"把纯电和换电做好，根本不用做什么增程。"在2025广州车展上，乐道汽车总裁沈斐直言道。 沈斐坦言目前最大挑战仍是"怎么能够多卖一点车"，核心在于提升品牌知名度和团队组织能力。俞斌补 充，产品层面将持续围绕家庭用户需求迭代，通过例如L90黑骑士版这类特别版车型"保持市场活力"， 而软件层面年底将为所有车主推送端到端智能驾驶升级。 面对越来越多品牌涌入"大三排SUV"赛道并主打增程方案，乐道汽车管理层立场鲜明：不追随眼下火热 的大电池增程路线，而是坚持"可充可换可升级"的纯电体系。乐道产品体验负责人、助理副总裁俞斌从 产品定义周期分析，今天市场产品的差异"代表的是三年前各个车厂做出的判断"。 （文章来源：21世纪经济报道） 沈斐则算了一笔经济账：增程系统增加重量、成本并侵占空间，在充电桩数量已比五六年前增长5-10倍 的今天，为极低频的长途需求常年背负一套系统"对用户来说其实不是很好的体验点"。他提出，换电模 式下，用户可选择一块"合理容量"的电池包，长途时临时升级，这才是"更优的资金使用效率"。目前， L90用户中选择60度标准电池包的比例约占20%-30%。 而针对近期热议的电池安全问题，沈斐提到，乐道用户 ...

Core Insights - The integration of intelligent driving technology is reshaping lifestyles at an unprecedented pace, driven by advancements in artificial intelligence and a unique market environment in China [1][3] - The Chinese intelligent driving industry is transitioning from a phase of rapid growth to one of high-quality development, with regulatory frameworks being strengthened alongside pilot programs for higher-level autonomous driving [3][4] - The rapid adoption of electric vehicles is providing an optimal platform for intelligent driving technologies, creating a virtuous cycle between electrification and intelligence [4][6] Industry Trends - The emergence of cognitive intelligence technologies is transforming intelligent driving from a rule-based tool to a cognitive-driven entity, with new architectures like end-to-end and VLA opening new possibilities for high-level autonomous driving [3][5] - The intelligent driving sector is witnessing a clear focus on L4-level scenario-based applications, with significant investments directed towards areas like unmanned delivery and logistics [6][7] - Key components of the supply chain, such as sensor manufacturers and chip companies, are receiving substantial funding, highlighting their foundational role in the development of autonomous driving [7] Regulatory Environment - The regulatory landscape is evolving, with policies being introduced to facilitate the testing and commercialization of L3-level and above autonomous driving technologies in multiple cities [3][4] - The dual approach of relaxing pilot programs while simultaneously enhancing regulatory frameworks is creating clearer competitive advantages for companies with core competencies [3][4] Investment Landscape - Investment activities in the intelligent driving sector are increasingly concentrated in later-stage financing, indicating a shift from technology validation to large-scale commercial applications [7] - Traditional automotive companies are actively participating in investments to address technological gaps, while collaborations within the supply chain are emerging to build ecological advantages [7] Future Outlook - The competition in intelligent driving is entering a new phase where success will depend on the ability to integrate technology, compliance, and commercialization effectively [9] - The industry is at a historical turning point, with the potential for new industry giants to emerge from the convergence of technology, policy, and market dynamics [8][9]

Core Viewpoint - The discussion highlights the advancements in intelligent driving systems, emphasizing the importance of smooth vehicle control and the integration of human driving data to enhance performance [1] Group 1: Intelligent Driving Technology - The current braking systems often face issues like abrupt stops due to rule interventions, leading to a lack of coherence in the system [1] - By utilizing comprehensive end-to-end learning from experienced human drivers, the occurrence of sudden braking can be significantly reduced, resulting in smoother vehicle control [1] - The company has achieved mass production this year, securing partnerships with over 10 automotive manufacturers for more than 20 vehicle models, indicating a strong market presence [1] Group 2: Future Vision - The company aims to lead the future of Full Self-Driving (FSD) technology with scalable mass production [1] - A slogan has been adopted to convey the vision of entrusting intelligent driving to the company, thereby allowing individuals to reclaim their time and focus on other aspects of life [1]

