[{"data":1,"prerenderedAt":299},["ShallowReactive",2],{"tags-av-safety":3,"tag-posts-av-safety":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",[126,140,150,160,170,180,190,200,210,220,230,240,250,260,270,280,290],{"id":127,"type":128,"url":129,"title":130,"description":131,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":131,"image":134,"img_alt":135,"content":136,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":138,"tags":139},323,"blog","tüv-süd-certifies-mobileyes-av-safety-approach-for-sae-level-4","TÜV南德认证 Mobileye 面向 SAE L4 级自动驾驶系统的安全方法","2026年3月，全球领先的独立认证机构之一TÜV南德（TÜV SÜD），正式对Mobileye面向SAE L4级自动驾驶系统的安全管理系统（SMS）出具推荐认可意见。","","en","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F38a5a6e889318030bade44f19b26f2d8_1777542826666.jpg","本文将解析TÜV南德如何开展自动驾驶安全评估，以及Mobileye安全管理系统如何满足SAE L4级自动驾驶系统与欧盟落地应用规范。","\u003Cp>在乘员、道路使用者及全行业层面建立自动驾驶安全公信力，是实现自动驾驶规模化落地的必经之路。而获取独立第三方认证认可，是构建安全公信力的核心环节。\u003C\u002Fp>\n\u003Cp>2026年3月，独立认证机构\u003Ca href=\"https:\u002F\u002Fwww.tuvsud.com\u002Fen\">TÜV南德\u003C\u002Fa>正式认可推荐适用于\u003Ca href=\"https:\u002F\u002Fwww.sae.org\u002Fnews\u002Fblog\u002Fsae-levels-driving-automation-clarity-refinements\">SAE L4级自动驾驶系统\u003C\u002Fa>的Mobileye安全管理系统。该认可结论基于对Mobileye安全管理系统的独立评估，标志着在满足自动驾驶大规模商业化落地标准方面迈出重要一步。\u003C\u002Fp>\n\u003Ch3>TÜV南德机构简介\u003C\u002Fh3>\n\u003Cp>TÜV南德是全球性测试、检验与认证机构，致力于保障各类产品及系统契合安全与法规标准。该机构业务覆盖多个行业，包括汽车领域，负责评估高级驾驶辅助系统（ADAS）与自动驾驶技术，此类技术在日常道路安全中的作用正日益凸显。\u003C\u002Fp>\n\u003Cp>对于主机厂与科技供应商而言，TÜV南德独立于研发流程之外，是客观、可信、中立的技术认证主体。其出具的认证，代表相关技术在功能安全、感知系统、网络安全、软件升级等核心维度契合行业主流标准。\u003C\u002Fp>\n\u003Cp>实操层面，上述标准不仅保障自动驾驶系统设计运行安全，同时可覆盖极端场景、筑牢网络安全防线、适配持续迭代的法规要求，为自动驾驶安全规模化落地提供支撑。\u003C\u002Fp>\n\u003Ch3>Mobileye 如何满足TÜV南德标准？\u003C\u002Fh3>\n\u003Cp>Mobileye将安全管理系统纳入SAE分级自动驾驶平台研发体系，经TÜV南德审核人员评审后，获得系统符合性审核报告的正式推荐，证明其安全管理系统契合欧盟2022\u002F1426法规相关要求。\u003C\u002Fp>\n\u003Cp>本次审核历时一年，对Mobileye全球多地自动驾驶研发、测试及落地全流程的作业规范、管理制度、安全权责组织架构进行了详尽核查。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F5a3da6349508ef9df33d0f61d277dfac_1777543320294.jpg\" alt=\"\" width=\"1200\" height=\"690\" \u002F>\u003C\u002Fp>\n\u003Ch3>TÜV南德认证的行业意义\u003C\u002Fh3>\n\u003Cp>满足区域法规标准，是自动驾驶从限定场景、地理围栏场景走向真实道路商用落地的关键。对Mobileye旗舰自动驾驶平台\u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fsolutions\u002Fdrive\u002F\">Mobileye Drive™\u003C\u002Fa>而言，持续对标各类行业标准，为其获得监管审批、实现大规模商业化部署创造更清晰的路径。\u003C\u002Fp>\n\u003Cp>Mobileye荣获此项认证，进一步彰显在自动驾驶与高级驾驶辅助领域的安全性承诺，也印证其面向商业部署的可量产自动驾驶系统的成熟度。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>",null,"2026-05-06T07:00:00.000Z",[27],{"id":141,"type":128,"url":142,"title":143,"description":144,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":144,"image":145,"img_alt":146,"content":147,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":148,"tags":149},310,"the-shift-towards-centralized-intelligence","集中式智能架构时代来临","当前行业面临的挑战不仅在于软件迭代，更在于确保安全关键驾驶功能万无一失。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F42e83d11a5ca50726f0fc0c8d9e1e8a6_1767170943828.jpg","车载平台嵌入式软件的规模会随着时间推移持续扩张，代码量已超过1亿行。","\u003Cp>随着行业不断整合算力资源，并致力于构建软件定义的驾乘体验，核心挑战已不仅在于软件更新本身，更在于确保安全关键的驾驶功能始终可靠无虞。如今，软件能力正日益成为车辆竞争力的核心，即便车辆驶出工厂，也能通过持续的软件更新不断解锁新功能，带来新的盈利增长机会。\u003C\u002Fp>\n\u003Cp>这一演进趋势可从车载平台软件规模的持续扩张中直观体现。如今，许多现代车辆的软件代码量\u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Findustries\u002Fautomotive-and-assembly\u002Four-insights\u002Fwinning-the-automotive-software-development-race\">已突破一亿行\u003C\u002Fa>。为了支撑如此庞大的代码规模，必须依赖新一代硬件平台——具备强大算力的系统集成芯片（SoC）域级处理器，能够同时支持高级计算、人工智能（AI）处理以及云端互联。此类计算系统可确保车辆具备持续进化能力，在保障性能与可靠性的前提下，高效运行复杂的安全功能，并为座舱应用场景提供强大算力支持。\u003C\u002Fp>\n\u003Cp>这一技术突破依赖深厚的专业积累，只有具备高算力和安全基础设施能力的企业，才能帮助车企整合控制架构、简化系统复杂度，并稳步推进新一代智能汽车的规模化落地。 \u003C\u002Fp>\n\u003Cp>\u003Cstrong>车企为何竞相推进ECU整合？\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>数十年来，车辆一直依赖多家供应商提供的分布式电子控制单元（ECU），一辆车往往配备上百个独立 ECU，各自承担特定功能。这种架构不仅成本高、结构复杂，而且难以实现高效的软件更新。为应对日益增长的系统复杂度，行业正通过架构整合，将数量更少、性能更强的域控制器作为核心，并通过高带宽网关实现跨域功能的协同与互联。\u003C\u002Fp>\n\u003Cp>这种整合模式以高性能系统集成芯片（SoC）为核心，重构车辆架构。单颗芯片即可承载多项软件功能及域级工作负载，使不同车型及车辆全生命周期的软件管理更加简化。借助灵活的硬件架构和在线升级（OTA）能力，车企能够在车辆量产后持续推送新功能、优化性能，并支持订阅服务的推出。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\">这一转型正在重塑供应链的竞争格局。芯片厂商与软件供应商纷纷发力，竞相打造既可靠又符合安全标准的平台，以满足快速数字化车队的需求。在当前环境下，兼具高计算性能与经验证的安全隔离机制的架构，可能成为决定车企能否在规模化量产中实现软件驱动目标的关键因素。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3fbf248390951761708a504d498c4b7f_1767170985038.jpg\" alt=\"\" width=\"1200\" height=\"574\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>汽车电子电气（E\u002FE）架构整合的局限性\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>计算架构整合也带来了新的挑战：安全关键系统与非安全应用之间的界限日益模糊。将所有功能集中在单一平台的架构方案，可能带来性能瓶颈和验证不足的风险。在极端情况下，甚至可能导致车辆出厂后的软件更新意外影响制动或感知等核心安全功能。\u003C\u002Fp>\n\u003Cp>车辆集中式车载计算架构并非唯一路径。Mobileye 采用 “整合与隔离” 并行的技术路线，通过多域控制器（MDC）架构连接 EyeQ™ 系列芯片，在实现算力资源整合的同时，确保安全关键驾驶功能与通用计算负载之间保持清晰隔离。该设计能够在通过 OTA 更新新增软件功能的同时，持续保障驾驶决策的可验证性与确定性。