors,” said Yaniv Avital, Mobileye’s Radar Vice President and General Manager. “WNC’s experience and accomplishments as an automotive supplier can help us bring this much-needed innovation to the market by our original targeted timeline and at the expected quality.”  \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">The imaging radar developed by Mobileye goes far beyond the simple devices on vehicles today. Radars emit radio frequency signals to detect obstacles, and just like cameras, the more data they can process, the more details they can spot. When paired with advanced cameras, radars can provide sensing at longer distances and in certain weather or lighting conditions that can even challenge camera-based imaging. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F39f65e4a35960603c77ed0cb7babb57c_1672783775834.png\" alt=\"A visualization of Mobileye’s imaging radar at left; a comparison of what camera sensors see on top right versus radar data on the bottom right. The different colors in the radar image represent speed.\">Mobileye’s imaging radars use advanced radar architecture including Massive MIMO (multiple-input, multiple-output) antenna design, a high-end radio frequency design developed in-house, and high-fidelity sampling – all enabling accurate object detection and wider dynamic range. Thanks to an integrated system-on-chip design that maximizes processor efficiency, and world-leading algorithms for interpreting radar data, Mobileye’s imaging radars deliver a detailed, four-dimensional image of surroundings up to 1,000 feet away and beyond. With a 140-degree field-of-view at medium range and 170-degree field of view in close range, the radar enables more accurate detection of pedestrians, vehicles or obstructions that other sensors might miss – even on crowded urban streets.  \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">“The new imaging radar technology is a key focus for future high-level autonomous driving,” said Repus Hsiung, Vice President & General Manager of the Automotive & Industrial Solutions BG at WNC. \"We are delighted to collaborate with Mobileye to accelerate the availability of advanced imaging radars in the market. Leveraging our expertise in automotive electronics and radar solutions, we look forward to working with Mobileye to further develop exciting new capabilities.” \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\"> Mobileye’s True Redundancy™ approach to autonomous vehicles envisions using imaging radars to create a 360-degree sensing system that operates in addition to, but independently from, a camera-based system. By having multiple systems that are each capable of navigating a vehicle alone, the “eyes off” autonomous system can deliver reliable rides with low chance of failure and simplified safety validation. Imaging radar can also play a role in more advanced hands-free ADAS solutions as an alternative to LiDAR solutions, which are typically far more expensive.  \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">___________________________________ \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 125 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(5, 99, 193);\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>\u003Cspan style=\"color: rgb(64, 64, 64);\">. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\"> “Mobileye,” the Mobileye logo and Mobileye product names are registered trademarks of Mobileye in various jurisdictions. All other marks are the property of their respective owners. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\"> \u003C\u002Fspan>\u003C\u002Fp>","2023-01-04T00:00:00.000Z",[91,99,21,27],{"id":732,"type":100,"url":733,"title":734,"description":735,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":735,"image":736,"img_alt":737,"content":738,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":729,"tags":739},191,"mobileye-kicks-off-av-pilot-in-germany","Mobileye Kicks Off AV Pilot in Germany","In a key step, Mobileye has successfully completed the AV-Permit process outlined by TÜV SÜD to operate NIO ES8 vehicles with AV technology on German streets.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F1da7649597f1a18fe101abbb7eeb4f87_1673551896394.jpg","NIO ES8 equipped with cameras, radar and lidar sensors, of the type to be used in an autonomous vehicle test in Germany.","\u003Cp>With the start of the year 2023, Mobileye has taken a key step on the road to the autonomous future of mobility: Mobileye obtained a permit recommendation from TÜV SÜD, an independent third-party for testing, certification, auditing and advisory service in Germany, enabling Mobileye to operate its AV technology on German streets. The permit makes way for Mobileye to expand the pilot phase in Germany and operate \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fself-driving-robotaxi-sixt-germany-iaa\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">Mobileye Drive™-equipped NIO ES8s\u003C\u002Fa> with a responsible safety driver on all roads in Germany.\u003C\u002Fp>\u003Ch3>\u003Cstrong>Kick-Off for Mobility-as-a-Service (MaaS) Projects in Munich and Darmstadt\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>With the official recommendation, Mobileye is taking the next step in realizing new mobility concepts in Germany and beyond. \u003Ca href=\"https:\u002F\u002Fwww.nio.com\u002Fnews\u002Fnio-inc-announces-strategic-collaboration-mobileye-bring-level-4-autonomous-driving-vehicles\" rel=\"noopener noreferrer\" target=\"_blank\">NIO’s ES8\u003C\u002Fa> was chosen by Mobileye in 2021 as the vehicle platform for Mobility-as-a-Service (MaaS) offerings underway with various partners in Munich and Darmstadt, as well as in other projects around Europe. NIO ES8s equipped with Mobileye’s self-driving hardware and software are planned to be used in a robotaxi service as well as in the integration of on-demand shuttles into local public transport in Germany. Following the regulations adopted by European Union and German authorities for safe autonomous driving (AV) testing and deployment in 2022, the pilot stage for these services on German roads will accelerate throughout 2023. A safety driver will be behind the wheel until all needed approvals and permits are obtained for the vehicle to be entirely unmanned.\u003C\u002Fp>\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F8c9ad648354eb06543761a4ea6d73f83_1673551976724.jpg\" alt=\"Mobileye will test its autonomous vehicles on German roadways, like this Autobahn through Munich, where TÜV SÜD is based.\">\u003C\u002Fp>\u003Cp>“We are excited to have taken the next steps in bringing our self-driving technology onto German streets,” says \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">Johann Jungwirth\u003C\u002Fa>, Senior Vice President, Autonomous Vehicles at Mobileye. “We are thankful for TÜV Süd’s trusted support in expanding our autonomous vehicle technology testing in Germany. This allows us to show our capabilities to consumers, automakers and transportation agencies.”\u003C\u002Fp>\u003Ch3>\u003Cstrong>Mobileye Technology Onboard\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>The NIO ES8 is retrofitted with a broad range of sensors and Mobileye’s own autonomous self-driving system Mobileye Drive™ for a defined operational design domain (“ODD”)\u003Cspan style=\"color: rgb(64, 64, 64);\">. A set of 13 cameras, plus an independent secondary perception system consisting of six surround radars and three long-range and six short-range surround lidars gives the self-driving vehicle redundant sensing capabilities (we call this approach \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(64, 64, 64);\">True Redundancy™\u003C\u002Fa>\u003Cspan style=\"color: rgb(64, 64, 64);\">). The \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(64, 64, 64);\">EyeQ™ System-on-Chip \u003C\u002Fa>\u003Cspan style=\"color: rgb(64, 64, 64);\">(SoC) provides the necessary computing power to not only process the real-world data but also to make use of Mobileye’s \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(64, 64, 64);\">Road Experience Management™ (REM™)\u003C\u002Fa>\u003Cspan style=\"color: rgb(64, 64, 64);\"> – AV maps – and lean driving policy with the mathematical model for automated driving we call \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(64, 64, 64);\">Responsibility-Sensitive Safety™ (RSS™)\u003C\u002Fa>\u003Cspan style=\"color: rgb(64, 64, 64);\">. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(64, 64, 64);\">This system allows for scalability and different MaaS services like autonomous robotaxis, public-transit shuttles or last-mile goods delivery for defined ODD.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fbcd5346c56d70331fe329e7beb6e2f0a_1673551997991.jpg\" alt=\"A fleet of NIO ES8 robotaxis powered by Mobileye Drive™ outside our headquarters in Jerusalem, Israel.