趁着小红书这波Ask Me Anything，跟着几位大佬学习到很多自动驾驶之心汇总了自动驾驶AMA的一些 问答，分享给大家！ AMA的完整版我们已经汇总至自动驾驶之心知识星球，后续还将持续整理大佬们的 问答，欢迎加入和4000人一起交流自动驾驶最前沿~ 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 小米陈龙 小米汽车自动驾驶与机器人Principal Scientist陈龙@陳龍龖龘 Q1：陈老师好！我目前是同济新大一学生（未选专业，工科可任选），未来想研究自动驾驶领域，请问您就 行业发展与人才缺口而言推荐学什么专业呢？ A1：自驾有可能4年后就解决的差不多了，但AI方向肯定是没错的，所以有AI专业的话首选，没有的话就计算 机 Q2：wayne工作体验怎么样呢？感觉很多黑科技，学生时代一直在follow A2：wayve确实想得比较远，端到端，世界模型，VLA等自驾模型基本上都是产业界的开创者 Q3：请问你认为人类可以实现完全自动驾驶吗，如果可以大概还需要几年 A3：肯定可以的，L4其实Waymo、萝卜快跑已经实现了，L5可能还要至少5年 Q4：现在业 ...

Core Viewpoint - The divergence between two major technological paths for intelligent driving, namely LiDAR and pure vision, has become increasingly evident, especially following the inclusion of LiDAR in the mandatory national standard for intelligent connected vehicles [1] Group 1: Technology Paths - The recent mandatory national standard (L2 strong standard) has incorporated LiDAR as a new perception unit, which has sparked discussions on whether both LiDAR and pure vision can meet the multi-scenario safety requirements [2] - Companies like Tesla and XPeng are focusing on high-performance chips and high-precision cameras to enhance their autonomous driving technology, while others like Huawei and Suyuan Ju Chuang are advocating for the use of LiDAR to improve safety redundancy [1][2] - The debate continues on whether LiDAR or pure vision provides higher safety, with proponents of pure vision arguing that advancements in AI models and local high-performance computing can meet safety standards without LiDAR [3][4] Group 2: Market Trends and Adoption - The market for LiDAR is growing, with over 66.7 million units of L3 and below intelligent auxiliary driving models sold, and 60% of these models equipped with LiDAR [7] - The price of LiDAR has been decreasing, with some products expected to drop to $200, making them more accessible for mass production [7] - Despite the growth of pure vision technology, the reliance on high-performance chips from foreign manufacturers poses a challenge for the development of this path in the future [6][7]

Core Viewpoint - The article discusses the ongoing debate between the use of LiDAR and pure vision systems in autonomous driving, highlighting the differing perspectives of industry leaders like Uber's CEO Dara Khosrowshahi and Tesla's Elon Musk regarding the safety and effectiveness of these technologies [1][2][6]. Group 1: Industry Perspectives - Uber's CEO supports LiDAR for its lower cost and higher safety, while Musk criticizes it, claiming that sensor competition reduces safety [1][2]. - Baidu, a significant player in the autonomous driving sector, advocates for LiDAR, asserting it ensures driving safety and has cost advantages [2][14]. - The article emphasizes the division in the industry, with Waymo and Baidu favoring multi-sensor fusion (including LiDAR) and Tesla sticking to a pure vision approach [6][11]. Group 2: Technical Analysis - Tesla's transition from LiDAR to a pure vision system was driven by cost considerations and the belief that AI can surpass human driving capabilities using camera data alone [8][9]. - Waymo employs a multi-modal approach, integrating LiDAR, radar, and cameras, achieving L4-level autonomous driving and expanding its services in complex urban environments [11][12]. - Baidu's autonomous driving service, "萝卜快跑," utilizes a multi-sensor fusion strategy, combining LiDAR, cameras, and radar to achieve L4 capabilities, with a strong safety record [14][16]. Group 3: Performance Comparison - LiDAR systems provide high-precision 3D environmental perception, unaffected by lighting conditions, while pure vision systems struggle in adverse weather and lighting [48][49]. - The article outlines the advantages of LiDAR in terms of distance measurement accuracy, environmental adaptability, and reliable identification of static objects, contrasting these with the limitations of pure vision systems [50][51]. - LiDAR's ability to maintain performance in extreme conditions, such as heavy rain or fog, is highlighted as a critical safety feature for autonomous vehicles [34][36]. Group 4: Market Trends and Regulations - The article notes that the decreasing cost of LiDAR technology is making it more accessible for widespread adoption in high-end vehicles, with significant market players integrating it into their models [25][42]. - Regulatory frameworks are increasingly favoring the use of LiDAR in autonomous vehicles, with new standards requiring advanced sensing capabilities that LiDAR can provide [55][56]. - The collaboration between Baidu's "萝卜快跑" and Uber to deploy autonomous vehicles globally indicates a growing acceptance of multi-sensor fusion solutions in the market [18].