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-contrast=\"auto\">同时，Mobileye 系统具备全域整合能力，在支撑各类应用和云端互联的同时，始终坚守安全关键ADAS的安全底线。\u003C\u002Fspan>\u003Cspan data-ccp-props=\"{}\"> \u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>软件层持续迭代，车企如何坚守经验证的安全性？\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>车企对所交付车辆的安全性负全责。而软件开始迭代之时，新的挑战也随之而来：在车辆全生命周期中不断新增功能、更新软件与应用，最初用于保障安全性能的验证结果可能会发生意外变化。核心在于构建一套“无干扰运行”系统，确保在软件持续更新过程中，安全关键任务始终不受影响。\u003C\u002Fp>\n\u003Cp>无论系统新增多少软件层，经验证的安全性都必须保持完整，且不能依赖共享算力资源或承受不可预测的资源竞争。这正是 Mobileye 架构的核心设计理念：在安全关键驾驶功能与车辆其他功能域之间建立严格隔离机制。通过这种隔离设计，即便周边软件持续迭代，核心 ADAS 或自动驾驶任务仍能保持完全经验证的状态和行为一致性。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\">Mobileye 的架构理念在关键环节保持开放性，同时在核心安全领域坚守隔离性。这一点在其 \u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fopinion\u002Fmobileye-dxp-as-a-novel-approach\u002F\">DXP\u003C\u002Fa> 平台上表现尤为突出：车企可以在该平台上集成自有中间件、OTA 系统及面向用户的应用，同时依托 Mobileye 经实战验证的底层技术，确保车辆在各类工况下都能安全完成感知、决策与执行。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>展望未来：安全性与自动驾驶功能并重\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>通过将经验证的驾驶智能与灵活的整合能力相结合，Mobileye 帮助车企在不牺牲道路安全核心的前提下，自信地推动数字化愿景的规模化落地。随着行业向更智能、更互联、更自主的出行方向演进，Mobileye 正推动安全能力与技术演进同步迭代。未来的自动驾驶不仅将具备高度智能，更将以安全为核心定义行业标准。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-12-31T08:00:00.000Z",[27],{"id":151,"type":128,"url":152,"title":153,"description":154,"primary_tag":20,"author_name":132,"is_hidden":96,"lang":133,"meta_description":154,"image":155,"img_alt":156,"content":157,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":158,"tags":159},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":161,"type":128,"url":162,"title":163,"description":164,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":164,"image":165,"img_alt":166,"content":167,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":168,"tags":169},300,"compound-ai-the-framework-powering-scalable-autonomy","复合人工智能：赋能可扩展驾驶自动化的技术架构","人工智能（AI）革命方兴未艾，其对驾驶领域的影响尤为深远。随着AI系统能力不断提升，其底层技术已成为竞争的核心焦点。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fb5767eb911fc0460e9110b1c81ec69ef_1753943068689.jpg","驾驶自动化可明确分解为感知、规划、执行等模块，每个模块对应一个或多个专用模型。","\u003Cp>在AI领域，Mobileye 独辟蹊径，植根于系统设计、现实世界验证与规模化。这一理念体现在我们的“复合人工智能（Compound AI）”架构中：融合灵活的端到端学习与专用算法，实现安全、可扩展的部署。它不单是架构体系，更是一套指导框架，为当前的高级辅助驾驶系统和更高等级驾驶自动化解决方案提供核心驱动力。\u003C\u002Fp>\n\u003Cp>本文将解析 Mobileye 复合人工智能架构的内涵及其如何奠定可扩展驾驶自动化的基石。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>何为面向高等级驾驶自动化的复合人工智能架构？\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>复合人工智能架构是指集成多个专用化、定制化的AI模型协同工作，以解决那些单一模型难以高效应对的复杂任务。与依赖单一通用型模型的方式不同，复合人工智能采用模块化、分层的架构。每个模块都针对特定子任务进行优化，系统通过协调各模块的输出，生成具连贯性且智能化的结果。\u003C\u002Fp>\n\u003Cp>目前，许多高等级驾驶自动化系统仍依赖于单一的端到端模型，将驾驶自动化视为一个庞大的学习任务。这种方法试图通过视觉输入学习全部内容，从而构建驾驶策略，即所谓的“从光子到控制”。\u003C\u002Fp>\n\u003Cp>然而，越来越多的尖端AI成果出自复合系统。此类架构由多个专用模块构成，各司其职。正如\u003Ca href=\"https:\u002F\u002Fbair.berkeley.edu\u002Fblog\u002F2024\u002F02\u002F18\u002Fcompound-ai-systems\u002F\">伯克利人工智能研究所（BAIR）\u003C\u002Fa>所称：“当前最先进的AI成果，正日益由多模块复合系统实现。”\u003C\u002Fp>\n\u003Cp>Mobileye 的复合人工智能架构也遵循相同的理念，将驾驶自动化明确解耦为感知（sensing）、规划（planning）、执行（acting）等模块，每个模块对应一个或多个专用的 AI 模型。\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Mobileye \u003C\u002Fstrong>\u003Cstrong>如何实践复合人工智能？\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>如 Mobileye《\u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fblog\u002Fthe-mobileye-safety-methodology-for-fully-autonomous-driving\u002F\">高等级驾驶自动化系统安全架构\u003C\u002Fa>》所述，实现可扩展驾驶自动化系统所需的安全性与可靠性需要坚实的技术基础。而Mobileye的技术基础在于模块化设计、多源独立感知模态以及多层冗余。\u003C\u002Fp>\n\u003Cp>这是 Mobileye 在开发现实世界 AI 系统时所采取的策略，融合多种技术与专业能力，共同构建现实世界中可扩展部署的关键路径。每一部分在复合人工智能的决策应用中都扮演着至关重要的角色。\u003C\u002Fp>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Wingdings\" data-listid=\"3\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"1\" data-aria-level=\"1\">\n\u003Cp>\u003Cstrong>模块化\u003C\u002Fstrong>：感知、规划、执行等各层均可以独立开发和优化。工程师能够专注于特定驾驶功能，从而实现更高效、灵活的开发和部署。\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Wingdings\" data-listid=\"3\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"2\" data-aria-level=\"1\">\n\u003Cp>\u003Cstrong>冗余\u003C\u002Fstrong>：为了确保在不可预测的环境中依然保持出色表现，Mobileye 集成了多感知模态（摄像头、雷达、激光雷达）、REM™智能路网信息、多样化AI方法及重叠算法层，可保障不确定环境下的性能。这些独立的路径相互强化，提升系统鲁棒性，不仅在常规驾驶条件下表现优异，也能应对边缘情况和复杂场景。\u003C\u002Fp>\n\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cul>\n\u003Cli aria-setsize=\"-1\" data-leveltext=\"\" data-font=\"Wingdings\" data-listid=\"3\" data-list-defn-props=\"{"335552541":1,"335559685":720,"335559991":360,"469769226":"Wingdings","469769242":[9642],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}\" data-aria-posinset=\"3\" data-aria-level=\"1\">\u003Cstrong>抽象化\u003C\u002Fstrong>：Mobileye 在关键环节融入结构化逻辑。RSS™模型开发了无需学习的核心安全原则，REM™则通过智能路网和驾驶智能层，增强实时感知能力。这些抽象层降低了系统的方差，同时保持系统的稳定性和可解释性。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch3>\u003Cstrong>软硬件协同\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Mobileye复合人工智能架构的内部设计体现了灵活性与效率之间的精妙平衡。