Core Viewpoint - The article emphasizes the need for collaboration and innovation in the autonomous driving industry, highlighting the importance of engaging more talented individuals to address the challenges and pain points in the sector [2]. Group 1: Industry Direction - The main focus areas in the autonomous driving field include but are not limited to: product management, 4D annotation/data loop, world models, VLA, large models for autonomous driving, reinforcement learning, and end-to-end solutions [4]. Group 2: Job Description - The positions are primarily aimed at training collaborations in autonomous driving, targeting both B-end (enterprises, universities, research institutes) and C-end (students, job seekers) audiences for course development and original content creation [5]. Group 3: Contact Information - For discussions regarding compensation and collaboration methods, interested parties are encouraged to add the WeChat contact provided for further communication [6].

Group 1: Industry Overview - The penetration rate of L2 autonomous driving is rapidly increasing, while L3 is on the verge of implementation and L4 is breaking through in scale [2] - The autonomous driving industry is undergoing a new round of reshuffling and resource integration, with some companies exiting the market, others merging or acquiring, and new players emerging [2] Group 2: New Forces in Autonomous Driving - Key new players in the autonomous driving sector include NIO, Xpeng, Li Auto, Xiaomi, Leap Motor, Didi, WM Motor, Niu Chuang, Zeekr, Avita, Lantu, Qianli Technology, and Jiyue [4] Group 3: Tier 1 Suppliers - Major Tier 1 suppliers in the industry consist of Huawei, Baidu, DJI, ZTE, Tencent (smart cockpit/high-precision maps/simulation toolchain), SAIC Lingxu, Jianzhi Robotics, Momenta, Bosch China, Magna, and Youjia Innovation Minieye [6] Group 4: Robotaxi Companies - Companies involved in the Robotaxi segment include Baidu, Pony.ai, Shanghai Zhaofu Intelligent Technology (Hello Robotaxi), WeRide, Didi, Momenta, Qizhou Zhihang, and Yushi Technology [8] Group 5: Robotruck Companies - Key players in the Robotruck sector are Carl Power, Zhijia Technology, Winche Technology, Pony.ai, Mainline Technology, Sien Intelligent Driving, Xijing Technology, Feibu Technology, MuYue Technology (WeRide), Zitu Technology, Changxing Intelligent, Huanyu Zhixing, Xidi Intelligent Driving, Qianhua, Xingxing, Youdao Zhitu, Karui Zhixing, Qianchen, Weidu, Geely Remote, Hengrun, Hongjing, Xidi, and Qingtian Zhika [10] Group 6: Other Autonomous Driving Applications - Companies involved in various applications of autonomous driving include Meituan, Jiushi Intelligent, JD.com, Suning, Alibaba Cainiao, China Post, Baidu Apollo, VIA Technologies, Baixiniu, Zhixingzhe, Yushi Technology, Xingshen Intelligent, Jiazhi Technology, and Xiaoshi Technology [12] - Traditional automakers in the industry include SAIC, Changan, GAC (Aion), BAIC (Extreme Fox), FAW, Great Wall, BYD, Geely (Furuitai), Dongfeng, Chery, and Geely (Zeekr) [14] - Companies focusing on agricultural autonomous driving include Fengjiang Intelligent, Zoomlion, China Yituo, Wuniu Intelligent, Zhongke Yuandong, Leiwo Heavy Industry, Chaoxing Intelligent, Bochuang Liandong, and Haoxing Technology [16] - Companies in the mining autonomous driving sector include Yikong Zhijia, Taga Zhixing, Huituo Intelligent, Lukai Zhixing, Bolai Technology, Mengshi Technology, and Qingzhi Technology [18] - Companies in the sanitation autonomous driving sector include Zhixingzhe, Kuwa, Xiantou, Gaoxian Robotics, Shenlan Technology, Haorui Intelligent, Yuwan Zhijia, and Yunchuang Zhixing [20] - Companies involved in parking solutions include Baidu, Zhuishi, Desai Xiwai, Dongsoft Ruichi, Hedu Technology, Niuli Technology, Hengrun Technology, Lingshi Technology, Moshih Intelligent, Oteming, Zhixingzhe, and Yushi Technology [22] Group 7: High-Precision Mapping - Major players in high-precision mapping include Baidu, Amap, Four-Dimensional Map New, Tencent, Huawei, Didi, JD.com, Meituan, Kuandeng, Shendong, Zhonghaiting, and Yikaton [24] Group 8: Vehicle-to-Everything (V2X) Collaboration - Companies involved in vehicle-to-everything collaboration include Mushroom Car Union, Juefei Technology, Baidu, Huawei, Datang High-Tech, Huali Zhixing, Alibaba, Hikvision, Xingyun Interconnect, and Yunjing Zhixing [24]

L4无人卡车领域迎来重要动态，主线科技（北京）股份有限公司近日正式向港交所递交招股书，开启上市征程。这家成立于 2017年的企业，在自动驾驶卡车赛道持续发力，展现出强劲的发展势头。 | | | | 截至12月31日止年度 | | | | | 截至6月30日止六個月 | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | 2022年 | | 2023年 | | 2024年 | | 2024年 | | 2025年 | | | | 金額 | କ୍ଷ | 슬額 | ్య | 金額 | క్ష | 金額 | କ୍ଷ | 金額 | રહ્યુ | | | | | | | (人民幣千元(除百分比外) | | | | | | | | | | | | | | (未經濟計) | | | | | Trunk Port | 65.826 | 58.6 | 39.980 | 29.8 | 181,894 | 71.6 | 1.932 | 36.0 | 15.910 | 16.1 | | 自動駕駛解決方案銷售 .. | 65.826 | ...

