每经记者｜高涵 每经编辑｜程鹏 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。 但这趟旅程并不轻松。大卫·莫斯告诉每经记者，由 ...

TOP2个人对激光雷达持有待进一步观察的基础观点。 关于激光雷达在自动驾驶应用上大致三个流派 1.完全不用派（特斯拉是代表，小鹏属于现在全系不用了，不过留了口子说将来或许会用） 核心逻辑链是：现阶段而言，纯视觉可以实现激光雷达的所有好处（主要指安全），且激光雷达带来了额外坏处（延时与scaling up效率降低），并不是 单纯的只有额外好处或额外冗余，额外坏处不包含更高的bom成本。 细化视角为： 光靠摄像头可以实现很高的安全水准， 任意时刻都全神贯注 开车的老司机的事故率远低于平均事故率。光靠摄像头能比全神贯注开车老 司机更安全。 2.激光雷达主要用于主动安全，当作一个类似安全带的安全件的定位，驾驶本身主要靠纯视觉。（理想是其中的典型代表） 3.激光雷达也要深刻参与自动驾驶本身（Waymo是代表，H此前也是，现在是什么状态不详） 本文将侧重分析纯视觉派与激光雷达安全冗余派的观点差异，不侧重激光雷达深度参与派的观点。 纯视觉派的常见叙事逻辑是：靠纯视觉不论博弈能力还是安全水平的上限都非常高，人类不需要激光雷达就能开车。 激光雷达安全冗余派的常见叙事逻辑是：XXX情况下，有激光雷达对主动安全很有帮助，当个安全件 ...

马斯克最近干了件大事，让特斯拉Robotaxi的安全员"集体下岗"。没有自欺欺人的远程安全员、云代驾，就是实打实的把方向盘交给机 器。也就是说，Robotaxi离真正的商业化落地又近了一大步。 作为纯视觉路线的"孤勇者"，马斯克当年没少为这事挨喷。很多大佬都认为马斯克做纯视觉是罔顾用户安全，无法应对复杂天气、路 况。但坚持"第一性"的他坚持认为，真正的自动驾驶就要和人脑、双眼协同模式一样，而不应该用激光雷达等传感器来"拄拐前行"。当 然，特斯拉也为他的坚持付出了代价——"白色大车货厢被误判为天空"引发的车祸。虽然该问题已经在多次迭代中得到修复，但算法识 别在低对比度等极端情况下的风险始终是一把悬顶之刃。再加上纯视觉方案的成本太低了，跟曾经动辄上千美元的激光雷达比，小小的 摄像头模组几乎等于"白给"。分析显示，特斯拉单车自动驾驶系统成本不足 Waymo 的四分之一，对于中国自动驾驶势力来说，一旦纯视 觉方案跑通，那么行业必然会形成特斯拉的一家独大，激光雷达缓慢的降本模式将被降维打击。 而巨大的"钱景"永远是原罪，一旦再次出现风险，"吃人血馒头"的舆论随时都会吞噬品牌。马斯克不是第一次玩钢丝起舞，从可回收火 箭颠 ...

Core Insights - The article highlights the rapid expansion and competitive positioning of the autonomous driving company, Luobo Kuaipao, in the global Robotaxi market, emphasizing its operational achievements and strategic shifts towards international markets and cost reduction strategies [1][4][6]. Group 1: Operational Achievements - Luobo Kuaipao has expanded its operations to 22 cities globally, including major locations like Beijing, Shanghai, Wuhan, Shenzhen, Hong Kong, Dubai, and Abu Dhabi, with over 25,000 weekly orders and a total of over 17 million cumulative orders [4]. - The company has achieved over 240 million kilometers in total autonomous driving mileage, with 140 million kilometers being fully driverless [4]. - In Wuhan, Luobo Kuaipao has reached breakeven on a unit economic basis, indicating that the revenue from each autonomous vehicle covers its direct operating costs [7]. Group 2: Competitive Landscape - Competitors such as Xiaoma Zhixing and Wenyan Zhixing are also seeking to expand, with Xiaoma Zhixing claiming to operate in four major cities while Luobo Kuaipao is limited to Beijing and Shanghai [2]. - The global Robotaxi market is witnessing aggressive expansion, with companies like Waymo and Tesla also ramping up their services in various U.S. cities [5][6]. Group 3: Strategic Shifts - Luobo Kuaipao is shifting its focus from domestic operations to international markets, having entered Dubai and formed partnerships with Uber and Lyft for extensive deployments outside of China [6]. - The company is transitioning from a multi-sensor approach to a pure vision technology strategy, aiming to reduce costs and improve market competitiveness [10][14]. Group 4: Cost Reduction and Future Plans - The sixth-generation autonomous vehicle (Apollo RT6) has seen a 60% reduction in procurement costs compared to its predecessor, with a target to further decrease costs by eliminating certain sensors [13][14]. - The company aims to achieve a per-kilometer cost below 1 yuan, significantly lower than traditional ride-hailing services, as part of its long-term strategy to dominate the market [14]. Group 5: Safety and Regulatory Considerations - Luobo Kuaipao emphasizes safety, claiming its accident rate is one-fourteenth that of human drivers, and has implemented multiple safety redundancies in its vehicles [21]. - The company faces challenges related to regulatory acceptance and the need to avoid major accidents as it expands its operations globally [19][21].