\">\u003C\u002Fp>\u003Ch3>\u003Cstrong>Ensuring AV Standards with TÜV SÜD\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>\u003Cspan style=\"color: black; background-color: white;\">As in 2020, when Mobileye was one of the first companies outside of automakers to receive a permit to \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-testing-self-driving-vehicles-germany\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(81, 94, 255); background-color: rgb(255, 255, 255);\">test autonomous vehicles (AVs) on open roads in Germany\u003C\u002Fa>\u003Cspan style=\"color: black; background-color: white;\">, TÜV SÜD and Mobileye have worked closely together with the regulatory authorities to ensure safe operation of the self-driving vehicle powered by Mobileye Drive.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>Mobileye provided comprehensive technical documentation as well as undergoing various safety tests with the robotaxi in the past months to obtain the TÜV SÜD approval recommendation for operating self-driving vehicles on public roads in Germany.. TÜV SÜD has developed a rigorous assessment framework and test procedure in recent years that works as a blueprint for providers of AV technologies while building consumer trust in the reliability and safety of the technology.\u003C\u002Fp>",[21,34,27,99],{"id":741,"type":100,"url":742,"title":743,"description":744,"primary_tag":20,"author_name":131,"is_hidden":96,"lang":132,"meta_description":744,"image":745,"img_alt":746,"content":747,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":748,"tags":749},188,"mobileye-announces-ces-press-conference-with-prof-amnon-shashua","Mobileye Announces CES 2023 Press Conference with Prof. Amnon Shashua  ","Mobileye: Now, Next, Beyond to be presented live from Las Vegas on January 5 at 11 a.m. PST ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F07bae5284d54540c19d53a26fece6615_1671703079240.png","Mobileye: Now, Next, Beyond -  CES 2023 Press Conference with Prof. Amnon Shashua","\u003Cp>\u003Cstrong style=\"color: #080606;\">JERUSALEM, December 21, 2022:\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> Mobileye (Nasdaq: MBLY) will present Mobileye: Now, Next, Beyond; its CES 2023 Press Conference with CEO Professor Amnon Shashua on January 5, 2023 at 11 a.m. PST. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #080606;\">Prof. Shashua will provide an update on the state of Mobileye’s market leadership and how Mobileye will bring its near- and long-term vision to life. The presentation will illustrate the industry’s most advanced ADAS-to-AV technology, detailing the spectrum of solutions Mobileye is pioneering to redefine the driving experience now and in the future. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #080606;\">CES visitors are invited to learn more about how Mobileye is driving the autonomous vehicle evolution by visiting Mobileye in the Las Vegas Convention Center (LVCC) West Hall booth #4601, Thursday, Jan. 5 through Sunday, Jan. 8, 2023, during show hours. \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">Mobileye: Now, Next, Beyond\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">Press Conference with Professor Amnon Shashua \u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">When:\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> Thursday, January 5, 11 a.m. PST (2 p.m. EST | 7 p.m. GMT | 9 p.m. IST) \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">Where:\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> LVCC West Hall | Room W327  \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">How:\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> Register today to reserve your seat: \u003C\u002Fspan>\u003Ca style=\"color: #0563c1;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\">\u003Cu>https:\u002F\u002Fwww.mobileye.com\u002Fces-2023\u003C\u002Fu>\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2023\u002F\" rel=\"noopener noreferrer\">\u003Cu>\u002F\u003C\u002Fu>\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #080606;\">Livestream:\u003C\u002Fstrong>\u003Cspan style=\"color: #080606;\"> Watch live at: \u003C\u002Fspan>\u003Ca style=\"color: #0563c1;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2024\u002F\">\u003Cu>https:\u002F\u002Fwww.mobileye.com\u002Fces-2023\u003C\u002Fu>\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fces-2023\u002F\" rel=\"noopener noreferrer\">\u003Cu>\u002F\u003C\u002Fu>\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #080606;\">Add the livestream to your calendar by registering in advance.  \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #080606;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"color: #101820;\">Contacts\u003C\u002Fstrong>\u003Cspan style=\"color: #101820;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #101820;\">Dan Galves \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #101820;\">Investor Relations \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca style=\"color: #0563c1;\" href=\"mailto:investors@mobileye.com\" target=\"_blank\" rel=\"noopener noreferrer\">investors@mobileye.com\u003C\u002Fa> \u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #101820;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #101820;\">Justin Hyde \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #101820;\">Media Relations \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Ca style=\"color: #0563c1;\" href=\"mailto:justin.hyde@mobileye.com\" target=\"_blank\" rel=\"noopener noreferrer\">justin.hyde@mobileye.com\u003C\u002Fa>\u003Cspan style=\"color: #101820;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #080606;\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #404040;\">___________________________________ \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"color: #404040;\">Mobileye (Nasdaq: MBLY) leads the mobility revolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 125 million vehicles worldwide have been built with Mobileye technology inside. In 2022 Mobileye listed as an independent company separate from Intel (Nasdaq: INTC), which retains majority ownership. For more information, visit \u003C\u002Fspan>\u003Ca style=\"color: #0563c1;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">https:\u002F\u002Fwww.mobileye.com\u003C\u002Fa>\u003Cspan style=\"color: #404040;\">. \u003C\u002Fspan>\u003C\u002Fp>","2022-12-21T08:00:00.000Z",[107,13,21,99,91,78],{"id":751,"type":100,"url":752,"title":753,"description":754,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":754,"image":755,"img_alt":756,"content":757,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":758,"tags":759},184,"goggo-network-and-mobileye-plan-to-collaborate-to-introduce-level-autonomous-vehicles-for-logistics-in-europe","Goggo Network & Mobileye collaborate on autonomous logistics vehicles","Goggo Network to incorporate up to 40 autonomous vehicles with the Level 4 self-driving system Mobileye Drive™ for the delivery of goods in Spain and France.\n","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7159351a49067075480f91fa4ddc9f9d_1670427843381.png","Goggo Network and Mobileye team up for autonomous logistics.","\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(34, 34, 34);\">Goggo Network, \u003C\u002Fspan>the autonomous mobility company founded by Martin Varsavsky and Yasmine Fage and with operations in Spain and France, has signed a Memorandum of Understanding (MoU) with Mobileye, a global leader in the development of computer vision and machine learning, data analysis, localization and mapping for Advanced Driver Assistance Systems and autonomous driving, as part of its strategy to drive the future of autonomous mobility and logistics in Spain and Europe. With this agreement, Goggo plans to introduce Level 4 autonomous vehicles in Spain for the first time.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Specifically, up to 40 autonomous vehicles with SAE Level 4 features, equipped with the Mobileye Drive technology, are expected to be deployed and operated by Goggo in cities around Spain and France.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">This system matches Goggo’s plans to roll out logistics services across Europe in a next step, as Mobileye Drive is capable of adapting to various driving environments and driver behavior.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Importantly, both Goggo Network and Mobileye agree that a transformation to a smarter, safer and more environmentally efficient driverless future is needed. For this reason, both companies have decided to join forces to achieve the autonomous delivery of goods using pioneering technology from Mobileye.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Mobileye Drive is a part of Mobileye’s full stack of self-driving Mobility-as-a-Service (MaaS) solutions. Powered by the EyeQ® system-on-a-chip and fed by multiple input sensors like camera, radar and lidar, the self-driving system can be implemented in various use cases like robotaxis, consumer passenger vehicles or commercial delivery vehicles.