Core Insights - WeRide and Uber have officially launched Robotaxi services in Dubai through the Uber App, supporting Dubai's "2030 goal of 25% automated travel" [1][5] - The Robotaxi service is now available in popular areas such as Umm Suqeim and Jumeirah, enhancing the scale of smart mobility in the Middle East [1][5] Group 1 - WeRide and Uber announced the launch of L4 level fully autonomous Robotaxi commercial operations in Abu Dhabi, marking the first pure autonomous operation in the Middle East [3] - Abu Dhabi is the first city outside the U.S. to offer this service on the Uber platform, receiving the first city-level permit for pure autonomous Robotaxi operations outside the U.S. [3] - The collaboration between WeRide and Uber began in April, involving multiple pilot runs and road tests to ensure a safe transition to practical applications of autonomous driving [3] Group 2 - Dubai's population exceeds 4 million, with a strong demand for transportation, projected to reach 153 million trips in 2024, including a 28% year-on-year growth in shared mobility users [5] - The introduction of Robotaxi services aligns with the increasing travel demands of residents and tourists, providing a crucial boost to Dubai's automation goals [5] - Uber's global head of autonomous driving expressed excitement about the rapid advancement of autonomous driving in the UAE and the Middle East, reaffirming the company's commitment to supporting the region's future mobility vision [5]

迪拜道路交通局（RTA）宣布，Robotaxi现已在Umm Suqeim和朱美拉提供预约服务，用户可在 Uber中选择"Autonomous"即刻下单。当前车辆配有安全员，计划2026年初实现完全无人驾驶。 文远知行表示，其全球验证的自动驾驶技术将支持在中东快速扩张，目标到2030年在全球部署"数 万台Robotaxi"。Uber也称，此次启动体现其加速布局自动驾驶、并与阿联酋未来交通愿景紧密对接。 目前文远知行在中东运营约150辆自动驾驶车辆，其中含100多台Robotaxi。随着迪拜人口突破400 万、共享出行需求在2024年同比增长28%，此次试点被视为迈向2026年全面无人驾驶的重要过渡。 （原标题：迪拜联合 Uber 与文远知行推出 Robotaxi 试点服务） 《Arabian Business》12月12日报道，迪拜首次通过Uber App上线AI无人驾驶Robotaxi试点服务，合 作方为全球自动驾驶公司文远知行（WeRide）。此举是推动迪拜"2030年实现25%自主驾驶出行"目标的 重要一步。 ...

Core Insights - The article highlights the advancements in 3D Gaussian Splatting (3DGS) technology, particularly its application in autonomous driving, and emphasizes the need for structured learning pathways in this rapidly evolving field [2][4]. Group 1: 3DGS Technology and Developments - Tesla's introduction of 3D Gaussian Splatting at ICCV has garnered significant attention, indicating a shift towards feed-forward GS algorithms in the industry [2]. - The rapid iteration of 3DGS technology includes static reconstruction (3DGS), dynamic reconstruction (4DGS), and surface reconstruction (2DGS), showcasing the need for effective learning resources [4]. Group 2: Course Offering - A comprehensive course titled "3DGS Theory and Algorithm Practical Tutorial" has been developed to provide a structured learning roadmap for newcomers, covering essential theories and practical applications [4]. - The course is designed to help participants understand point cloud processing, deep learning, real-time rendering, and coding practices, with a focus on hands-on experience [4]. Group 3: Course Structure - The course consists of six chapters, starting with foundational knowledge in computer graphics and progressing to advanced topics such as feed-forward 3DGS and its applications in autonomous driving [8][9][10][11][12]. - Each chapter includes practical assignments and discussions to enhance understanding and application of the concepts learned [8][9][10][11][12]. Group 4: Target Audience and Prerequisites - The course is aimed at individuals with a background in computer graphics, visual reconstruction, and programming, particularly those interested in pursuing careers in the 3DGS field [17]. - Participants are expected to have a foundational understanding of probability, linear algebra, and programming languages such as Python and PyTorch [17].