Core Viewpoint - Tesla's dominance in the intelligent driving sector is attributed to its continuous evolution of self-developed driving chips, which have become a key force in reshaping the industry landscape [1][54]. Group 1: Tesla's Early Development and Partnerships - In 2014, Tesla began its journey into intelligent driving by collaborating with Mobileye, utilizing the EyeQ3 chip for its Autopilot 1.0 system [3][6]. - The initial hardware platform HW1.0 was limited by Mobileye's black-box solutions, which restricted Tesla's ability to customize algorithms and utilize data effectively [8][9]. Group 2: Transition to NVIDIA and HW2.0 - After ending its partnership with Mobileye in 2016, Tesla partnered with NVIDIA to develop the HW2.0 system, significantly increasing processing power from 0.256 TOPS to 12 TOPS [10][11]. - HW2.0 featured a "vision-first" approach, utilizing multiple cameras to create a 360-degree view, enhancing the vehicle's environmental perception [14][15]. Group 3: Advancements with HW3.0 and Self-Development - In 2019, Tesla launched the HW3.0 platform with its self-developed Full Self-Driving (FSD) chip, achieving a processing power of 144 TOPS, marking a significant leap in capabilities [21][23]. - The FSD chip's architecture allowed Tesla to optimize chip design according to its algorithm needs, facilitating rapid iterations of intelligent driving features [25][49]. Group 4: HW4.0 and Enhanced Scene Adaptation - The HW4.0 system, introduced in 2023, aimed to address the limitations of HW3.0 in complex urban environments, featuring a new FSD chip with over three times the processing power [30][31]. - HW4.0 reintroduced millimeter-wave radar to improve safety and reliability, enhancing the system's ability to handle diverse driving scenarios [33][34]. Group 5: Future Developments with AI5 and HW5.0 - Tesla's next-generation AI5 chip, expected to achieve 2000-2500 TOPS, is set to redefine the standards for intelligent driving technology [42][46]. - The HW5.0 system is anticipated to begin small-scale deliveries in mid-2025, with plans for mass production in 2026, further solidifying Tesla's leadership in the autonomous driving market [43][46]. Group 6: Synergy with Shanghai Factory - The Shanghai factory plays a crucial role in Tesla's self-developed chip strategy, providing a cost-effective production environment that supports rapid technological iterations [48][50]. - The factory's high localization rate and production efficiency have significantly reduced costs, allowing Tesla to invest more in R&D for intelligent driving technologies [49][52].