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">For the implementation of the deployment, Goggo will assess the coverage of the road network and provide backend interfaces (APIs) for mission control and fleet management. In turn, Goggo will be responsible for obtaining all necessary permits and licences to test and operate the service in the relevant municipalities.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Goggo plans to start operating with safety drivers to oversee the entire service in 2023, and once the respective safety validations have been completed and regulatory clearance obtained, to eliminate the driver altogether to make the service autonomous Level 4.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\"At Goggo Network we are looking to collaborate with leading companies in their sector, such as Mobileye, which will allow us to add value to the autonomous logistics sector. With this agreement, we will be able to go a step further in our strategy and introduce Level 4 autonomous vehicles for the first time in our country, making the most of a pioneering technology that stands out for its safety”, explains Yasmine Fage, co-founder and COO of Goggo Network.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Johann Jungwirth, Senior Vice President, Autonomous Vehicles of Mobileye, adds: “The collaboration with Goggo Network shows how our vision of delivering self-driving systems for various use cases will come to life. Reshaping mobility for the cities of the future will bring great benefits for everybody, and Goggo’s logistics solutions help bring us closer to this reality.”\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong>About Goggo Network\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Founded in 2018 by Martin Varsavsky and Yasmine Fage, \u003Ca href=\"https:\u002F\u002Fgoggo.network\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: windowtext;\">Goggo Network\u003C\u002Fa> operates fleets of autonomous vehicles and robots for last mile transport, with a vision to provide autonomous, electric and shared mobility solutions by creating Autonomous Mobility Networks (AMN). Currently based in Madrid, Berlin and Paris, Goggo Network operates in Spain, France and Germany.\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">Mobileye (Nasdaq: MBLY) is driving the autonomous vehicle evolution with its autonomous driving and driver-assistance technologies, harnessing world-renowned expertise in computer vision, artificial intelligence, mapping, and data analysis. Since its founding in 1999, Mobileye has pioneered such groundbreaking technologies as REM™ crowdsourced mapping, True Redundancy™ sensing, and Responsibility Sensitive Safety (RSS). These technologies are driving the ADAS and AV fields towards the future of mobility – enabling self-driving vehicles and mobility solutions, powering industry-leading advanced driver-assistance systems and delivering valuable intelligence to optimize mobility infrastructure. To date, more than 125 million vehicles worldwide have Mobileye technology inside. In 2022, Mobileye was listed as an independent company, separate from Intel (Nasdaq: INTC) which retains majority ownership of Mobileye.\u003C\u002Fp>","2022-11-28T00:00:00.000Z",[21,99,34],{"id":761,"type":100,"url":762,"title":763,"description":764,"primary_tag":136,"author_name":136,"is_hidden":96,"lang":132,"meta_description":764,"image":765,"img_alt":766,"content":767,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":768,"tags":769},136,"autonomous-vehicle-detroit-united-states","Level 4 Autonomy Now Testing in Detroit with Mobileye Drive™","Our fully autonomous vehicle reaches American roads for the first time with True Redundancy™ sensing subsystems: one based on cameras and another on radar and lidar.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F2f49505e45882ee08906fe494b3f7d20_1664775234337.png","NIO ES8 autonomous vehicle equipped with Mobileye Drive arrives in Detroit, Michigan, for testing in the United States.","\u003Cp>Over the past few years, Mobileye has run one of the most ambitious testing programs in the world for autonomous vehicles. To date, our development AVs have operated in about 20 cities across ten countries on three continents around the globe. Now, this program is entering its next phase as \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">our fully autonomous vehicle equipped with Mobileye Drive™\u003C\u002Fa> has begun testing in Detroit \u003Cspan style=\"background-color: rgb(255, 255, 255); color: rgb(0, 0, 0);\">– \u003C\u002Fspan>the first time our future Level 4 self-driving solution has hit U.S. roads.\u003C\u002Fp>\u003Cp>Integrated into the all-electric NIO ES8 sport-utility vehicle, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-drive-self-driving-system\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">Mobileye Drive\u003C\u002Fa> combines the power of our unique approach to autonomous mobility with our experience in delivering driver-assistance systems in nearly 120 million vehicles. The system benefits from unique Mobileye innovations, including \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">True Redundancy™\u003C\u002Fa> sensing, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">Road Experience Management™\u003C\u002Fa> (REM™) crowdsourced mapping, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">Responsibility-Sensitive Safety\u003C\u002Fa> (RSS) driving policy.\u003C\u002Fp>\u003Cp>Where our \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002FvL_QNy25n74\" rel=\"noopener noreferrer\" target=\"_blank\">prior test cars\u003C\u002Fa> used either cameras alone or a combination of lidars and radars alone, the commercial version of Mobileye Drive employs both – a 360-degree suite of advanced sensing technology containing 11 cameras, 6 radars, 3 long-range lidars and 6 short-range lidars – all powered by our industry-leading \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">EyeQ® chips\u003C\u002Fa>. Under our True Redundancy approach, the camera subsystem operates independently of the radar\u002Flidar subsystem, providing more robust sensing of road conditions and other traffic, while also providing safety-critical redundancy as each subsystem complements its fellow subsystem.\u003C\u002Fp>\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7972ba7a570cd5ecf164a006930f3ada_1662541681368.jpg\" alt=\"A fleet of NIO ES8 autonomous vehicles equipped with Mobileye Drive at our headquarters in Jerusalem, Israel.\">\u003C\u002Fp>\u003Cp>\u003Cem>Pictured above: a fleet of NIO ES8 electric crossover utility vehicles outside Mobileye headquarters in Jerusalem, Israel (for illustration).\u003C\u002Fem>\u003C\u002Fp>\u003Cp>\u003Cstrong>Testing Globally, Driving Locally\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Rather than deploying autonomous mobility in limited geographic areas, we believe that self-driving technology will need to be widely usable across many different types of roads and situations. This means that our technology should be adaptable not just to different locations, but to different climates and driving cultures as well.\u003C\u002Fp>\u003Cp>Anyone who’s ever driven in a foreign country knows you need not just a map, but also an understanding of the local “rules of the road.” The REM-powered Mobileye Roadbook™ helps us gather data on the general behavior of traffic in different places, and RSS adapts the Mobileye Drive system to local behavior in those places. By testing Mobileye Drive in Detroit, we’ll expose Mobileye Drive to the everyday challenges of American driving, and some unique local roadway characteristics (like “\u003Ca href=\"https:\u002F\u002Fwww.michigan.gov\u002Fmdot\u002FTravel\u002Fsafety\u002FRoad-Users\u002Fmichigan-lefts\" rel=\"noopener noreferrer\" target=\"_blank\">Michigan lefts\u003C\u002Fa>”) to further verify its capabilities.\u003C\u002Fp>\u003Cp>“Our Detroit testing of Mobileye Drive is helping us ensure that the system can bring forward the global commercialization of autonomous driving technology and deliver on its promise to vastly improve road safety,” said Johann “JJ” Jungwirth, Senior Vice President of Autonomous Vehicles at Mobileye. “We take the challenge of proving the capabilities of our technology seriously. By testing in the birthplace of the American automotive industry, we expect to make major progress toward our goals.”