每经记者｜高涵 实习生 雷婷婷 每经编辑｜兰素英 "实现完全自动驾驶不一定需要激光雷达。" 这是28岁的激光雷达销售员大卫•莫斯（David Moss）在完成了特斯拉"完全自动驾驶"（FSD）横跨美国之旅后得出的结论。 当地时间2025年12月28日凌晨2:30，美国加州洛杉矶的特斯拉餐厅门前，大卫•莫斯坐进他的Model 3，指尖轻点屏幕启用FSD系统，车辆平稳启动。 在接下来的2天20小时，他声称自己的手未碰过一次方向盘，也未踩过一脚油门或刹车，任凭这辆搭载FSD V14.2的电动汽车，驶过繁忙的洛杉矶街道， 汇入州际高速，穿越24个州，最终抵达南卡罗来纳州大西洋岸边的默特尔海滩。 全程2732.4英里（约合4397公里），无人工接管。 这是全球首次、数据可验证的依靠FSD跨美之旅，也让埃隆•马斯克2016年"让汽车自己横穿美国"的愿望成为现实。 他为何要进行这场挑战？在复杂多变的路况下，FSD表现究竟如何？ 近日，大卫•莫斯接受了《每日经济新闻》记者（以下简称每经记者）独家专访。从激光雷达的从业者，到对马斯克"纯视觉"路线的信徒，他向我们讲述 了这场颠覆认知的旅程。 近4400公里全程放手，但不能放松 ...

东四十条资本 . 聚焦股权投资行业人物、事件、数据、研究、政策解读，提供专业视角和深度洞见 | 创投圈有趣的灵魂 以下文章来源于东四十条资本 ，作者张雪 激光雷达领域， 美国已经被判出局。 文 ｜ 张雪 来源｜ 东四十条资本（ID：DsstCapital） 封面来源 ｜ Luminar官网 " 任何依赖激光雷达的人都注定要失败 " 马斯克曾如此断言。 12 月 15 日，被看做是美国激光雷达最后一根独苗的 Luminar ，在官网宣布了破产重组的消息，根据 Luminar 提交的法庭文件，其资产估值在 1 亿至 5 亿美元之间，而债务及负债总额则高达 5 亿至 10 亿美元。 受破产消息影响， Luminar 当天股价应声暴跌 60.82% ，降至每股 0.35 美元，市值仅 2744.53 万美元。 从天才少年的创业项目，到百亿美元市值的科技新贵，再到现在戏剧性的关门大吉， Luminar 的故事也成为了美国激光雷达发展历史的一个缩影。它的 倒下也意味着在激光雷达领域，美国已经被判出局，相应的，中国厂商占领了绝大部分的市场份额。 溃败 2020 年 SPAC 火热时， Luminar 通过这种方式登陆资本市 ...

Core Viewpoint - Luminar, once valued at $7.8 billion, filed for Chapter 11 bankruptcy on December 15, 2025, marking a significant decline in the U.S. lidar industry, as it was seen as a leading hope for the sector [1][16][30] Group 1: Company Overview - Luminar was founded in 2012 by Austin Russell with the vision of providing precise environmental perception for vehicles [3][18] - The company became a unicorn in 2017 after raising $36 million in Series B funding, reaching a valuation of over $1 billion [19] - Luminar went public via a SPAC merger in December 2020, raising approximately $600 million and achieving a market cap of $7.8 billion [19][20] Group 2: Business Challenges - Despite initial success, Luminar faced significant challenges, including reliance on a few major clients, particularly Volvo, which led to vulnerability [20][21] - In 2024, Volvo cut its annual order expectations by 75%, exacerbating Luminar's cash flow issues and leading to layoffs and restructuring [5][21] - By the end of 2024, Luminar's cash reserves fell below $100 million, with debts reaching $380 million [5][21] Group 3: Market Dynamics - The global lidar market is shifting, with Chinese manufacturers capturing approximately 92% of the market share by 2024, contrasting with the decline of U.S. players [2][11] - Chinese firms like Hesai and RoboSense have adopted a more diversified approach, focusing on various applications beyond passenger vehicles, which has contributed to their growth [26][27] - Luminar's reliance on a high-cost 1550nm lidar technology limited its competitiveness against the more cost-effective 905nm solutions favored by Chinese manufacturers [7][26] Group 4: Technological Debate - The debate over the necessity of lidar in autonomous driving continues, with figures like Elon Musk arguing that lidar is unnecessary and costly [8][23] - In contrast, companies like WeRide advocate for a multi-sensor fusion approach, emphasizing the importance of lidar for safety in complex driving environments [24][25] - The divergence in technology strategies reflects broader commercial model differences, with Tesla targeting mass-market vehicles and WeRide focusing on commercial applications [10][25] Group 5: Future Outlook - Luminar's bankruptcy signifies a pivotal moment in the lidar industry, indicating a potential restructuring of market leadership towards Chinese firms [28][29] - The future of lidar technology may see continued innovation and competition, with potential disruptions from companies like Apple and Google entering the space [29][30] - Despite current advantages, Chinese manufacturers must remain vigilant against technological disruptions and market fluctuations to maintain their lead [30]