Core Viewpoint - The debate between pure vision and LiDAR technology for autonomous driving continues, with no clear resolution expected by 2027, as both technologies gain supporters and evolve in capabilities and costs [2][5][10] Group 1: Technology Adoption - Both pure vision and LiDAR technologies have gained significant traction, with various automakers adopting either approach. New entrants and established companies are increasingly choosing sides, with some switching from LiDAR to pure vision [2][3] - Recent models like the Tank 500 and Li Auto i8 have adopted LiDAR, while companies like Xiaomi and Audi are also integrating LiDAR into their vehicles [2][3] - Conversely, companies like Xiaopeng and NIO are firmly committed to pure vision technology, with Xiaopeng's models like the MONA M03 and the new P7 exclusively using this approach [4][5] Group 2: Market Trends - The market for LiDAR-equipped vehicles is expanding, with significant growth in the number of LiDAR units delivered in China, reaching 1.0439 million units in the first half of the year, a year-on-year increase of 83.14% [3] - LiDAR is no longer limited to high-end models, as companies like Leap Motor and Changan are introducing LiDAR-equipped versions in the lower price segments [3] Group 3: Cost and Safety Debate - The ongoing debate between the two technologies centers on cost and safety. Pure vision systems are seen as more cost-effective and easier to scale, while LiDAR is favored for its superior performance in extreme conditions [5][6] - The cost of LiDAR has significantly decreased, with prices for L2-level LiDAR now around $200, down from previous prices of $20,000 to $30,000, representing a reduction of over 99.5% [5][9] Group 4: Future Outlook - Experts suggest that both technologies will likely coexist, with pure vision being sufficient for urban commuting and LiDAR providing safety redundancy in complex scenarios [10] - The advancement of computing power and algorithms is expected to enhance the capabilities of pure vision systems, potentially making them the preferred choice for many automakers [8][9]

Core Viewpoint - The development of intelligent driving technology has become a significant indicator of automotive companies' capabilities, but it has also led to industry chaos and safety incidents, prompting regulatory bodies to enhance safety standards [2][3] Group 1: Industry Challenges - The industry faces three main bottlenecks: technical issues, testing and inspection challenges, and ecosystem deficiencies [3] - Technical challenges include the ongoing debate between vision-based and LiDAR-based solutions, which distracts companies and affects performance in complex scenarios [3] - The lack of clear standards for assisted driving levels leads to marketing exaggerations, causing misuse by consumers [3] - Testing resources are fragmented, with companies duplicating efforts in building testing facilities, leading to inefficiencies [4] - The traditional testing methods are inadequate for the needs of intelligent connected vehicles, necessitating the development of new technologies [4] Group 2: Regional Development and Investment - The East China region, as a major automotive cluster, accounts for over 35% of the national automotive industry, with cities like Shanghai and Suzhou at its core [5] - China Automotive Research Institute (CARI) is investing over 2.3 billion yuan to establish a headquarters in Suzhou, aiming to support the automotive industry's high-end, intelligent, and green upgrades [5][6] - The headquarters will feature over 1,000 advanced R&D and testing facilities, providing comprehensive support across the automotive supply chain [6] Group 3: Collaborative Ecosystem - CARI's headquarters aims to create a collaborative ecosystem involving local governments, testing institutions, and enterprises to enhance the automotive industry's development [7][8] - The establishment of the "Suzhou New Energy Vehicle Public Service Platform" will provide integrated testing and certification services, promoting high-quality development in the intelligent connected vehicle sector [8] - Collaboration with universities and technology companies is emphasized to accelerate research and innovation in key areas such as vehicle-grade chips and intelligent driving systems [9][10]

Core Viewpoint - The competition between lidar and pure vision systems in the automotive industry is intensifying, with more companies shifting towards pure vision technology for advanced driver assistance systems (ADAS) [2][3][5] Group 1: Technology Comparison - Companies like Xiaomi are equipping their vehicles with lidar, while others like Xpeng are adopting pure vision systems for their ADAS [2] - Xpeng's senior director argues that the long-range detection capability of lidar is a "false proposition" due to its technical limitations, such as energy decay and point cloud density [3] - Lidar's performance is significantly reduced in adverse weather conditions, with effective detection range dropping to under 30 meters during heavy rain, while pure vision systems show better performance in similar conditions [4] Group 2: Cost and Market Dynamics - The primary reason for the shift to pure vision systems is cost-effectiveness, as they are significantly cheaper than lidar systems [5] - Xpeng's MONA M03 MAX is the first model to offer full-featured intelligent driving assistance at a price point below 150,000 yuan (approximately 22 million USD) [5] - The competition in the automotive market is pushing companies to adopt more affordable solutions to equip mid-range vehicles with ADAS capabilities [9] Group 3: Future Trends - The trend is moving towards a combination of pure vision and lidar systems to leverage the strengths of both technologies, especially for high-end models [9][10] - Companies are increasingly focusing on the integration of AI algorithms and self-developed chips to enhance the performance of pure vision systems [6][10] - The ultimate goal for autonomous driving technology is a multi-sensor fusion system that combines cameras and lidar to achieve a comprehensive solution [10]