Mobileye专为高等级驾驶自动化系统设计的EyeQ™6 High芯片，内置五个专用模块；每个模块都在灵活性与专用性之间实现了不同的平衡：双CPU（MPC和MIPS）提供灵活算力，XNN加速器实现高效目标性能；VMP与PMA加速器弥合灵活性与专用性之间的差距，使系统能够动态适配多元运行需求。\u003C\u002Fp>\n\u003Cp>EyeQ™6 High 芯片算力为34 TOPS (INT8)，但单纯的TOPS指标并不足以衡量其性能，实际应用场景和效率更为重要。在实际驾驶负载下，该芯片能够以超过每秒1000帧的速度处理像素标注神经网络，充分展示了智能架构在实际中的强大表现。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"335559738":240,"335559739":240}\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F9ab71dda0ddbbda9ba39001e815b5bf2_1753942887727.png\" alt=\"\" width=\"1200\" height=\"673\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>为道路而生\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>复合人工智能作为一种架构体系，也承载着我们持续构建以安全、效率与可扩展性为核心的解决方案的使命。它构成了从高级驾驶辅助系统（ADAS）到高等级驾驶自动化平台（如Mobileye Chauffeur™和Mobileye Drive™）的技术基础，这些平台支持视觉脱离乃至完全自动驾驶的出行方式。\u003C\u002Fp>\n\u003Cp>随着AI持续重塑出行，驾驶自动化的可行性已不是问题所在。行业焦点已转向如何使其具备可扩展性、安全性和现实可行性。一种基于实际性能、分层化、模块化且严谨的方法论 - 复合人工智能架构，就是Mobileye交出的答卷。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-07-31T07:00:00.000Z",[27],{"id":171,"type":128,"url":172,"title":173,"description":174,"primary_tag":63,"author_name":132,"is_hidden":96,"lang":133,"meta_description":174,"image":175,"img_alt":176,"content":177,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":178,"tags":179},295,"a-new-balancing-act-for-automakers","车企的全新平衡之道","随着汽车日益由软件定义，车企正重新思考从产品路线图到核心定位等方方面面。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fda823c81d6e4b65ed464043cb532d556_1748340481466.jpg","目标是在不牺牲驾驶体验关键要素的前提下，采取务实的发展策略。","\u003Cp>汽车行业正快速引入更复杂的出行方案系统。传统车企的运营通常涵盖整车生产、深厚的机械工程积累、对多元供应商零部件的高效集成，以及复杂供应链网络的管理。但在过去五到七年间，整个行业已开始从机械时代迈向数字时代，传统车企正积极应对这一转变，拓展其作为软件公司的角色。 \u003C\u002Fp>\n\u003Cp>这一转变既带来挑战，也孕育机遇，关键在于怎么看待。这些挑战包括：车企如何转型为科技驱动的汽车制造商，如何在机械系统与数字能力之间找到平衡点，以及如何推动高等级驾驶自动化汽车的大规模普及。\u003C\u002Fp>\n\u003Ch3>汽车制造商的身份演变\u003C\u002Fh3>\n\u003Cp>消费者的购车决策越来越看重\u003Ca href=\"https:\u002F\u002Fwww.spglobal.com\u002Fautomotive-insights\u002Fen\u002Fblogs\u002F2024\u002F12\u002Frisks-and-rewards-of-automakers-on-software-defined-vehicles?utm_source=chatgpt.com\">软件\u003C\u002Fa>和驾驶自动化功能。因此，无论是通过内部自研还是战略合作，传统汽车领域的主要参与者正越来越多地涉足人工智能和大数据等先进技术。\u003C\u002Fp>\n\u003Cp>那些早期时未将自身定位为软件型企业的车企，正在规划全新的产品路线图。但如今，制定十年产品规划充满挑战，涉及诸多新问题：应该自研吗？未来的合作伙伴关系会是何种形态？哪些是关键组件？实施的复杂度有多高？无论如何，传统车企都必将经历转型，而最大的挑战在于：如何在学习过程中理解消费者最看重哪些功能，并据此为品牌做出全面的战略决策。 \u003C\u002Fp>\n\u003Ch3>平衡传统制造与软件开发\u003C\u002Fh3>\n\u003Cp>在软件行业，可能每一两年就会发生一次变化。然而，这并非汽车行业的常态。尽管汽车已成为新技术的落地前沿（且变革速度确实在加快），但必须认识到：汽车行业有其自身合理的发展节奏。\u003C\u002Fp>\n\u003Cp>这里涉及安全性、操控性和可靠性等重要考量因素，不是为技术而技术，而是要打造真正实用的系统，高效、安全、舒适地将人们从A点送达B点。目标在于采取平衡、渐进且务实的策略，在将新技术推向市场的同时，绝不牺牲安全性和可靠性，也不损害驾驶体验的其他核心要素。 \u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{"201341983":0,"335559739":0,"335559740":276}\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0d59842888bd8ff01dbde2bb996da919_1748341765006.jpg\" alt=\"\" width=\"1200\" height=\"565\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Ch3>高等级驾驶自动化如何走向主流\u003C\u002Fh3>\n\u003Cp>放眼当下，高等级驾驶自动化汽车在全球行驶总里程中仍只占极小比例。但技术、商业模式和法规框架已日臻成熟，因此高等级驾驶自动化汽车的大规模普及指日可待。\u003C\u002Fp>\n\u003Cp>近年来，业界更广泛地认识到，真正安全且可扩展的驾驶自动化，不能靠追逐短期热点，而需持之以恒地投入工程创新与软件创新。唯有如此，面向大众市场的驾驶自动化才能真正为消费者和车企创造价值。\u003C\u002Fp>\n\u003Ch3>赢得消费者接纳\u003C\u002Fh3>\n\u003Cp>尽管包括技术专家、供应商、制造商和监管机构在内的幕后力量正在共同努力，全力推动驾驶自动化走向主流，但只有当大量消费者能够真正接受人类无需主动去驾驶的理念时，这场变革才算真正完成。\u003C\u002Fp>\n\u003Cp>随着高速公路上的L2+级（需注视\u002F驾驶员运动脱离）辅助驾驶和L3级（需注视\u002F驾驶员运动脱离）有条件自动驾驶日益普及，一种人机协同的驾驶思维模式正在形成。这种转变在特定区域已提供商业化完全自动驾驶服务的企业和L4级出租\u003Ca href=\"https:\u002F\u002Fwww.mobileyechina.com\u002Fnews\u002Flyft-and-mobileye-team-up-to-enable-autonomous-mobility-at-scale\u002F\">车队\u003C\u002Fa>中同样显而易见。\u003C\u002Fp>\n\u003Ch3>量产产品，而非原型概念\u003C\u002Fh3>\n\u003Cp>得益于多年经验积累，Mobileye在为下一代高级驾驶辅助系统（ADAS）和高等级驾驶自动化汽车开发高性能软件方面拥有深厚专长。依托与头部车企的紧密合作，我们深知如何交付性能可靠、设计精良的先进技术。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2025-05-27T07:00:00.000Z",[27,13,64],{"id":181,"type":128,"url":182,"title":183,"description":184,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":184,"image":185,"img_alt":186,"content":187,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":188,"tags":189},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":191,"type":92,"url":192,"title":193,"description":194,"primary_tag":5,"author_name":132,"is_hidden":96,"lang":133,"meta_description":194,"image":195,"img_alt":196,"content":197,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":198,"tags":199},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":201,"type":128,"url":202,"title":203,"description":204,"primary_tag":5,"author_name":132,"is_hidden":96,"lang":133,"meta_description":204,"image":205,"img_alt":206,"content":207,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":208,"tags":209},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":211,"type":128,"url":212,"title":213,"description":214,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":214,"image":215,"img_alt":216,"content":217,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":218,"tags":219},275,"mobileyes-camera-vision-beyond-what-you-see","Mobileye 摄像头视觉：超越眼前所见","Mobileye 的ADAS解决方案以及其摄像头视觉，助力实现更安全的道路交通。","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F860936e4c2dac83b3ff7e0f6ef066af7_1729509729689.png","Mobileye的不同解决方案平台可由1到13个摄像头组成","\u003Cp>俗语说，眼睛是心灵的窗户。