\u003C\u002Fp>\u003Cp>\u003Cstrong>Safety for Everyone\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>The \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fself-driving-robotaxi-sixt-germany-iaa\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">NIO ES8 equipped with Mobileye Drive\u003C\u002Fa> serves as a test platform in the development of our turnkey self-driving solutions for both commercial and future consumer AVs. Fleets of this vehicle will also form the basis of the robotaxi services we’re preparing to roll out in the coming months with our partners in Germany and Israel.\u003C\u002Fp>\u003Cp>Mobileye has worked closely with the U.S. National Highway Traffic Safety Administration to ensure safe operation of these vehicles on U.S. roads. A highly trained safety driver is behind the wheel of the Mobileye vehicles while testing in Detroit. Our current test plan does not include giving rides to members of the public, or testing without safety drivers.\u003C\u002Fp>\u003Cp>In the months ahead, we’ll have more milestones to announce around the progress of Mobileye Drive.\u003C\u002Fp>","2022-09-07T00:00:00.000Z",[21,99],{"id":771,"type":141,"url":772,"title":773,"description":774,"primary_tag":12,"author_name":136,"is_hidden":96,"lang":132,"meta_description":774,"image":775,"img_alt":776,"content":777,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":778,"tags":779},129,"eyeq-kit-sdk","EyeQ Kit™ Unlocks the Power of Our System-on-Chip","Our new software development kit (SDK) empowers automakers to develop and deploy their own differentiated market offerings on top of Mobileye’s efficient and scalable EyeQ® SoC.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F17635ed8e5c1a3721e5239f2d18b3405_1669106212111.jpg","EyeQ Kit™ opens up new possibilities for automobile manufacturers using Mobileye's hardware.","\u003Cp>Over the course of the past two decades, the world’s leading automakers have come to count on the efficiency, scalability, and performance of EyeQ®. This automotive-grade family of Systems-on-Chip serves as the brain behind everything Mobileye does. And now we’re unlocking the power of EyeQ further with the introduction of the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Feyeq-kit\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">EyeQ Kit™\u003C\u002Fa>.\u003C\u002Fp>\u003Cp>This new software development kit (SDK) is designed to \u003Cspan style=\"color: black;\">enable our OEM customers to realize the full potential of \u003C\u002Fspan>EyeQ\u003Cem> \u003C\u002Fem>to power their own applications. \u003Cspan style=\"color: black;\">Based on the highly efficient and heterogeneous compute architecture of our \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Feyeq6-system-on-chip\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">powerful new EyeQ6\u003C\u002Fa>\u003Cspan style=\"color: black;\"> and \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-ces-2022-tech-news\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">EyeQ\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-ces-2022-tech-news\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">\u003Cem> \u003C\u002Fem>\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-ces-2022-tech-news\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">Ultra\u003C\u002Fa>\u003Cspan style=\"color: black;\"> processors, EyeQ Kit allows automotive manufacturers to build their own applications on top of \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">Mobileye's cutting-edge core technologies\u003C\u002Fa>\u003Cspan style=\"color: black;\">.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: black;\">Proven Technology, Greater Flexibility\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: black;\">From general-purpose CPU cores to high-compute-density accelerators – including deep-learning neural networks – \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">EyeQ\u003C\u002Fa>\u003Cspan style=\"color: black;\"> has the scalable and modular architecture to deliver high performance, while \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fwhy-tops-arent-tops-when-it-comes-to-av-processors\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">requiring modest TOPS (Trillions of Operations per Second)\u003C\u002Fa>, all within a low power envelope\u003Cspan style=\"color: black;\">. These are the advantages that make EyeQ\u003C\u002Fspan>\u003Cem> \u003C\u002Fem>\u003Cspan style=\"color: black;\">the System-on-Chip that’s trusted by dozens of the world’s leading automakers to power the ADAS features in hundreds of models – amounting to more than \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002F100-million-eyeq-chips\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">100 million vehicles\u003C\u002Fa>\u003Cspan style=\"color: black;\"> (as of the end of 2021). And now, as more \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: black;\">advanced driver-assistance features evolve into autonomous driving\u003C\u002Fa>\u003Cspan style=\"color: black;\">, EyeQ Kit provides automakers with a platform for brand expression on top of Mobileye’s proven technology stack.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: black;\">EyeQ Kit allows automakers to benefit from our \u003C\u002Fspan>EyeQ \u003Cspan style=\"color: black;\">architecture and the technologies that we have built upon it – including \u003C\u002Fspan>industry-leading computer vision capabilities\u003Cspan style=\"color: black;\">, REM™ crowdsourced mapping, and RSS-based driving policy. Using EyeQ Kit, OEMs can further leverage the power of our System-on-Chip for what \u003C\u002Fspan>\u003Cem style=\"color: black;\">they \u003C\u002Fem>\u003Cspan style=\"color: black;\">need so that they can concentrate on what matters most: implementing the latest technological functions to enhance the driving experience, with a look and feel unique to their products. \u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: black;\">These functions include advanced driver-assistance features such as Adaptive Cruise Control, Traffic Jam Assist\u002FPilot, Highway Assist\u002FPilot, Full ODD In-Path Assist, and much more. Beyond driver-assistance, EyeQ Kit also \u003C\u002Fspan>enables co-hosting of a broad range of visualization and driver-monitoring applications directly on the EyeQ SoC. Integrating these increasingly sought-after functions directly onto EyeQ removes the need for \u003Cspan style=\"color: black;\">additional safety-critical ECUs and collateral integration, which unlocks the potential for cost-savings and reduced complexity. \u003C\u002Fspan>EyeQ Kit also enables additional functions including automated parking, augmented and virtual reality displays, and human-machine interfaces.\u003C\u002Fp>\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb6006d861e6908b90f7f221bf2ff3474_1657016205850.png\" alt=\"EyeQ Kit uses standardized APIs, development platforms, and operating systems to enable smooth access by Mobileye's OEM customers.\">\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"color: black;\">EyeQ Kit Speaks Your Language\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: black;\">EyeQ Kit is based on standard APIs – such as OpenCL and TensorFlow – and X86 development platforms. By \"speaking\" these common languages, EyeQ Kit allows OEMs to develop their own applications conveniently and efficiently, without the need for specialized skills or specific hardware vendors. This, of course, carries the potential to reduce development costs, accelerate time to market, and enable hardware-vendor flexibility for the full development cycle – from functional bring-up to deployment and performance-tuning.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>In short, EyeQ Kit opens up a whole new world of possibilities for the automakers whose vehicles we’re committed to enhancing with our cutting-edge technologies. Visit the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002Feyeq-kit\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">EyeQ Kit\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">EyeQ SoC\u003C\u002Fa> pages on the Mobileye website to learn more.\u003C\u002Fp>","2022-07-05T00:00:00.000Z",[13,21],{"id":781,"type":100,"url":782,"title":783,"description":784,"primary_tag":58,"author_name":136,"is_hidden":96,"lang":132,"meta_description":784,"image":785,"img_alt":786,"content":787,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":788,"tags":789},122,"autonomous-vehicle-testing-miami-stuttgart","Autonomous on the Streets of Miami and Stuttgart","With the addition of two more locations in Florida and Germany, we have tested AVs in ten cities in six countries across three continents around the world.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F2e1f3ee26f2da03071bbd121f032c0fb_1651055587131.jpg","Mobileye autonomous vehicle testing in Miami, Florida","\u003Cp>An autonomous vehicle capable of operating in one place may be of benefit to those in that particular location – but Mobileye’s stated goal is to develop self-driving technology to be easily deployable anywhere and everywhere.