2026年开年，全球自动驾驶领域在技术验证与商业化探索上继续前行。我国首批L3级有条件自动驾驶 车型的准入许可，特斯拉将在二季度启动无方向盘、无踏板车型量产的计划，以及Waymo持续扩张无 人出租车服务网络，标志着自动驾驶的竞争重点，正从攻克"能否实现"的技术挑战，转向如何构建一个 可盈利、安全且被广泛接受的生态系统。 近日，麦肯锡未来移动中心发布了第三版自动驾驶行业领导者调查报告。这份基于全球行业专家洞察的 报告揭示了一个关键趋势：在经历了早期狂热之后，自动驾驶行业正褪去光环，进入一个更加务实、理 性且充满复杂挑战的新发展阶段。 时间表普遍延后：商业化预期趋于保守 报告最直观的发现是，行业对自动驾驶普及速度的预期显著回调。与2023年预测相比，2025年度调查报 告将大多数自动驾驶应用场景的普及时间表平均推迟1-2年。尽管中美部分城市已开通L4级无人驾驶出 租车服务，但全球性大规模商业化推广的预期节点还是从2029年推迟至2030年。面向私人乘用车的L4 级城市试点预计将从2030年推迟至2032年，而完全自动驾驶卡车的商业可行性也从2031年延后至2032 年。总体而言，专家认为L4级自动驾驶将首先在出租 ...

来源：环球网 【环球网科技综合报道】1月14日消息，据路透社报道称，特斯拉首席执行官埃隆·马斯克宣布，自2026 年2月14日起，公司旗下的"全自动驾驶"（Full Self-Driving，简称FSD）软件将仅以月度订阅形式向用 户提供，不再支持一次性买断选项。 目前，特斯拉在美国市场为车主提供两种FSD（监督驾驶版）获取方式：一次性支付8000美元，或按月 订阅99美元。该系统属于高级驾驶辅助功能，要求驾驶员始终保持注意力，并在必要时随时接管车辆控 制。 值得注意的是，美国国家公路交通安全管理局（NHTSA）已于2025年对约288万辆配备FSD系统的特斯 拉汽车展开正式调查，起因是收到50余起与该系统相关的交通违规报告及多起碰撞事故。作为回应，特 斯拉已在面向消费者的FSD产品描述中加入"监督驾驶"（Supervised）字样，以明确其技术定位。（青 云） ...

Core Viewpoint - The "Mosu Zhixing" Action Plan aims to establish Shanghai as a leading area for high-level autonomous driving by 2027, focusing on technology innovation, application demonstration, and industry collaboration [2]. Group 1: Development Goals - The plan outlines a vision for large-scale implementation of Level 4 autonomous driving applications, targeting over 6 million passenger trips and 80,000 TEU in cargo transport by 2027 [2]. - It aims to create a comprehensive ecosystem for smart connected vehicles, achieving international competitiveness in key technologies and industry scale [2]. Group 2: Key Tasks - **Diverse Application Scenarios**: - Expand passenger vehicle applications through organized smart taxi operations and pilot projects for Level 3 autonomous vehicles [3]. - Enhance commercial vehicle applications in key locations like airports and train stations, transitioning to fully unmanned operations [3]. - Promote the deployment of autonomous equipment in urban inspection, logistics, and municipal services [3]. - **High-Energy Innovation Elements**: - Establish a digital twin training ground for autonomous driving, accumulating extensive data for model training [4]. - Develop a unified data monitoring platform for smart connected vehicles to ensure real-time operational oversight [4]. - Gradually expand open areas for autonomous driving, focusing on major urban zones and transport hubs [4]. - **Innovative Industry Ecosystem**: - Implement key technology research initiatives for advanced hardware and software solutions in autonomous driving [6]. - Build a world-class automotive industry cluster in regions like Pudong and Jiading, focusing on smart connected vehicles and key components [6]. - Strengthen testing and validation capabilities for autonomous systems through dedicated laboratories and simulation technologies [6]. Group 3: Support Measures - **Policy Support**: - Enhance data management mechanisms and establish a comprehensive safety assurance system for autonomous driving [7]. - **Financial Support**: - Encourage investment in startups focused on smart connected vehicles and support established companies in accessing diverse financing channels [7]. - **Talent Development**: - Promote talent acquisition in the smart connected vehicle sector and foster collaboration between enterprises and educational institutions [7]. Group 4: Regional Collaboration - Streamline testing and application management across the city, ensuring data sharing and coordinated operations [8]. - Foster collaboration within the Yangtze River Delta region to enhance testing capabilities and facilitate large-scale applications [8].