照此说来，摄像头就是通往Mobileye创新技术的门户。从高级驾驶辅助系统（ADAS）到自动驾驶汽车，Mobileye的一切成就都源于我们具有成本效益且可扩展的摄像头，其他传感器以及计算机视觉技术。在本中，我们将探讨Mobileye如何利用这些技术实现更安全的道路交通。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>视觉与自动驾驶的未来\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>摄像头在车身的配置方式、其识别物体的范围以及与Mobileye平台的整合能力，对于开创安全的自动驾驶未来至关重要。考虑到光照或距离等视觉限制因素，Mobileye的摄像头可处理镜头畸变等问题，以帮助驾驶员对道路上的物体做出有效反应。\u003C\u002Fp>\n\u003Cp>Mobileye的不同解决方案平台可由1到13个摄像头组成。这些方案或产品虽然以不同的形式存在，但都有一个共同的目标 - 根据不断变化的路况环境识别并调整驾驶行为。\u003C\u002Fp>\n\u003Cp>凭借我们先进的算法、高性能的硬件和强大的系统大脑--EyeQ™系统集成芯片的支持，我们的解决方案旨在尽可能高效地计算更多数据。换言之，Mobileye的ADAS平台旨在从持续的摄像头输入中提取并标记元素，分析车辆周围的环境，进而基于深度学习技术了解车辆周围的驾驶环境，并提出正确的行驶建议。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\">\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F863a173db5dee3a32376c1a9c77847d5_1729510125253.png\" alt=\"\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>安全标配化\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>随着ADAS安全标配化日益成为汽车生产不可或缺的一部分，未来的道路将带来更安全的驾驶体验，且效果有目共睹。许多报告都强调了驾驶辅助技术对减少道路交通事故具有重大影响。例如，\u003Ca href=\"https:\u002F\u002Fnewsroom.aaa.com\u002F2023\u002F08\u002Fyour-autos-safety-net-the-lifesaving-potential-of-driving-assistance-tech\u002F\">美国汽车协会交通安全基金会（AAA Foundation for Traffic Safety）\u003C\u002Fa>在2023年的一份报告中指出，如果将目前可用的驾驶辅助技术作为标配搭载到所有车辆上，美国将在未来30年内预防3700万起的碰撞事故。这凸显了规模化部署高级驾驶辅助系统的巨大潜力，并强调了未来道路安全性的重要性。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>功能概览\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>Mobileye的高级驾驶辅助系统采用120度800万像素前置摄像头，可确保对各种目标物进行鲁棒性检测和响应。搭载后，驾驶员可以从一系列增强驾驶性能的工具中获益。这些工具包括高级告警系统（AWS）、自动巡航控制系统（ACC）、自动紧急制动（AEB）和车道保持辅助系统，以及车道偏离警告、车道居中（如适用）、交通灯警告系统等。多摄像头配置（如EyeQ™6H芯片与六个摄像头连接，包括前后两个长焦摄像头和四个短距摄像头）则可实现高速公路上“可脱手\u002F需注视”的驾驶体验。\u003C\u002Fp>\n\u003Cp>此外，Mobileye为汽车制造商提供的智能车速辅助系统（ISA）解决方案被公认为首个符合欧盟（EU）最新\u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fmobileye-launches-the-first-camera-only-intelligent-speed-assist-to-meet-new-eu-standards\u002F\">《通用安全法规（GSR）》标准\u003C\u002Fa>的“纯视觉”解决方案。\u003C\u002Fp>\n\u003Cp>\u003Cspan data-ccp-props=\"{}\"> \u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fa6287c9dcde9b68184e9d662880cf40e_1729510161477.png\" alt=\"\" width=\"1518\" height=\"984\" \u002F>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>安全规模化\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>总而言之，配备高级驾驶辅助系统和先进视觉技术的车辆在提高道路安全方面具有巨大的潜力，这一点在Mobileye努力为全球驾驶员提供经济高效、可扩展解决方案的背景下尤为明显。通过利用先进的摄像头视觉和人工智能技术，Mobileye 将引领未来，大幅减少道路交通安全事故，让自动驾驶成为现实。\u003C\u002Fp>\n\u003Cp> \u003C\u002Fp>","2024-10-21T07:00:00.000Z",[13,27],{"id":221,"type":128,"url":222,"title":223,"description":224,"primary_tag":20,"author_name":132,"is_hidden":96,"lang":133,"meta_description":224,"image":225,"img_alt":226,"content":227,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":228,"tags":229},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":231,"type":128,"url":232,"title":233,"description":234,"primary_tag":20,"author_name":132,"is_hidden":96,"lang":133,"meta_description":234,"image":235,"img_alt":236,"content":237,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":238,"tags":239},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":241,"type":128,"url":242,"title":243,"description":244,"primary_tag":20,"author_name":132,"is_hidden":96,"lang":133,"meta_description":244,"image":245,"img_alt":246,"content":247,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":96,"featured":96,"publish_date":248,"tags":249},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":251,"type":100,"url":252,"title":253,"description":254,"primary_tag":137,"author_name":137,"is_hidden":96,"lang":133,"meta_description":254,"image":255,"img_alt":256,"content":257,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":137,"featured":96,"publish_date":258,"tags":259},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":261,"type":128,"url":262,"title":263,"description":264,"primary_tag":12,"author_name":137,"is_hidden":96,"lang":133,"meta_description":264,"image":265,"img_alt":266,"content":267,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":137,"featured":96,"publish_date":268,"tags":269},216,"making-safety-seen-international-women-in-engineering-day","Making Safety Seen on International Women in Engineering Day","Women make vital contributions to a company's growth and culture. Meet some of the women engineers who drive advancements in our products and technologies.","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fd901ba75499d608e388f1e4390e42ca6_1687431455849.jpg","Shira Hirsh and Tomer Hochbaum are two of the many woman engineers making a meaningful professional impact at Mobileye.","\u003Cp>It wasn’t until the Second World War that serious attention was paid to women’s education in technical fields, and women began to enter the male-dominated workforce. In America, Rosie the Riveter became an enduring symbol for the physical and intellectual capabilities of American women engineers. In 2019, women accounted for about 34% of all engineers in Israel. Globally, the proportion of women engineers in 2023 stands at 24% in the United States, 17% in the European Union, 16% in Japan, and 14% in India.