\u003C\u002Fp>\n\u003Cp>That’s why we’ve been spending the past several years \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frobotaxi-night-drive-jerusalem-unedited-video\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">testing our self-driving vehicles\u003C\u002Fa> not in carefully selected and geofenced environments, but rather alongside actual traffic, in real-life conditions, in locations around the world. And now we’ve expanded our global footprint yet again by commencing testing of our autonomous vehicles in both Miami and Stuttgart.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>AV Everywhere\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Beyond its image of exotic cars cruising sun-soaked streets, driving in downtown Miami is characterized by heavy congestion, with significant \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Favs-and-the-drive-for-pedestrian-safety\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">pedestrian\u003C\u002Fa>, cyclist, even skateboard and inline-skating traffic.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Ciframe class=\"ql-video\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fipc1o5M0lRQ\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>Meanwhile Stuttgart – aside from being widely known as the birthplace of the automobile and a major hub of the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-salutes-israels-induction-into-the-global-automotive-industry\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">global automotive industry\u003C\u002Fa> – presents a complex mix of steep landscapes and driving on urban, rural, and high-speed (often even derestricted) Autobahn highways.\u003C\u002Fp>\n\u003Cp>These latest locations join our AV testing programs previously launched in \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002FvL_QNy25n74\" target=\"_blank\" rel=\"noopener noreferrer\">Detroit\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fpress-kit\u002Fpress-kit-mobileye-new-york-city\u002F\" target=\"_blank\" rel=\"noopener\">New York\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-releases-unedited-footage-of-a-40-minute-av-ride-through-jerusalem\u002F\" target=\"_blank\" rel=\"noopener\">Jerusalem\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fyoutu.be\u002FZSihbQDg2HA\" target=\"_blank\" rel=\"noopener noreferrer\">Tel Aviv\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmunich-av-video\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Munich\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fparis-ratp-autonomous-vehicle-testing-pilot\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Paris\u003C\u002Fa>, Tokyo, and Shanghai. With the addition of Miami and Stuttgart, we have had testing programs in ten cities in six countries across three continents around the world.\u003C\u002Fp>\n\u003Cp>“Mobileye is scaling its AV testing through the addition of new locations,” notes Johann “JJ” Jungwirth, Vice President of Mobility-as-a-Service (Maas) at Mobileye. “Adding Miami and Stuttgart to our testing program represents a commitment to ensuring, first and foremost, safety, and, second, a ‘quality’ rider experience, and at the same time strengthens the foundation for the large-scale commercialization of autonomous mobility services worldwide by confronting and coping with broad and complex driving scenarios, traffic rules, and unique conditions in various cities.”\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Ciframe class=\"ql-video\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FlVQuUPvy9GU\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Scalable by Design\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>As with each city our autonomous vehicles have reached, the unique parameters presented by these latest locations pose a novel set of challenges and conditions for our autonomous vehicles to adapt to. And they’ve adapted rather quickly: in fact, our AVs were cruising the streets of Miami within just two weeks of arrival.\u003C\u002Fp>\n\u003Cp>Central to that quick turnaround and Mobileye’s “AV everywhere” strategy is our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Road Experience Management™\u003C\u002Fa> mapping technology. By crowdsourcing data from millions of vehicles already on the road equipped with our technology, REM™ can map new roadways quickly, efficiently, and exactingly – at the push of a button and in near-real time. The resulting Mobileye Roadbook™ provides our autonomous vehicles with \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frem-mapping-avs\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">highly detailed, precise, and up-to-date information\u003C\u002Fa> about the driving environment, supplementing the vehicle’s onboard sensors.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F73b5342ec7a22fb9e21bc13e48a058e1_1651055665297.jpg\" alt=\"Mobileye autonomous vehicle testing in Miami, Florida\" \u002F>\u003C\u002Fp>\n\u003Cp>The scalability of our approach to self-driving technology is further reinforced by our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Responsibility-Sensitive Safety\u003C\u002Fa> model. RSS yields both a lean driving policy that accounts for differences in local driving culture and an open framework for regulators to pave the way for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fav-scale-erez-dagan-jack-weast-reuters\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">the deployment of autonomous vehicles at scale\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>From mapping and driving policy to sensing and processing, everything Mobileye builds, we build to scale. That’s what enables us to bring the benefits of self-driving technology to everywhere, in every way, for everyone – from Miami to Stuttgart and beyond.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F991d3b4affc461445e64b3ab374b2ae7_1651055633626.jpg\" alt=\"Mobileye autonomous vehicle testing in Miami, Florida\" \u002F>\u003C\u002Fp>","2022-04-27T07:00:00.000Z",[21,84,99],{"id":791,"type":100,"url":792,"title":793,"description":794,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":794,"image":795,"img_alt":796,"content":797,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":96,"publish_date":798,"tags":799},167,"mobileye-avs-now-driving-with-full-sensing-suite","Mobileye AVs Now Driving with Full Sensing Suite","Now equipped with True Redundancy sensing, Mobileye AVs display human-like driving skill in a new, unedited driving video.","https:\u002F\u002Fstatic.mobileye.com\u002Fdev\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3d8be41c9e388e164080ec03ce233f26_1663241886991.jpg","​Mobileye Vice President Johann Jungwirth takes viewers on a virtual drive through the hectic streets of Jerusalem in a robotaxi.","\u003Cp>\u003Cem>This news content was originally published on the Intel Corporation Newsroom.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"background-color: #ffffff; color: #262626;\">What’s New:\u003C\u002Fstrong>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> Mobileye, an Intel company, today showed its True Redundancy™ sensing system operating hands-free in Israel – a major milestone in preparation for the debut of its planned robotaxi services in Israel and Germany. A new, \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fyoutu.be\u002FpDyMzz8HMIc\" target=\"_blank\" rel=\"noopener noreferrer\">unedited video\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> shows the vehicle operating in autonomous mode while mimicking the multi-stop behavior of a ride-hailing service with humanlike skill.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cem>“Mobileye Drive™ with True Redundancy defies industry norms with separate sensing subsystems that act as backups to one another. The very normal way in which the vehicle navigates very complex scenarios proves the value in this approach.”\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp>–Johann Jungwirth, vice president of mobility-as-a-service at Mobileye\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"background-color: #ffffff; color: #262626;\">What It Means: \u003C\u002Fstrong>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">The video shows the Mobileye AV going through the motions of a robotaxi service, driving to multiple destinations and pausing where it might pick up and drop off passengers. In this fifth installment of the \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLWCfS_Yhbvs5MtQIjNfN-xLU30mc1qjEc\" target=\"_blank\" rel=\"noopener noreferrer\">unedited drive series\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">, the capabilities of \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\" target=\"_blank\" rel=\"noopener\">True Redundancy\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">, Mobileye’s alternative approach to autonomous vehicle (AV) sensor fusion, are on full display as the Mobileye AV robotaxi navigates the complex streets of Jerusalem at night. While previous unedited videos have shown the AV driving only with the camera subsystem, this new installment comes from the fully configured \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-moves-garage-streets\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">AV\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> that Mobileye is planning to use in commercial robotaxi deployments.  \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"background-color: #ffffff; color: #262626;\">How It Works:\u003C\u002Fstrong>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> True Redundancy is Mobileye’s unique approach to environmental sensing whereby two independent subsystems – one camera-only and the other a lidar-radar combination – each serve as backups to each other instead of as complementary systems. The result is a sensing solution believed to deliver a higher mean time between failures. Prototype AVs now driving in Israel are Mobileye’s first to combine the two systems in a single vehicle, demonstrating how the robotaxi is expected to perform in real-world operations.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">In the 40-minute unedited video, the Mobileye AV is seen completing complex, real-world driving maneuvers despite harsh nighttime roadway lighting and complicated road signs. The very humanlike driving behavior of the AV comes across as remarkably unremarkable in that it handles very challenging maneuvers smoothly.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">Making it look easy, the AV negotiates with human drivers when executing a left turn at an unprotected junction (4:04; 06:48); safely and successfully navigates around jaywalking pedestrians (08:28; 10:42); seamlessly handles illegal maneuvers by other drivers (04:34); completes a 180-degree turn in an intersection with multiple traffic signals (25:18); navigates around vehicles blocking proper lane usage (25:39); rides through a roundabout with pedestrians (26:44); and completes other more regular driving maneuvers.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"background-color: #ffffff; color: #262626;\">Why It Matters:\u003C\u002Fstrong>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> The demonstration of True Redundancy on real roads helps to dispel past industry skepticism that doubted whether Mobileye’s cutting-edge approach to environmental sensing could work. More remarkable is the almost mundane quality to the video. The AV handles the drive more or less as a human would (and in some cases better), showing its near-readiness for planned robotaxi operations. Building on the already vast capabilities of Mobileye’s camera-first AV development fleet, the addition of radar-lidar to its sensor suite is the final piece to achieving what the company set out to do with its differentiated AV technology.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">Operationalizing the True Redundancy system is a crucial milestone toward Mobileye’s planned robotaxi service scheduled for later this year in \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-sixt-plan-new-robotaxi-service\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Germany\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> and Israel. Mobileye has started the permit and regulatory approval process in both countries to enable the company to begin removing safety drivers on public roads.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong style=\"background-color: #ffffff; color: #262626;\">More Context: \u003C\u002Fstrong>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">Mobileye Drive – Mobileye’s self-driving system – combines Mobileye’s industry-leading technologies, including \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Frem\u002F\" target=\"_blank\" rel=\"noopener\">Road Experience Management™\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\">, the company’s proprietary approach to mapping that leverages crowdsourced data from mass-market advanced driver-assistance systems to build AV maps on short notice; the \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" target=\"_blank\" rel=\"noopener\">Responsibility-Sensitive Safety (RSS)\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> driving policy that implements a mathematical model to enhance safety through improved adaption to unique driving environments; and \u003C\u002Fspan>\u003Ca style=\"background-color: #ffffff; color: #0068b5;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Ftrue-redundancy\u002F\" target=\"_blank\" rel=\"noopener\">True Redundancy,\u003C\u002Fa>\u003Cspan style=\"background-color: #ffffff; color: #262626;\"> which combines two independent perception sub-systems powered by cameras and radar-lidar, with each alone capable of developing full models and ultimately supporting full end-to-end autonomous capabilities.\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye, an Intel Company, is leading the mobility revolution with its autonomous driving and driver-assist technologies, harnessing world-renowned expertise in computer vision, machine learning, mapping and data analysis. Our technology enables self-driving vehicles and mobility solutions, powers industry-leading advanced driver-assistance systems and delivers valuable intelligence to optimize mobility infrastructure. Mobileye pioneered such groundbreaking technologies as True Redundancy™ sensing, REM™ crowdsourced mapping, and Responsibility Sensitive Safety (RSS) technologies that are driving the ADAS and AV fields toward the future of mobility. For more information: \u003Ca style=\"color: #0068b5; background-color: transparent;\" href=\"https:\u002F\u002Fwww.mobileye.com\u002F\" target=\"_blank\" rel=\"noopener\">www.mobileye.com\u003C\u002Fa>.\u003C\u002Fp>","2022-04-12T07:00:00.000Z",[99,21],{"id":801,"type":100,"url":802,"title":803,"description":804,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":804,"image":805,"img_alt":804,"content":806,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":136,"publish_date":807,"tags":808},138,"zeekr-mobileye-working-together","CES: Mobileye, Zeekr Collaborate on Consumer AV","Together, Mobileye and Zeekr aim to deliver the world’s first consumer autonomous vehicle with L4 capabilities by 2024.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F47789c8048ca30177d73a102a43886c2_1666086631415.png","\u003Cp>\u003Cem>This news content was originally published on the Intel Corporation Newsroom.\u003C\u002Fem>\u003C\u002Fp>\u003Cp>LAS VEGAS, Jan. 4, 2022 — Mobileye, an Intel company, and Zeekr, the global premium electric mobility technology brand from Geely Holding Group, today announced plans to expand their strategic technology partnership with the goal of developing a new all-electric consumer vehicle with \u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcommon\u002Ffiles\u002FMobileye-Drive-Fact-Sheet-675839.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">Level 4 (L4) capabilities\u003C\u002Fa>.\u003C\u002Fp>\u003Cp>The planned autonomous vehicle (AV) will be powered by six EyeQ®5 system-on-chips to process Mobileye True Redundancy™ sensing, Responsibility-Sensitive Safety (RSS)-based driving policy and a new open collaboration model on Road Experience Management™ (REM™) mapping technology. The vehicle will utilize Geely SEA architecture’s redundant braking, steering and power, under an “open EyeQ” concept that allows efficient integration with Zeekr software technologies. In addition, Mobileye will enhance its China-related research and development capabilities, establishing a local data center and enhancing its local teams to support its rapidly growing China activities.\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>“The broadening scope of our partnership reflects just how closely Mobileye and Zeekr are aligned on the vision for future mobility,” said Prof. Amnon Shashua, Mobileye president and chief executive officer. “Zeekr’s confidence in Mobileye as a technology partner demonstrates our ability to execute toward joint goals and further solidify our industry leadership.”  \u003C\u002Fp>\u003Cp>With an anticipated debut in China in 2024, the new all-electric Zeekr vehicle is expected to be the world’s first consumer AV with L4 autonomous capability. Built using \u003Ca href=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fcommon\u002Ffiles\u002FMobileye-Drive-Fact-Sheet-675839.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">Mobileye Drive™\u003C\u002Fa> technology, together with the open SEA architecture, and expanding on Zeekr’s existing models, this new vehicle is expected to eventually roll out across global markets.