Core Viewpoint - Tesla's reputation as a leader in autonomous driving technology has been severely challenged following the launch of its paid Full Self-Driving (FSD) pilot program in Austin, which showcased significant operational failures and raised questions about the company's reliance on low-cost camera systems instead of more advanced sensor technologies like LiDAR [1][2][4][5]. Group 1: Autonomous Driving Technology - Elon Musk has repeatedly stated that a significant portion of Tesla's traditional fleet will be converted into revenue-generating autonomous taxis, with expectations of "millions of self-driving Tesla cars" by 2026 [2][5]. - Tesla argues that a set of commercial cameras, trained on billions of frames, can achieve human-like vision and outperform more expensive sensor suites, but peer-reviewed literature challenges the feasibility of achieving Level 4 autonomy with cameras alone [2][4]. - A study published in June 2025 indicated that pure camera systems have a 40% higher misjudgment rate in fog and snow compared to systems equipped with LiDAR, raising concerns about safety in adverse conditions [2][4]. Group 2: Regulatory and Safety Concerns - The absence of radar exacerbates safety issues, as radar can measure relative speed and identify metal objects through rain or dust, providing a backup when cameras are obstructed [4][5]. - Recent incidents during the Austin pilot program, including a Model Y vehicle making dangerous maneuvers, have prompted investigations by the National Highway Traffic Safety Administration (NHTSA) [7][10]. - New Texas regulations effective September 1, 2025, allow the state to revoke autonomous driving permits that do not meet safety standards, highlighting the potential for increased regulatory scrutiny on Tesla's operations [5][7]. Group 3: Financial Performance and Market Reaction - Tesla's production in Q2 2025 was 410,244 vehicles, a slight increase from Q1 but a 0.2% decrease year-over-year, while deliveries fell 13.5% to 384,122 vehicles, missing market expectations [10][11]. - Following the disappointing delivery numbers, Tesla's stock price dropped 3.8%, reflecting investor concerns over the company's ability to generate revenue from its autonomous driving initiatives amid declining sales [11][12]. - Analysts are divided on Tesla's future, with some raising target prices based on potential FSD revenue, while others downgrade ratings due to rising regulatory risks and the uncertainty surrounding the FSD rollout [12][13]. Group 4: Future Outlook and Investor Sentiment - The failure of the Austin pilot program has led to increased legal liability risks, with potential collective lawsuits looming if passengers are harmed [13][17]. - Investors are advised to adjust their forecasts, anticipating no significant revenue from autonomous taxis until at least 2028, and to increase discount rates to reflect execution and legal risks [17][18]. - Despite the challenges, Tesla retains advantages such as a vast data collection capability and manufacturing efficiency, which could support future improvements in its autonomous driving technology [14][15].

Core Viewpoint - Tesla's Robotaxi project, which relies on pure vision technology for autonomous driving, faced its first public collision incident just two weeks into trial operations, raising new safety concerns about the technology's reliability in complex scenarios [1][3]. Group 1: Incident Details - The collision involved a fully autonomous Model Y that unexpectedly accelerated and turned, scraping against a parked Toyota Camry without causing injuries or significant damage [1]. - The incident was recorded by a well-known Tesla blogger, highlighting the vehicle's erratic behavior after multiple failed attempts to enter a parking lot [3]. Group 2: Technology Concerns - Experts pointed out that the pure vision system may struggle with obstacle recognition in low-light conditions or areas with visual blind spots, leading to potential failures in identifying hazards [3]. - Other testers reported similar issues, including sudden braking, incorrect responses to emergency vehicle lights, and even scenarios where passengers were left stranded in dangerous locations [3]. Group 3: Expert Opinions - Elon Musk has consistently advocated for the superiority of the pure vision approach over lidar technology, asserting that a combination of cameras and neural networks is sufficient for achieving full autonomy [3]. - A traffic engineering professor from the University of Texas criticized the Tesla vehicles for fundamental environmental understanding flaws, such as ignoring speed limit signs and exhibiting structural decision-making vulnerabilities [3].

Core Viewpoint - Tesla emphasizes its commitment to a vision-based processing solution for affordable and safe intelligent products, contrasting with the rising popularity of LiDAR technology in the automotive industry [2][3]. Group 1: Technology Disagreement - Tesla's upcoming Full Self-Driving (FSD) solution relies solely on camera and AI chip collaboration, while companies like Huawei and Li Auto advocate for LiDAR, citing its ability to detect obstacles without needing to identify them [3][4]. - The divergence between Tesla and domestic automakers reflects a philosophical debate between "algorithm-driven" and "hardware-driven" approaches, with Tesla focusing on data-driven algorithms and others prioritizing hardware redundancy for safety [4][5]. Group 2: Cost and Market Strategy - Tesla's insistence on a vision-based approach is partly due to cost considerations, as CEO Elon Musk has labeled LiDAR as an "expensive crutch" [5][6]. - The removal of radar from Tesla's Model 3 and Model Y has reduced hardware costs, allowing for competitive pricing in the global market, although there are concerns about the affordability of Tesla's FSD package compared to offerings from domestic brands [6][7]. Group 3: Market Trends and Adjustments - The automotive market is witnessing a shift in how companies configure their vehicles, with many adjusting their marketing strategies regarding intelligent driving features, particularly in light of stricter regulations and intense price competition [7][8]. - Companies are increasingly recognizing that adding LiDAR may only provide additional safety redundancy rather than a significant upgrade in system capabilities, leading to a potential reduction in the emphasis on high-end features in favor of more competitive pricing [7][8].