\u003C\u002Fp>\n\u003Cp>While stereotypes persist in STEM fields especially, there is a growing number of women who contribute to the necessary growth and culture of the companies which in turn benefit from their talents. At Mobileye, women engineers are making a meaningful impact on our \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fsolutions\u002F\">products\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\">technologies\u003C\u002Fa>.  Here, read about two women who embody the theme of this year’s \u003Ca href=\"https:\u002F\u002Fwww.inwed.org.uk\u002F\">International Women in Engineering Day\u003C\u002Fa>: “make safety seen.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fc03ae56c199365298bda634143e89b61_1687431542718.jpg\" alt=\"Woman engineers like Shira Hirsh and Tomer Hochbaum work alongside men in Mobileye’s various engineering departments.\" width=\"1605\" height=\"1070\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Saving lives \u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>There are numerous factors that contribute to road accidents, with speeding, distractions, and non-adherence to \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\">traffic rules\u003C\u002Fa> ranking among the top five causes. At Mobileye, the core value of saving lives and promoting accessible, sustainable mobility drives the work of our engineers. Among them is Shira Hirsh, a senior principal engineer specializing in deep learning and computer optimization. Her focus is on integrating numerous algorithms into \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\">EyeQ™\u003C\u002Fa> – Mobileye’s proprietary System-on-Chip (SoC) – which aims to ensure an efficient and very quick response time, ultimately leading to a safe and seamless driving experience.\u003C\u002Fp>\n\u003Cp>Since Shira was young, she has always been curious and drawn to problem solving. But before starting her career as an engineer, she faced her own stereotypes about the field.\u003C\u002Fp>\n\u003Cp>“I had this vision that computer engineers spend most of their days in front of a computer, devoid of human interaction, which is the opposite of the social person that I am,” Shira reflects. “But after careful contemplation and great support from my family and friends, I embraced the decision to pursue a degree in computer science.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002Fe76096cc79a4085c11591f80a564e8cf_1687431574825.jpg\" alt=\"Woman engineers are an integral part of the workforce at Mobileye, helping to make our roads safer through technology.\" width=\"1605\" height=\"1070\" \u002F>\u003C\u002Fp>\n\u003Cp>“My choice,” she explains, “was motivated by my passion for problem-solving and the realization that engineering necessitates exceptional social skills for effective collaboration, communication, and understanding people’s needs. My strength in connecting with people is an asset in my field.”\u003C\u002Fp>\n\u003Cp>Together with her expertise in \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmoving-our-machine-learning-to-the-cloud-inspired-innovation\u002F\">machine learning\u003C\u002Fa> and computer optimization, she plays a pivotal role in the development and integration of advanced algorithms, ensuring that Mobileye’s \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fwhat-is-advanced-driver-assistance-system-adas\u002F\">driver-assistance\u003C\u002Fa> technologies deliver the highest level of safety and reliability.\u003C\u002Fp>\n\u003Cp>Like Shira, Mobileye algorithm and machine learning team manager Tomer Hochbaum had the same at-home support to break the gender barrier as a female engineer.\u003C\u002Fp>\n\u003Cp>“Both of my parents are in similar fields, so to focus on math and science was second nature to me,” she explains. “At home, I grew up with a big sister and mother whom I both admire, and I was always told that gender is not a barrier. It helped me overlook the obvious when I arrived at university: that all the teachers and my classmates in my engineering department were male. On top of that, studying did not come easily to me, and I found university to be very difficult. I worked very hard and found myself at Mobileye towards the end of my university experience. Despite managing a team of five, I still don’t see myself as an engineer only – I volunteer a lot, I work with animals. I am a lot of things outside of my work.”