以下文章来源于东四十条资本 ，作者张雪 东四十条资本 . 聚焦股权投资行业人物、事件、数据、研究、政策解读，提供专业视角和深度洞见 | 创投圈有趣的灵魂 将投中网设为"星标⭐"，第一时间收获最新推送 在激光雷达领域，美国已经被判出局。 作者丨张雪 来源丨东四十条资本 " 任何依赖激光雷达的人都注定要失败 " 马斯克曾如此断言。 12 月 15 日，被看做是美国激光雷达最后一根独苗的 Luminar ，在官网宣布了破产重组的消息，根据 Luminar 提交的法庭 文件，其资产估值在 1 亿至 5 亿美元之间，而债务及负债总额则高达 5 亿至 10 亿美元。 受破产消息影响， Luminar 当天股价应声暴跌 60.82% ，降至每股 0.35 美元，市值仅 2744.53 万美元。 从天才少年的创业项目，到百亿美元市值的科技新贵，再到现在戏剧性的关门大吉， Luminar 的故事也成为了美国激光雷达 发展历史的一个缩影。它的倒下也意味着在激光雷达领域，美国已经被判出局，相应的，中国厂商占领了绝大部分的市场份 额。 溃败 2020 年 SPAC 火热时， Luminar 通过这种方式登陆资本市场。上市即巅峰，这句 ...

来源：市场投研资讯 （来源：东四十条资本） "任何依赖激光雷达的人都注定要失败"马斯克曾如此断言。 12月15日，被看做是美国激光雷达最后一根独苗的Luminar，在官网宣布了破产重组的消息，根据 Luminar 提交的法庭文件，其资产估值在1亿至5亿美元之间，而债务及负债总额则高达5亿至10亿美 元。 受破产消息影响，Luminar当天股价应声暴跌60.82%，降至每股0.35美元，市值仅2744.53万美元。 从天才少年的创业项目，到百亿美元市值的科技新贵，再到现在戏剧性的关门大吉，Luminar的故事也 成为了美国激光雷达发展历史的一个缩影。它的倒下也意味着在激光雷达领域，美国已经被判出局，相 应的，中国厂商占领了绝大部分的市场份额。 溃败 2020年SPAC火热时，Luminar通过这种方式登陆资本市场。上市即巅峰，这句话用在Luminar再合适不 过了。这里的"巅峰"，不光指股价，还有Luminar的业务。 虽然很多车企跟Luminar签了订单，但在实际交付上却一直面临挑战，这使得Luminar一直深陷亏损的漩 涡，长期低于成本价供货导致"卖得越多亏得越多"，2025年第三季度财报显示其运营利润率低 ...

Investment Rating - The industry investment rating is "Outperform the Market" [5] Core Insights - Tesla's CEO announced the removal of safety drivers for Robotaxi in Austin, Texas, marking a significant step towards the commercialization of a pure vision-based autonomous driving solution [2] - As of October 2025, Tesla's Robotaxi has accumulated over 400,000 kilometers in Austin and 1.6 million kilometers in the Bay Area without major accidents, providing a foundation for validating the safety of the autonomous system [2] - The removal of safety drivers is expected to save over $100,000 in annual operating costs per vehicle, with significant reductions in labor costs [2] - Tesla plans to launch the Cybercab, a dedicated autonomous taxi, in Q2 2026, aiming to reduce the vehicle cost to $30,000 to support larger-scale commercialization [2] - The report suggests that the successful implementation of the Robotaxi business model relies on a safe, cost-effective, and easily scalable advanced driving solution, benefiting automakers and key component suppliers with strong control over the supply chain [2] Summary by Sections Industry Overview - The report highlights the differentiation in annual sales target completion among car manufacturers, particularly in the smart vehicle segment [1] Tesla's Developments - Tesla's Robotaxi initiative is advancing with the removal of safety drivers, supported by extensive road testing data [2] - The company is enhancing its Full Self-Driving (FSD) capabilities, with improvements in complex driving scenarios [2] Cost and Pricing Strategy - The report details the cost savings from eliminating safety drivers and outlines Tesla's dynamic pricing strategy for Robotaxi services [2] Investment Recommendations - The report recommends focusing on companies with strong capabilities in advanced driving technology and supply chain management, including Xiaopeng Motors, Li Auto, Xiaomi Group, and Leap Motor [2]