\u003C\u002Fp>\u003Cp>Mobileye and Zeekr’s new collaboration expands on the companies’ long-term strategic technology partnership, which includes the development of advanced ADAS (advanced driver-assistance systems) with enhanced capabilities for a variety of Zeekr models. The joint efforts are supported by open collaboration with technologies including REM, as Mobileye and Zeekr work toward achieving a safer and more sophisticated future on the roads.  \u003C\u002Fp>\u003Cp>“Mobileye has been a strategic partner to our mission of delivering lifestyle vehicles fit for a more sustainable and autonomous future of transportation,” said Andy An, CEO of Zeekr Intelligent Technology. “Our partnership supports Zeekr and Mobileye’s shared ambitions for leading the global ADAS and AV industry. Zeekr welcomes open collaboration that enables the integration of technological expertise to create a more sophisticated autonomous mobility experience for our customers.”\u003C\u002Fp>\u003Cp>\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Mobileye is a global leader in the development of computer vision and machine learning, data analysis, localization and mapping for Advanced Driver Assistance Systems and autonomous driving. Mobileye’s technology helps keep passengers safer on the road, reduces the risks of traffic accidents, saves lives and has the potential to revolutionize the driving experience by enabling autonomous driving. Mobileye’s proprietary software algorithms and EyeQ® chips perform detailed interpretations of the visual field in order to anticipate possible collisions with other vehicles, pedestrians, cyclists, animals, debris and other obstacles. Mobileye’s products are also able to detect roadway markings such as lanes, road boundaries, barriers and similar items; identify and read traffic signs, directional signs and traffic lights; create a Mobileye Roadbook™ of localized drivable paths and visual landmarks using REM™, and provide mapping for autonomous driving.\u003C\u002Fp>\u003Cp>\u003Cstrong>About ZEEKR\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Zeekr is the global premium electric mobility technology brand from Geely Holding Group. Zeekr aims to create a fully integrated user ecosystem with innovation as standard. The brand utilizes Sustainable Experience Architecture (SEA) and includes its own battery technologies, battery management systems, electric motor technologies and electric vehicle supply chain. Zeekr’s value is equality, diversity, and sustainability. Its ambition is to become a true mobility solution’s provider. Zeekr began delivery of its first product, Zeekr 001, in October 2021. It will launch at least two new model offerings each year to satisfy the rapidly expanding global EV industry. For more information regarding Zeekr, please refer to the official website at \u003Ca href=\"http:\u002F\u002Fwww.zgh.com\u002F\" rel=\"noopener noreferrer\" target=\"_blank\">https:\u002F\u002Fzeekrlife.com\u002F\u003C\u002Fa>\u003C\u002Fp>\u003Cp>\u003Cstrong>Forward-looking statements:\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>Statements in this press release that refer to future plans and expectations are forward-looking statements that involve a number of risks and uncertainties. Words such as “anticipates,” “expects,” “intends,” “goals,” “plans,” “believes,” “seeks,” “estimates,” “continues,” “may,” “will,” “would,” “should,” “could,” and variations of such words and similar expressions are intended to identify such forward-looking statements. Statements that refer to or are based on estimates, forecasts, projections, uncertain events or assumptions, including statements relating to future products and technology and the availability and benefits of such products and technology, expectations regarding customers, market opportunity, and anticipated trends in our businesses or the markets relevant to them, also identify forward-looking statements. Such statements are based on current expectations and involve many risks and uncertainties that could cause actual results to differ materially from those expressed or implied in these forward-looking statements. Important factors that could cause actual results to differ materially are set forth in Intel’s SEC filings, including the company’s most recent reports on Forms 10-K and 10-Q, which may be obtained by visiting our Investor Relations website at www.intc.com or the SEC’s website at www.sec.gov. Intel does not undertake, and expressly disclaims any duty to update any statement made in this press release, whether as a result of new information, new developments or otherwise, except to the extent that disclosure may be required by law.\u003C\u002Fp>","2022-01-04T15:00:00.000Z",[21,99],{"id":810,"type":100,"url":811,"title":812,"description":813,"primary_tag":20,"author_name":136,"is_hidden":96,"lang":132,"meta_description":813,"image":814,"img_alt":813,"content":815,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":136,"publish_date":816,"tags":817},158,"mobileye-ces-2022-tech-news","New Mobileye EyeQ Ultra will Enable Consumer AVs","Single-package design will deliver industry’s leanest, most performance-power efficient SoC for fully autonomous vehicles.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7c1fa9c5ea5f33d9ada1c5a32c390ea4_1666087048027.png","\u003Cp>\u003Cem>This news content was originally published on the Intel Corporation Newsroom.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>\u003Cstrong>NEWS HIGHLIGHTS\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cul>\n\u003Cli>Mobileye introduces EyeQ® Ultra™ – a single package AV-on-chip super-computer that is purpose-built for end-to-end autonomous driving.\u003C\u002Fli>\n\u003Cli>Proven Mobileye EyeQ® architecture underpins EyeQ Ultra, maximizing performance and efficiency at 176 TOPS (tera operations per second).\u003C\u002Fli>\n\u003Cli>First silicon for the EyeQ Ultra is expected in late 2023 with full automotive-grade production in 2025.\u003C\u002Fli>\n\u003Cli>Mobileye also introduces the next-generation EyeQ system-on-chip (SoC) for advanced driver-assistance systems (ADAS): EyeQ6L and EyeQ6H.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>LAS VEGAS, Jan. 4, 2022 – Mobileye today introduced the EyeQ® Ultra™, the company’s most advanced, highest performing system-on-chip (SoC) purpose-built for autonomous driving. As unveiled during CES 2022, EyeQ Ultra maximizes both effectiveness and efficiency at only 176 TOPS, making it the industry’s leanest autonomous vehicle (AV) chip. This efficiently designed SoC builds on seven generations of proven EyeQ architecture to deliver exactly the power and performance needed for AVs, which are all but certain to be all-electric vehicles.\u003C\u002Fp>\n\u003Cp>First silicon for the EyeQ Ultra SoC is expected at the end of 2023, with full automotive-grade production in 2025.  \u003C\u002Fp>\n\u003Cp>“Consumer AV is the end game for the industry,” said Prof. Amnon Shashua, Mobileye president and chief executive officer. “By developing the entire self-driving solution – from hardware and software to mapping and service models – Mobileye has a unique perspective into the exact requirements for the self-driving system that enables us to reach the performance-and-cost optimization that will make consumer AVs a reality.” \u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>Mobileye designed the EyeQ Ultra after having first built an AV to understand exactly what a self-driving vehicle needs to operate at a very high meantime between failures. This approach enables the optimum balance of performance across different accelerators and general-purpose processors in an extremely efficient power-performance envelope.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Delivering Unmatched Cost-to-Performance\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Marking a leap in the evolution of the EyeQ family of SoCs, EyeQ Ultra packs the performance of 10 EyeQ5s in a single package. Leveraging 5 nanometer process technology, EyeQ Ultra can handle all the needs and applications of Level 4 (L4) autonomous driving without the power consumption and costs related to integrating multiple SoCs together. Like its EyeQ predecessors, EyeQ Ultra has been engineered in tandem with Mobileye software, enabling extreme power efficiency with zero performance sacrifices.\u003C\u002Fp>\n\u003Cp>EyeQ Ultra utilizes an array of four classes of proprietary accelerators, each built for a specific task. These accelerators are paired with additional CPU cores, ISPs and GPUs in a highly efficient solution capable of processing input from two sensing subsystems – one camera-only system and the other radar and lidar combined – as well as the vehicle’s central computing system, the high-definition map and driving policy software. At a mere 176 TOPS, the EyeQ Ultra is much more efficient than other AV solutions, delivering the necessary performance and price-point required for consumer-level AVs.