\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The pursuit of safety\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>Tomer and Shira’s work at Mobileye aligns perfectly with this year’s theme, “make safety seen”. For Tomer, she and her team strive to improve safety by developing technologies that can outperform human drivers. By accurately detecting objects, their goal is to reduce accidents and create a safer environment for all.  \u003C\u002Fp>\n\u003Cp>For Shira, her cross-project role focuses on accelerating and optimizing algorithms across various domains, including solution-based \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fceo-amnon-shashua-on-the-technological-megashifts-impacting-our-world\u002F\">AI technology\u003C\u002Fa> such as machine and deep learning, computer vision, and model-based approaches on Mobileye's proprietary EyeQ chip. Her team’s main goal is to enhance the algorithms, enabling them to function in real-time and deliver rapid response times for ADAS systems, ensuring utmost safety.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F0c3f1e981a7066c947c2dcabd415f775_1687431615069.jpg\" alt=\"The autonomous vehicle garage at Mobileye is where our self-driving technologies are put to the test in various vehicles.\" width=\"1605\" height=\"1070\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The impact on the world\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>In \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fmobileye-campus-jerusalem-leed-platinum-environmental-rating\u002F\">the office\u003C\u002Fa>, the creative collaboration between \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fwe-are-mobileye-by-kutiman\u002F\">their colleagues\u003C\u002Fa> is precisely what is needed to push through and achieve breakthroughs. Shira explains: “As projects progress and \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fintelligent-speed-assist-general-safety-regulation\u002F\">safety regulations\u003C\u002Fa> become stricter, there are instances where it may appear that we have reached maximum efficiency and cannot fit in even one more needle. However, together with others on the algorithm teams, we consistently conquer the challenge. We discover innovative approaches to reduce cycles and optimize new algorithms, enabling them to fit within our constraints. These efforts often yield results that allow us to continually enhance performance and functionality. “\u003C\u002Fp>\n\u003Cp>“Mobileye is a company that works towards improving safety,“ Tomer highlights. “Everything we do is towards that goal of what’s going to be safer and better for people. Every check is to make sure that our technology can become more accurate than a human.”\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7d4ac1ab1a4ba4f512d5afe8d09e7c18_1687431651240.jpg\" alt=\"Mobileye’s autonomous driving technologies are tested and deployed in vehicles like the Zeekr 001 and Nio ES8.\" width=\"1605\" height=\"1070\" \u002F>\u003C\u002Fp>\n\u003Cp>For Tomer and Shira, improving safety is just one of the many impacts engineers can make in the world. These exemplary women engineers are not limited to the work they do at Mobileye – their expertise allows them to address smaller, yet no-less-significant problems that align with their personal values and passions. Tomer highlights this type of opportunity through her volunteer work with animal adoption where she uses her expertise to identify committed owners and prevent abandonment.\u003C\u002Fp>\n\u003Cp>By playing pivotal roles in the development and integration of advanced algorithms, women engineers, like those we’ve spotlighted here, ensure that Mobileye's driver-assistance technologies deliver unmatched safety and reliability. The road for women engineers may indeed be long, but it's paved with the stories like those of Shira and Tomer who break stereotypes along the way.\u003C\u002Fp>","2023-06-22T07:00:00.000Z",[13,27],{"id":271,"type":128,"url":272,"title":273,"description":274,"primary_tag":15,"author_name":132,"is_hidden":96,"lang":133,"meta_description":274,"image":275,"img_alt":276,"content":277,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":137,"featured":96,"publish_date":278,"tags":279},189,"responsibility-sensitive-safety-unwritten-rules-of-the-road","The Unwritten Rules of the Road, Codified in RSS™","Our drive for autonomous vehicle safety led Mobileye to formulate the Responsibility-Sensitive Safety™ model and share it with the world.