Investment Rating - The report does not explicitly state an investment rating for the smart driving industry Core Insights - The smart driving industry is experiencing rapid evolution driven by "end-to-end" and "smart driving equity" concepts, with significant growth in both new energy vehicle sales and smart driving functionalities [3][4][9] - The penetration rate of L2-level smart driving in new energy vehicles in China has increased from approximately 7% in 2019 to around 65% by the first half of 2025, indicating a strong correlation between new energy vehicle sales and the adoption of smart driving technologies [9][10] - The smart driving market is projected to exceed 5 trillion yuan by 2030, with a compound annual growth rate driven by technological advancements and increased consumer acceptance [15][16] Summary by Sections 1. "Equity + End-to-End" Accelerating Smart Driving Evolution - The smart driving industry has seen a significant increase in new energy vehicle sales, which has created a positive feedback loop for the adoption of smart driving technologies [9][10] - The penetration of L2-level smart driving features in new energy vehicles has rapidly increased, reflecting the growing consumer acceptance and market expansion of smart driving technologies [9][10] 2. End-to-End Smart Driving Review - The evolution of end-to-end smart driving can be categorized into four main stages, with advancements in perception, decision-making, and control processes [30][32] - The introduction of the "occupancy network" has enhanced environmental perception capabilities, allowing for more accurate and stable decision-making in complex driving scenarios [46][47] 3. VLA Technology Route - The VLA (Vision-Language-Action) model is emerging as a key driver of paradigm shifts in autonomous driving, integrating visual, linguistic, and action modalities into a cohesive framework [70][71] - The VLA model's development is divided into four stages, with significant advancements in task understanding and execution capabilities [76][77] 4. World Model Technology Route - The world model approach emphasizes physical reasoning and spatial understanding, representing a long-term evolution path for smart driving technologies [69][70] - The integration of world models with cloud computing is expected to enhance the iterative optimization of end-to-end smart driving systems [65][66]

Core Viewpoint - The article emphasizes the significance of high computing power, large models, and extensive data in achieving Level 3 (L3) autonomous driving, highlighting the advancements made by XPeng with its G7 model and its proprietary AI chips [3][18][19]. Group 1: Technological Advancements - XPeng's G7 is the world's first L3 level AI car, featuring three self-developed Turing AI chips with over 2200 TOPS of effective computing power [3][18]. - The G7 introduces the VLA-OL model, which incorporates a "motion brain" for decision-making in intelligent assisted driving [4]. - The VLM (Vision Large Model) serves as the AI brain for vehicle perception, enabling new interaction capabilities and future functionalities like local chat and multi-language support [5][19]. Group 2: Industry Positioning - XPeng was the only invited Chinese car company to present at the global computer vision conference CVPR 2025, showcasing its advancements in autonomous driving models [6][13]. - The company has established a comprehensive system from computing power to algorithms and data, positioning itself as a leader in the autonomous driving sector [8][18]. Group 3: Model Development and Training - The next-generation autonomous driving base model developed by XPeng has a parameter scale of 72 billion and has been trained on over 20 million video clips [20]. - The model utilizes a large language model backbone and extensive multimodal driving data, enhancing its capabilities in visual understanding and reasoning [20][21]. - XPeng employs a distillation approach to adapt large models for vehicle-side deployment, ensuring core capabilities are retained while optimizing performance [27][28]. Group 4: Future Directions - The development of a world model is underway, which will simulate real-world conditions and enhance the feedback loop for continuous learning [36][41]. - XPeng aims to leverage its AI advancements not only for autonomous driving but also for AI robots and flying cars in the future [43][64]. - The transition to an AI company involves building a robust AI infrastructure, with a focus on optimizing the entire production process from cloud to vehicle [50][62].

Core Insights - The report focuses on the trends and market dynamics in the fields of intelligent driving and humanoid robots, highlighting the expected explosive growth in advanced driving technologies and the emergence of humanoid robots in commercial applications by 2025 [1][4]. Intelligent Driving - Advanced driving technology is anticipated to enter a phase of explosive growth, with a projected penetration rate exceeding 15% by 2025 and potentially surpassing 70% in the next 2-3 years, significantly altering the automotive landscape [1][4]. - The Robotaxi segment is reaching a critical turning point, with costs expected to align with ride-hailing services by 2025, suggesting a competitive edge for companies like Didi that integrate both self-operated and platform-based models [1][5]. - Key supply chain components such as intelligent driving chips, LiDAR, and sensor cleaning are expected to see substantial growth driven by policy, technology, and market demand, with companies like Horizon Robotics and Hesai Technology leading the way [1][5]. Humanoid Robots - The humanoid robot sector is poised for a breakthrough in mass production by 2025, with economic viability in general commercial scenarios expected by 2027, particularly in high-cost labor markets [1][6]. - The supply chain for humanoid robots is characterized by high-value components such as dexterous hands, lead screws, and sensors, which are becoming core segments due to their high barriers to entry and significant cost reduction potential [1][6]. - The domestic market for lead screws is growing, with a market share exceeding 10% and increasing, driven by the demand for lightweight materials like PEEK in humanoid robots [1][6]. Supply Chain Dynamics - The supply chain for intelligent driving and humanoid robots is evolving, with high-value segments like dexterous hands and lead screws becoming increasingly important due to their cost structure and technological barriers [1][6]. - The report emphasizes the importance of domestic production capabilities in the supply chain, particularly in the context of rising demand for humanoid robots and the need for cost-effective solutions [1][6].