特斯拉首席执行官埃隆·马斯克（Elon Musk）不久前在 X 上发文，对竞争对手 Waymo 予以暗讽，称该 公司"从来就没有真正胜出的机会"，并表示"这一点事后回看将显而易见"。 目前，特斯拉与谷歌旗下的 Waymo 是美国自动驾驶领域的两大主要推动者，双方均在美国运营无人驾 驶网约车服务。不过，特斯拉在得克萨斯州奥斯汀的车辆中仍配备有"安全监督员"（Safety Monitor）， 而在旧金山湾区的运营中则安排人员坐在驾驶座上。，到今年年底，奥斯汀的运营将完全取消所有安全 监督员。 作为美国无人驾驶浪潮中的两大核心企业，双方的竞争关系显而易见。两家公司已在奥斯汀和旧金山湾 区就地理围栏（geofence，即服务区域）展开多次交锋。 Waymo 的战略聚焦于大型城市，而特斯拉则表示其自动驾驶能力将扩展至全球每一辆特斯拉车辆。这 正是两者之间真正的差异所在。此外，特斯拉使用自有车型，而 Waymo 的车队则包含多个制造商提供 的不同车型。 在技术路线上，双方也存在根本分歧：特斯拉坚持纯视觉（vision-only）方案，而 Waymo 则依赖包括 激光雷达（LiDAR）在内的多种传感器，马斯克曾将激光雷达称 ...

Core Viewpoint - The ongoing debate in the autonomous driving field revolves around the merits of pure vision systems versus sensor fusion approaches, with a strong emphasis on the superiority of camera-based systems in terms of information richness and processing frequency [5][6][11]. Group 1: Technical Insights - Cameras provide higher frequency and richer information compared to LiDAR, with frame rates reaching 30 frames per second for cameras versus 10 frames per second for LiDAR [7][11]. - The reliance on LiDAR in some fusion systems may indicate a deficiency in the visual processing capabilities of those systems [5][6]. - The performance ceiling of autonomous driving systems is significantly influenced by the choice of sensors, with pure vision systems having a higher potential if algorithms and computational power are sufficiently advanced [8][11]. Group 2: Industry Perspectives - The current trend shows that many domestic manufacturers are achieving around 10 frames per second, while Tesla's systems are reportedly exceeding 20 frames per second, highlighting a gap in visual processing capabilities [17]. - The use of LiDAR is often seen as a shortcut to quickly deploy systems, but it may limit the long-term performance and development of autonomous driving technologies [6][19]. - The integration of multiple sensor types, including cameras and LiDAR, is viewed as beneficial, but the primary focus should remain on enhancing visual capabilities [14][19]. Group 3: Future Considerations - The industry is moving towards data-driven systems that leverage AI to generate diverse driving scenarios, which can enhance the training of autonomous systems without the high costs associated with extensive data collection [19]. - The evolution of sensor technology, such as the increase in LiDAR line counts, aims to improve detection capabilities, but this also raises cost considerations [18]. - The debate over sensor reliance continues, with some manufacturers still favoring LiDAR due to perceived limitations in visual processing, indicating a need for further advancements in camera-based systems [17][19].