\n\n ","https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F7c7cc092c168c2aaa405916a1d7bef4f_1672933384808.png"," Responsibility-Sensitive Safety™ is an open, comprehensive, and verifiable mathematical model for autonomous vehicle safety.","\u003Cp>Picture yourself pulling up at an intersection. The right of way is yours, and the intersection looks clear – but still you proceed cautiously, with your foot covering the brake pedal. And good thing you did, because the other driver didn’t yield, and then a pedestrian you couldn’t see stepped off the curb from behind a parked van.\u003C\u002Fp>\n\u003Cp>Had you simply acted according to what you saw when approaching the intersection and legitimately followed the written rules of the road, you might have collided with one or both of them. But as an experienced driver, you followed your intuition and heeded the unwritten rules of the road as well.\u003C\u002Fp>\n\u003Cp>At Mobileye, we understand that those informal “rules” are no less important than the formal ones, so we’ve codified the former into the \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Fresponsibility-sensitive-safety\u002F\" target=\"_blank\" rel=\"noopener\">Responsibility-Sensitive Safety™\u003C\u002Fa> model – an open, comprehensive, and verifiable mathematical model for \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Ftag\u002Fav-safety\u002F\" target=\"_blank\" rel=\"noopener\">autonomous vehicle safety\u003C\u002Fa>. It’s a formula for enabling self-driving cars to safely share the road with human drivers and a crucial element in the effort to deploy AVs at scale around the world.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F2c4b23d1842f9a42d8bffe01a946e938_1672933725530.png\" alt=\"For autonomous vehicles to interact safely with human-driven vehicles, they need a decision-making framework like RSS.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Why Do We Need an Autonomous Vehicle Safety Model?\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>The Responsibility-Sensitive Safety model (RSS™) is based on the premise that for self-driving technology to be both safe and useful, it must be able to handle not only the majority of everyday driving tasks, but the “edge cases” as well. That is, it must be able to deal with unexpected events in an inherently unpredictable driving environment – at least for as long as autonomous vehicles (AVs) share the road with human drivers.  \u003C\u002Fp>\n\u003Cp>What an AV needs, then, is a set of parameters by which to evaluate all of its decisions. Not simply to control the vehicle’s movements or to strictly abide by traffic laws, but an all-encompassing framework for autonomous vehicle safety allowing the AV to deal with whatever situation might arise – even those we cannot predict. \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Five Rules to Live and Drive By\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>RSS rises to that challenge by codifying the intuitive skills of driving into \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Frss-explained-the-five-rules-for-autonomous-vehicle-safety\u002F\" target=\"_blank\" rel=\"noopener\">five all-encompassing rules\u003C\u002Fa>:\u003Cbr \u002F>1) \u003Cstrong>Do not hit the car in front of you\u003C\u002Fstrong> – based on a mathematical formulation of the “two-second rule” we all learn in driving school.\u003Cbr \u002F>2) \u003Cstrong>Do not cut in recklessly\u003C\u002Fstrong> – similar to the longitudinal safe distance established by Rule #1, but applied here to the lateral distance between vehicles.\u003Cbr \u002F>3) \u003Cstrong>Right of way is given, not taken\u003C\u002Fstrong> – which tells the AV to watch out for other vehicles that may not yield the right of way to it, even when they should.\u003Cbr \u002F>4) \u003Cstrong>Be cautious in areas with limited visibility\u003C\u002Fstrong> – just because the vehicle’s sensors can’t detect a potential hazard doesn’t mean the way is clear.\u003Cbr \u002F>5) \u003Cstrong>If you can avoid a crash without causing another one, you must\u003C\u002Fstrong> – because ultimately, the goal is to prevent collisions.\u003C\u002Fp>\n\u003Cp>\u003Ciframe src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fpn88uJbkQqc\" width=\"560\" height=\"314\" allowfullscreen=\"allowfullscreen\">\u003C\u002Fiframe>\u003C\u002Fp>\n\u003Cp>We believe that any AV following the five rules of RSS will never cause an accident, and will respond safely and appropriately to any potentially dangerous situation it might encounter. To substantiate that position, we’ve opened RSS up to independent scrutiny, and continue to invite outside members of industry, academia, and government to identify any scenario that an AV operating under RSS would not be able to handle. \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>The Leanest Possible Driving Policy\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>RSS stems from a \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F1708.06374\" target=\"_blank\" rel=\"noopener\">research paper on autonomous vehicle safety published in 2017\u003C\u002Fa> by three of \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fabout\u002Fmanagement\u002F\" target=\"_blank\" rel=\"noopener\">Mobileye’s leading minds\u003C\u002Fa>, but its real-world applications extend far beyond the academic.