\u003C\u002Fp>\n\u003Cp>By optimizing for efficiency, EyeQ Ultra unlocks the AV potential for safer roads and reduced congestion for consumers.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evolution of the EyeQ Architecture\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>The introduction of EyeQ Ultra comes at the same time as two new EyeQ SoCs for ADAS – the EyeQ6L and EyeQ6H – and follows the shipment of Mobileye’s \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002F100-million-eyeq-chips\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">100 millionth EyeQ\u003C\u002Fa> SoC late last year. First introduced in 2004, Mobileye’s EyeQ transformed the ADAS market by proving that cost-effective camera sensors processed by Mobileye’s purpose-built technology were capable of preventing and mitigating collisions. The innovation of EyeQ helped make roadway safety technology more accessible, bringing features including forward-collision warning, lane departure warning and blind spot detection to millions of drivers around the world.\u003C\u002Fp>\n\u003Cp>Mobileye’s proven EyeQ architecture lays the foundation for EyeQ Ultra. Designed to make consumer AVs accessible, EyeQ Ultra fills a void in the automotive market as the EyeQ family of SoCs has done before it. As an extension of the EyeQ family, EyeQ Ultra will also be informed by Mobileye’s Road Experience Management™ (REM) mapping technology. Gathered via millions of vehicles on the road already equipped with Mobileye, REM captures packages of road data to create the Mobileye Roadbook™, which is accessed via the cloud to provide, in real time, up-to-date information on the drivable paths ahead. \u003C\u002Fp>\n\u003Cp>\u003Cstrong>Two New EyeQ SoCs for Next-Generation ADAS\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>The EyeQ6L will be the successor to the EyeQ4 SoC in a package that is just 55 percent the size of the EyeQ4. This one-box windshield solution delivers more deep-learning TOPS at ultra-low power for highly efficient entry and premium (L2) ADAS. It began sampling last year and is due to reach start of production by the middle of 2023.\u003C\u002Fp>\n\u003Cp>The EyeQ6H will support premium ADAS or partial AV capabilities with full surround. It is equivalent to two EyeQ5 SoCs in terms of computing power but more importantly supports visualization and performs better under heavy artificial intelligence workloads. This centralized solution will provide all ADAS L2+ functionalities, multi-camera processing (including parking cameras), and will host third-party apps such as parking visualization and driver monitoring. This most advanced ADAS SoC in the EyeQ family will begin sampling this year and is due to begin production by the end of 2024.\u003C\u002Fp>\n\u003Cp>Both EyeQ6 SoCs will be manufactured on 7nm process technology.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>More Context\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>As Mobileye continues to execute its plan to enable autonomous driving, the versatility and scalability of the company’s portfolio comes into view. Mobileye recently shipped its \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002F100-million-eyeq-chips\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">100 millionth EyeQ SoC\u003C\u002Fa>, unveiled its production robotaxi, and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fpress-kit\u002Fpress-kit-mobileye-new-york-city\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">scaled its autonomous vehicle testing\u003C\u002Fa> across multiple cities around the world including in the U.S., Europe and Asia.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>About Mobileye\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye is leading the mobility revolution with its autonomous driving and driver-assist technologies, harnessing world-renowned expertise in computer vision, machine learning, mapping and data analysis. Our technology enables self-driving vehicles and mobility solutions, powers industry-leading advanced driver-assistance systems and delivers valuable intelligence to optimize mobility infrastructure. Mobileye pioneered such groundbreaking technologies as True Redundancy™ sensing, REM™ crowdsourced mapping, and Responsibility Sensitive Safety (RSS) technologies that are driving the ADAS and AV fields toward the future of mobility.\u003C\u002Fp>\n\u003Cp>For more information: \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002F\" target=\"_blank\" rel=\"noopener\">www.mobileye.com\u003C\u002Fa>.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Forward-Looking Statements\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Statements in this press release that refer to future plans and expectations are forward-looking statements that involve a number of risks and uncertainties. Words such as “anticipates,” “expects,” “intends,” “goals,” “plans,” “believes,” “seeks,” “estimates,” “continues,” “may,” “will,” “would,” “should,” “could,” and variations of such words and similar expressions are intended to identify such forward-looking statements. Statements that refer to or are based on estimates, forecasts, projections, uncertain events or assumptions, including statements relating to future products and technology and the availability and benefits of such products and technology, expectations regarding customers, market opportunity, and anticipated trends in our businesses or the markets relevant to them, also identify forward-looking statements. Such statements are based on current expectations and involve many risks and uncertainties that could cause actual results to differ materially from those expressed or implied in these forward-looking statements. Important factors that could cause actual results to differ materially are set forth in Intel’s SEC filings, including the company’s most recent reports on Forms 10-K and 10-Q, which may be obtained by visiting our Investor Relations website at www.intc.com or the SEC’s website at www.sec.gov. Intel does not undertake, and expressly disclaims any duty, to update any statement made in this press release, whether as a result of new information, new developments or otherwise, except to the extent that disclosure may be required by law.\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>\n\u003Cp>[**]gallery:mobileye-ces-2022-tech-news-gallery-1[**]\u003C\u002Fp>","2022-01-04T08:00:00.000Z",[21,99],{"id":819,"type":100,"url":820,"title":821,"description":822,"primary_tag":98,"author_name":136,"is_hidden":96,"lang":132,"meta_description":822,"image":823,"img_alt":824,"content":825,"download_doc":136,"download_title":136,"download_btn":136,"webinar_video":136,"thumbnail":136,"is_gated":136,"featured":136,"publish_date":826,"tags":827},139,"udelv-unveils-autonomous-cab-less-transporter","CES: Udelv Unveils Mobileye-Powered AV Transporter","The autonomous, electric delivery vehicle will help solve two challenges: a shortage of drivers and fleet electrification.","https:\u002F\u002Fstatic.mobileye.com\u002Fdev\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F99b4ba3c8b8edab1262fc170ae397979_1663142139761.jpg","Udelv  aims to have 50,000 units of the Transporter, driven by Mobileye, on public roads by 2028.","\u003Cp>\u003Cem>This news content was originally published on the Intel Corporation Newsroom.\u003C\u002Fem>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>​Today, Udelv unveiled its Transporter – the company’s next-generation autonomous delivery vehicle driven by Mobileye Drive™ – in advance of this week’s International Consumer Electronics Show 2022 in Las Vegas. The cab-less Transporter is designed for commercial delivery fleets and is expected to help solve two of the most pressing challenges facing commercial fleets: the current shortage of drivers and the coming electrification of fleets.\u003C\u002Fp>\u003Cp>The Mobileye Drive self-driving system is powered by the Mobileye EyeQ® 5 system-on-chip for automotive applications and a robust suite of cameras, lidars and radars. To enable Udelv to rapidly deploy the Transporter at scale, the company has also integrated Mobileye’s Road Experience Management™,  a crowdsourced, continuously updated map of the world that digitizes what autonomous vehicles need to navigate.\u003C\u002Fp>\u003Cp>The Transporter features a patented cargo space that is secure, automated, hot-swappable and modular. It is specifically designed for autonomous delivery and can carry up to 2,000 pounds of cargo and make up to 80 stops per run. It is made to deliver nearly anything from convenience goods, e-commerce packages and groceries to auto parts, electronics and medical supplies for B2B and B2C applications.\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>[**]gallery:udelv-unveils-autonomous-cab-less-transporter-gallery-1[**]\u003C\u002Fp>","2022-01-03T13:00:00.000Z",[21,99],1784714290254]