Core Viewpoint - The ongoing debate in the autonomous driving field revolves around the merits of pure vision systems versus sensor fusion approaches, with a strong emphasis on the superiority of camera-based systems in terms of information richness and processing frequency [3][4][9]. Summary by Sections Technical Insights - Pure vision systems utilize cameras as the primary sensors, providing higher frequency and richer data compared to LiDAR systems, which have lower frame rates and less detailed point cloud information [4][9]. - The performance ceiling of autonomous driving systems is significantly influenced by the choice of sensors, with pure vision systems having a higher potential if algorithms and computational power are sufficiently advanced [5][9]. Sensor Performance - Cameras can capture images at 30 frames per second, while LiDAR typically operates at around 10 frames per second, leading to a disparity in the amount of information processed [4][9]. - The reliance on LiDAR in some fusion systems may indicate a lack of development in visual processing capabilities, which can hinder overall system performance in challenging scenarios [10][11]. Industry Perspectives - The CEO of Nullmax, Xu Lei, advocates for prioritizing visual capabilities in autonomous systems, suggesting that over-reliance on LiDAR may provide a short-term solution but limits long-term performance [4][10]. - Xu Lei emphasizes the importance of developing robust visual processing algorithms to fully leverage the data captured by cameras, as the information density is significantly higher than that of LiDAR [6][9]. Cost and Practical Considerations - The integration of multiple sensor types must consider cost and performance trade-offs, as adding LiDAR can increase system complexity and expense without necessarily enhancing performance [5][14]. - The industry is witnessing a trend where companies prioritize rapid deployment of systems, often opting for LiDAR to expedite the process, despite potential limitations in performance [11][16]. Future Directions - Xu Lei expresses an open-minded approach towards the use of various sensors, including future technologies, while maintaining that visual capabilities should remain the core focus of development [10][11]. - The evolution of sensor technologies, such as 4D millimeter-wave radar, is seen as complementary to camera systems, particularly in adverse weather conditions, although the necessity of LiDAR is debated [13][14].

Core Insights - The discussion at Morgan Stanley's 24th Asia-Pacific Summit featured Sebastian Thrun, a key figure in autonomous driving, and analyst Adam Jonas, covering various aspects of autonomous driving technology, industry stages, and the evolution of companies like Waymo [1][3] Autonomous Driving Technology - The primary technical debate in autonomous driving is between "pure vision" and "multi-sensor fusion" approaches, with Thrun highlighting Tesla's pure vision FSD tests in Austin as a potential industry turning point [4][6] - The cost advantage of pure vision systems is significant, as high-end LiDAR costs thousands of dollars compared to camera costs of only tens of dollars, which could disrupt the multi-sensor fusion approach if proven safe [6] - Pure vision systems face challenges in adverse weather and low-light conditions, requiring advanced AI models to infer complete environmental states from limited visual information [7] Industry Development and Commercialization - Thrun considers the 2005 DARPA Grand Challenge a pivotal moment for the industry, and notes that approximately one-third of the 500 summit attendees had experienced autonomous vehicles, primarily from Waymo [9] - The industry is transitioning from Level 4 (L4) to Level 5 (L5) autonomy, with significant economic value in freeing up driving time, and Thrun predicts the next 3-5 years will be crucial for commercialization [9][11] - Waymo's expansion plans include manual driving tests in cities like Minneapolis and New Orleans, with a goal to extend fully autonomous services to 15 cities by 2026 [9][11] Robotics and Market Dynamics - Thrun expresses caution regarding humanoid robots, suggesting that market expectations may be overly optimistic while underestimating the technical challenges involved [12] - He emphasizes the potential of aerial robots, stating that their growth will surpass that of ground robots, with infrastructure being a key limiting factor [14] - The existing air traffic control systems in the U.S. require significant upgrades to accommodate large-scale aerial robot operations, presenting investment opportunities in eVTOL and air traffic management [16] Waymo's Historical Context and Future Plans - Thrun shared insights into Waymo's origins as a Google moonshot project focused on traffic safety, emphasizing the importance of team dynamics and iterative development [17][18] - Waymo's long-term goal is to achieve fully autonomous driving without human intervention, with a current focus on expanding testing areas and scenarios [18] - The company is adopting a dual-track strategy of validating consumer experiences while exploring B2B opportunities, aiming for sustainable commercialization [18][19] Challenges in Robotaxi Deployment - Despite the acceleration of companies like Waymo and Zoox, Thrun believes the robotaxi industry has not yet reached a critical mass to transform transportation [19][21] - Key factors for reaching this critical point include geographic coverage, healthy competition, and ecosystem spillover effects, with urban density being a significant indicator [21] - The technological challenges for robotaxis include high-precision navigation, obstacle avoidance, and reliability in extreme weather conditions [20][23]