\u003C\u002Fp>\n\u003Cp>RSS forms the basis of the singularly lean driving policy by which our AVs operate. Rather than trying to determine every possible scenario that could potentially happen, our RSS-based driving policy focuses on what is likely to happen. It does so by continually calculating reasonable worst-case assumptions within the range of realistic possibilities – not unlike how a human drives.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F3562e87a9e8ff414c63f5e334583c9af_1672933433454.png\" alt=\"Responsibility-Sensitive Safety codifies safe driving into five rules to govern all of an autonomous vehicle’s decisions.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Cp>This “lean” computing process takes place on our highly efficient and compact \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Ftechnology\u002Feyeq-chip\u002F\" target=\"_blank\" rel=\"noopener\">EyeQ™ Systems-on-Chip\u003C\u002Fa> and enables the AV to make sound, split-second decisions on how to operate in real-world scenarios – not just in limited geographic areas, but in \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fnews\u002Fautonomous-vehicle-testing-miami-stuttgart\u002F\" target=\"_blank\" rel=\"noopener\">locations around the world\u003C\u002Fa>, where driving conditions and behavior differ widely. \u003C\u002Fp>\n\u003Ch3>\u003Cstrong>Opening Roads to Autonomous Mobility\u003C\u002Fstrong>\u003C\u002Fh3>\n\u003Cp>However good and trustworthy it is, developing the technology required for an AV to function correctly is only part of the equation. To deploy autonomous vehicles at scale, AVs will need roads on which they’re allowed to drive. And that means that government regulators will need to adapt the rulebooks developed over the course of decades for human-driven vehicles to include self-driving vehicles as well.\u003C\u002Fp>\n\u003Cp>RSS supports that process by not merely telling, but showing regulators that self-driving technology based on RSS can be trusted to safely operate on public roadways. And that empowers regulators, policymakers, and other \u003Ca href=\"https:\u002F\u002Fwww.mobileye.com\u002Fblog\u002Fresponsibility-sensitive-safety-gains-traction-worldwide\u002F\" target=\"_blank\" rel=\"noopener\">stakeholders\u003C\u002Fa> to make informed decisions in paving the way for autonomous mobility.\u003C\u002Fp>\n\u003Cp>The adaptability of RSS even allows for individual jurisdictions to customize the model to suit their local roadways and driving cultures. One country might prioritize safety, for example, by mandating that AVs maintain a greater distance from other vehicles, while another might emphasize fitting more seamlessly into traffic. RSS allows for such fine-tuning – much in the same way that speed limits are determined according to local conditions.\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Fstatic.mobileye.com\u002Fwebsite\u002Fus\u002Fcorporate\u002Fimages\u002F2c34229cd8ee4f4cd998e05a3af9c63b_1677141578538.png\" alt=\"RSS formulates the unwritten rules of the road into an open, comprehensive, and verifiable mathematical model.\" width=\"1650\" height=\"776\" \u002F>\u003C\u002Fp>\n\u003Cp>Arguably more than any individual application or parameter, however, the Responsibility-Sensitive Safety framework is about engendering trust through transparency. And we believe that trust is precisely what’s needed for the world to embrace the future of transportation whose time has come.\u003C\u002Fp>","2023-02-23T08:00:00.000Z",[84,27],{"id":281,"type":100,"url":282,"title":283,"description":284,"primary_tag":98,"author_name":137,"is_hidden":96,"lang":133,"meta_description":284,"image":285,"img_alt":286,"content":287,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":137,"featured":96,"publish_date":288,"tags":289},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":291,"type":100,"url":292,"title":293,"description":294,"primary_tag":20,"author_name":137,"is_hidden":96,"lang":133,"meta_description":294,"image":295,"img_alt":296,"content":297,"download_doc":137,"download_title":137,"download_btn":137,"webinar_video":137,"thumbnail":137,"is_gated":137,"featured":96,"publish_date":288,"tags":298},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],1784714290425]