据徐宾分析，五年前中国乘用车出口量约为100万辆，2025年达到约600万辆，增幅巨大。值得关注的 是，五年前中国出口乘用车的单车售价为10万元人民币左右，现在则达到约30万元人民币，价格上涨说 明中国出口的乘用车产品已从低端走向中高端。 徐宾表示，现在中国车企出海的产品除了乘用车以外还有其他品类，包括摩托车、重型卡车、巴士等， 中国汽车产品叠加了电动化的优势，再加上自动驾驶、辅助驾驶等功能，海外消费者发现与全球同行的 产品相比，中国汽车产品的性价比较高。 "当前中国车企正在加强与欧洲当地企业的合作，直接出口规模的增长和当地产能的逐步扩大，有望让 中国汽车品牌在西欧市场的占有率稳步提升。在全球市场，目前中国汽车品牌的占有率为20%，至2030 年有望达到25%。"徐宾说。(完) 来源：中国新闻网 瑞银：2030年中国汽车品牌在西欧市场占有率有望达15% 中新社上海1月14日电 (记者 姜煜)瑞银证券研究部总监徐宾14日在上海举办的"第26届瑞银大中华研讨 会"媒体分享会上表示，至2030年，中国汽车品牌在西欧市场的占有率有望从目前的5%提升到15%。 中新经纬版权所有，未经书面授权，任何单位及个人不得转载、摘 ...

不过，值得注意的是，虽然市场对于特斯拉估值与基本面前景的展望已经全面转向基于特斯拉独家AI 超算体系打造的FSD全自动驾驶、Robotaxi(完全无人自动驾驶出租车)，以及名为"擎天柱"的特斯拉AI 人形机器人，特斯拉电动车销量与汽车业务基本面并未被削弱到无足轻重，它仍是当前现金流与资产负 债表的支柱，也是FSD数据闭环与车队规模的基础(Robotaxi最终也要落到可规模化的车辆产能与运 营)。 此举将取消FSD高达约8000美元的一次性买断费用，大幅降低用户体验该技术的初始门槛。尽管命名 为"全自动驾驶"，该技术目前仍需驾驶员持续监控并随时准备接管。 在面临销售增长乏力的背景下，特斯拉正将其战略重心转向以科技为核心的增长点，如FSD、无人驾驶 出租车和机器人业务。去年，特斯拉已将全球最大电动汽车制造商的头衔让位于中国的比亚迪 （002594）。 特斯拉公司(TSLA.US)宣布将彻底改变其高级驾驶辅助系统"全自动驾驶"(FSD)的销售模式，全面转向 月度订阅服务。首席执行官埃隆·马斯克在社交媒体平台X上公布了这一转变，计划于2月14日后生效。 马斯克未具体说明决策原因，该服务目前月度费用为99美元。 ...

1月14日，大华继显发表报告指，小鹏汽车为2026年设定了55万至60万辆的交付目标(同比增长28- 40%)，此目标基于强劲的产品阵容及出口量翻倍，高于该行的预估。由于先进驾驶辅助系统、自动驾 驶出租车及人形机器人等新项目投入，2026年研发支出可能增加至超过100亿元。该行维持小鹏2025年 净亏损预测为14.81亿元，这意味着第四季净利润预测为4200万元，而市场共识预测为1亿元。基于更高 的研发支出，该行下调小鹏2026及2027年净利润预测39%及6%；维持"买入"评级，目标价从145港元下 调至125港元。（新浪财经） 作者丨彭鑫 编辑丨安安 ...

Core Viewpoint - The article discusses the stagnation of autonomous driving technology in China, highlighting a lack of significant advancements and innovation in recent years, despite intense competition in the industry [2]. Group 1: Current State of Technology Sharing - Recent technology sharing events in the autonomous driving sector have become less substantive, focusing more on high-level discussions rather than specific technical details or innovations [3]. - There has been a noticeable absence of new algorithms or system architecture upgrades in recent presentations, leading to a perception that the content is repetitive and lacks depth [5]. Group 2: Historical Context and Evolution - In the past, significant advancements such as BEV perception and the elimination of reliance on high-precision maps marked important milestones in the development of autonomous driving technology [4]. - The end-to-end technology paradigm has improved the efficiency of urban driving systems, but recent events have failed to deliver new technological breakthroughs that enhance user experience [5]. Group 3: Market Dynamics and Competition - The democratization of smart driving features has led to a situation where even lower-priced vehicles can offer advanced functionalities, diminishing the competitive edge of high-end models [6]. - The stagnation of leading brands has allowed traditional players to leverage their latecomer advantages, creating opportunities for them to catch up in the market [7]. Group 4: Future Implications - The potential for a lack of innovation in the autonomous driving sector raises concerns about the sustainability of research and development investments, which are crucial for long-term progress [8]. - The industry faces a critical period where the ability to break free from stagnation and advance towards fully autonomous driving will determine its future trajectory [8].