Core Viewpoint - SenseTime's R-UniAD end-to-end autonomous driving solution is set to be unveiled at the Shanghai Auto Show in April, with real vehicle deployment completed and expected delivery by the end of the year [1][3]. Group 1: Company Developments - Wang Junping, former senior director of intelligent driving at Nezha Auto, joined SenseTime's autonomous driving division in February 2023, previously being part of Baidu's intelligent driving team [2]. - SenseTime has been collaborating with Nezha Auto since September 2021, focusing on intelligent driving and smart cockpit technologies [2]. - Wang Weibao, who took over from Shijianping as the head of intelligent driving, joined SenseTime at the end of 2023 and has a background in Apple's autonomous driving team and as CTO at New Stone Unmanned Vehicle Company [3]. Group 2: Industry Context - The autonomous driving sector is experiencing intensified competition, particularly for companies not in the top tier, highlighting the challenges faced by solution providers [3]. - SenseTime collaborates with over 30 automotive companies, including GAC, BYD, Honda, and NIO, with solutions already deployed in models like the Haobo and Nezha's super sedan [3].

以下文章来源于晚点Auto ，作者晚点团队 晚点Auto . 从制造到创造，从不可能到可能。《晚点LatePost》旗下汽车品牌。 目前主要服务北汽、上汽大通等车企。 文丨赵宇 编辑丨 程曼祺 我们独家获悉，智能驾驶供应商易航智能近日完成数亿元 C 轮融资，由北汽产投、浙江金控投资公司、德 清产投、财通资本联合投资。其中，浙江金控投资公司为浙江省级投资平台，德清产投为湖州德清县级投 资平台。 北汽在 2022 年与易航智能达成合作，主打越野车的北汽 BJ40 系列车型已搭载易航智能的 L2 级前视一体 机（集成摄像头等传感器的硬件套件）和 L2+ 级高速 NOA 方案。 易航智能称，本轮融资后，易航智能或将为北汽集团旗下 BEIJING、极狐品牌的车型开发智驾方案。 浙江德清县政府则正在招引智驾项目，打造智能驾驶示范区。蔚来激光雷达供应商图达通的一条产线和港口 无人驾驶公司斯年智驾总部基地已落地德清。 易航智能由陈禹行于 2015 年 8 月创立。他博士毕业于吉林大学车辆工程专业，师从中国工程院院士郭孔辉， 郭孔辉也是空气悬架公司浙江孔辉的前身 "长春孔辉" 的创始人；在美国加州伯克利大学交流期间，陈禹行还 ...

以下文章来源于晚点Auto ，作者晚点团队 晚点Auto . 从制造到创造，从不可能到可能。《晚点LatePost》旗下汽车品牌。 "有了人才之后，其他东西都会有。" 文丨赵宇 张家豪 制图丨黄帧昕 编辑丨 程曼祺 宋玮 "有了人才之后，其他东西都会有。" 一位曾在美国硅谷工作多年的自动驾驶从业者说，自动驾驶是人才密 集型产业。人才的流动直接影响一家公司的发展势头，也指示着整个行业的风向变化。 自动驾驶人才流动的最新一个例子是小鹏向英伟达的 "输血"。自小鹏前自动驾驶副总裁吴新宙去年 8 月加 入英伟达后，12 个月里，至少 6 位小鹏技术人员加入英伟达。 芯片巨头英伟达下场做方案，希望成为垂直整合的智能驾驶 Tier 1（一级供应商）。2023 年下半年，英伟 达也把目光投向了全球智驾人才最丰富、实践经验最多的中国，开始在这里组建智驾方案团队，希望挽救 进展缓慢的智驾业务。 有同样野心的还有高通、地平线等跨界选手。2022 年，高通收购了瑞典智能驾驶技术服务商 Arriver，将 其计算机视觉、驾驶辅助等资产整合进自身业务；地平线则招募了原华为智能驾驶产品部部长苏箐，基于 征程 6 开发高阶智能驾驶方案。 ...