以下文章来源于深蓝AI ，作者深蓝学院 深蓝AI . 专注于人工智能、机器人与自动驾驶的学习平台。 作者 | 深蓝学院 来源 | 深蓝AI 原文链接： 南洋理工、哈佛提出OpenREAD：用端到端RL统一驾驶认知与轨迹规划 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 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 本文只做学术分享，如有侵权，联系删文 让视觉语言大模型 同时学会 " 思考 " 与 " 执行 " 」 在自动驾驶研究中，利用大语言视觉语言模型(LLMNLM)学习开放式驾驶知识，进而提升轨迹规划与决策能力，正逐渐成为新的趋势。 然而，传统的监督微调(SFT)范式难以充分挖掘模型的推理潜力，对知识的学习效率也存在不足。DeepSeek-R1的出现向我们展示了强化学习在提升模 型推理与思考能力方面的巨大潜力，使模型具备更强的泛化表现。 因此，一个关键问题随之而来:如何通过强化学习增强视觉语言模型的推理能力，让模型"学会思考"，并在同一框架下同时掌握开放式驾驶知识与轨迹规 划?这正是基于视觉语言大模型实现端到端自动驾驶所面临的全新挑战。 南洋理 ...

Group 1: Regulatory Developments in the Automotive Industry - The State Administration for Market Regulation is seeking public opinion on the "Guidelines for Compliance with Pricing Behavior in the Automotive Industry," which aims to standardize pricing practices from vehicle production to parts manufacturing [1] - The guidelines emphasize full-process price management, requiring a comprehensive pricing management system covering vehicle sales and financial services [1] - The guidelines also prohibit price collusion between producers and parts manufacturers, and mandate clear communication of pricing for paid features to protect consumer rights [1] Group 2: Corporate Governance and Management Changes - Dongfeng Motor Group's former deputy general manager of the Special Equipment Division, Xiao Jinghua, is under investigation for serious violations of discipline and law [2] - Seres announced the resignation of non-executive director You Zheng due to work adjustments, with a new candidate, Yang Yanding, proposed for the board [3] Group 3: Financial and Operational Updates - Seres has completed its "Factory Intelligent Upgrade and Electric Drive Production Line Construction Project," reallocating surplus funds of 19.462 million yuan to the "Electric Vehicle Model Development and Product Platform Technology Upgrade Project" [4] - Dongfeng Commercial Vehicle has set a sales target of 176,000 units for 2026, planning to launch 214 new products across various energy types [5] Group 4: Strategic Partnerships and Technological Advancements - Black Sesame Intelligence and Yuanrong Qixing have signed a cooperation agreement to promote the mass production of advanced driver assistance technologies [6][7] - Uber plans to launch autonomous taxi services in over 10 markets by the end of next year, with ongoing operations in the U.S. and Middle East [7]

12月11日，在小马智行2025媒体沟通会上，小马智行联合创始人、首席财务官王皓俊介绍，小马智行的 Robotaxi（自动驾驶出租车）车队规模从去年的200多辆到今年年底近1000辆，到2026年底会达到3000 辆。关于实现盈利需要多久，王皓俊从小马智行运营情况来看，"预期2030年到10万辆级，所以时间点 应该是在2030年前，公司实现盈亏平衡。"对于投资摩尔线程，王皓俊提到，参与了摩尔线程的早期投 资，当时不是财务投资，更多是战略考虑。 ...

Core Viewpoint - Mainline Technology (Beijing) Co., Ltd. has submitted its listing application to the Hong Kong Stock Exchange, aiming to raise funds for enhancing R&D capabilities, building production and supply chain systems, market expansion, and strategic investments [1][5]. Company Overview - Mainline Technology is a provider of L4 autonomous driving trucks and solutions, recognized as the first in China to commercialize unmanned transport solutions in port scenarios [1][3]. - The company was founded in 2017 by Zhang Tianlei, a PhD from Tsinghua University and a founding member of Baidu's autonomous vehicle team [10][12]. Financial Performance - The company's revenue for the years 2022 to 2025 (first half) is projected to be CNY 112.36 million, CNY 134.11 million, CNY 254.09 million, and CNY 99.92 million respectively, showing significant growth driven by the commercialization of autonomous driving products [5][6]. - The gross profit margin has improved from 3.7% in 2022 to 30.3% in 2025, although the company remains in a net loss position with losses of CNY 278.17 million, CNY 212.63 million, CNY 187.18 million, and CNY 96.4 million over the same period [7][9]. R&D and Market Position - R&D expenditures have been substantial, amounting to CNY 1.47 billion, CNY 1.19 billion, CNY 1.15 billion, and CNY 0.6 billion, representing 131%, 89%, 45.3%, and 60.9% of revenue respectively [9]. - As of December 5, 2025, the company has delivered 830 autonomous trucks and 349 smart terminals, with 821 trucks and 920 terminals on order, positioning it as the largest L4 autonomous truck provider in closed road scenarios in China [6][8]. Business Segments - In 2024, 71.6% of the company's revenue is expected to come from logistics hub operations, while 16.6% will be from highway logistics, and 11.7% from urban traffic [6][8]. - The number of projects executed has increased from 24 in 2022 to 48 in 2024, with 28 projects completed in the first half of 2025 [5].