Core Insights - The article emphasizes the importance of probabilistic perception and control in autonomous driving, advocating for a tight coupling between perception and control systems to enhance safety and decision-making [10][11][12]. Technical Approach - The core idea is to output a probability distribution rather than a single deterministic result, allowing the system to quantify its uncertainty and make informed decisions based on that uncertainty [10][11]. - The system should output key features of obstacles, including position, speed, size, and category, along with their uncertainties, which are crucial for safety decisions [11]. Challenges - Major challenges include algorithm limitations, sensor noise, and the inherent ambiguity of the environment, which can lead to uncertainty in perception [15]. - Developing algorithms that can naturally output probability distributions and optimizing planning and control algorithms to utilize uncertainty information effectively are critical [15]. Case Study - A case study illustrates the difference between traditional deterministic approaches and probabilistic outputs in handling a stationary vehicle potentially encroaching into the lane, highlighting the advantages of probabilistic decision-making [14][16]. Sensor Fusion and Localization - The article discusses the significance of multi-sensor fusion for precise localization, combining data from LiDAR, cameras, RTK GNSS, IMU, and wheel speed sensors to achieve robust positioning [46][47]. - The proposed solution includes a self-developed RTK GNSS tightly coupled localization scheme that enhances robustness against GNSS signal loss [49][53]. Prediction and Planning - The article outlines two main prediction methodologies: rasterized representation and vectorized representation, each with its strengths and weaknesses in modeling traffic interactions [60][65]. - A hybrid approach is suggested, utilizing both methods to adapt to different driving environments, ensuring effective modeling of structured and unstructured roads [75][77]. Control Strategies - The article introduces a closed-loop control system that adapts to real-time vehicle dynamics, enhancing robustness compared to traditional open-loop control methods [91][92]. - The system incorporates adaptive feedback control and online learning to continuously optimize control strategies based on vehicle performance and environmental conditions [99][100]. Simulation and Testing - End-to-end simulation is emphasized as a crucial component for testing the entire algorithm system, allowing for comprehensive evaluation and refinement of the autonomous driving framework [106][108].

人民财讯1月14日电，1月14日，中国汽车工业协会旗下中国汽车工业经济技术信息研究所发布《2025城 市NOA汽车辅助驾驶研究报告》。《报告》建议尽快出台自动驾驶分级管理路线图，明确各级别功能 边界、安全责任与准入标准，并推动《道路交通安全法》等相关法规修订，以明晰责任认定规则。同时 建议扩大L3级及以上自动驾驶在典型城市群和特定场景下的试点范围，通过分层级、分场景的规模化 应用，加速技术验证与商业模式探索。 ...

Core Viewpoint - The Shanghai Municipal Government has issued a three-year action plan (2026-2028) to support the transformation and upgrading of advanced manufacturing, emphasizing the development of the intelligent connected new energy vehicle industry, indicating ongoing policy support for the sector [1] Industry Dynamics - Geely Auto Group has obtained a full-area L3 autonomous driving road test license in Hangzhou, while BAIC Blue Valley's L3 vehicles are officially on the road and plan to gradually open to individuals, showcasing the acceleration of autonomous driving technology implementation [1] - The vehicle replacement policy from 2024 to 2025 is expected to drive the proportion of new energy vehicles to nearly 60%, indicating a sustained growth in industry demand [1] - In the humanoid robot sector, Chinese company Zhiyuan Robotics leads with a 39% global market share, reflecting the expansion of intelligent technology applications [1] - Despite the recent underperformance of the automotive sector, policy support and technological breakthroughs provide long-term development momentum for the smart automotive industry [1] Investment Vehicle - The Smart Automotive ETF (159889) tracks the CS Smart Automotive Index (930721), which selects listed companies involved in smart driving and vehicle networking from the A-share market, covering the entire smart automotive industry chain from hardware to software [1] - The index's industry allocation is primarily focused on information technology and consumer discretionary, aiming to reflect the overall performance of listed companies related to smart automotive [1]