Group 1 - The core viewpoint of the article emphasizes the need for clear communication and regulation regarding the distinction between assisted driving and autonomous driving in the context of smart connected electric vehicles [1][3][5] - Recent regulatory efforts have focused on enhancing the recall and supervision of smart connected electric vehicle products, particularly concerning the safety and usage instructions for combined driving assistance systems [1][4] - The rapid development of smart driving technology has led to consumer confusion, as marketing often blurs the lines between assisted and autonomous driving capabilities [1][2][3] Group 2 - There is a significant gap in consumer education regarding smart driving technologies, with many users unable to discern the true capabilities and limitations of these systems [3][5] - The Ministry of Industry and Information Technology (MIIT) has proposed the establishment of mandatory national standards for the safety requirements of combined driving assistance systems, reflecting a push for more conservative marketing practices in the industry [5][4] - Safety remains the primary concern for consumers, necessitating a cautious approach to marketing that avoids exaggeration and misinformation about smart driving technologies [6][1]

证 券 研 究 报 告 汽车行业周报（20250811-20250817） 行业研究 汽车 2025 年 08 月 17 日 推荐（维持） 8 月上旬折扣环比微升，下半年销量展望乐观 | 华创证券研究所 | | | | --- | --- | --- | | 证券分析师：张程航 | 证券分析师：夏凉 证券分析师：李昊岚 | 联系人：张睿希 | | 电话：021-20572543 | 电话：021-20572532 邮箱：lihaolan@hcyjs.com | 邮箱：zhangruixi@hcyjs.com | | 邮箱：zhangchenghang@hcyjs.com | 邮箱：xialiang@hcyjs.com 执业编号：S0360524010003 | | | 执业编号：S0360519070003 | 执业编号：S0360522030001 | | | | 8 月上旬延续 7 月淡季状态，新能源增速强于燃油车，我们维持对下半年量价乐观的预 | | | | 期。市场对明年政策变化有一定预期，下半年行情已经开始提前演绎。 | | | | 投资角度，结合明年弱 beta 预期、潜在油车反转预期以及估值位置 ...

"天神之眼"、全程脱手零接管、一站式泊车、端到端模型……各种各样的新词层出不穷，而每一个都可 能成为企业在激烈市场竞争中的卖点。 智驾是其中最热的卖点，也是争议最大的一项。辅助驾驶发展如火如荼，其前景是经过逐步迭代，实现 自动驾驶，避免交通事故。 现实情况却是，在消费者并未完全弄懂L2/L3等层次差别以及当前行业普遍所能及的水平，企业口中 的"智能驾驶"，车辆行驶中的辅助驾驶功能，传到消费者耳中经常就变成"自动驾驶"了。 近日，有关部门针对加强智能网联新能源汽车产品召回、生产一致性监督管理与规范宣传发布通知，向 社会公开征求意见。 最引人关注的是有关辅助驾驶与自动驾驶的说明。其中提到，企业应当在车辆App、车载信息中显示组 合驾驶辅助系统的安全提示和使用说明，避免驾驶员将组合驾驶辅助功能视为自动驾驶使用。 在新能源智能车发展的滚滚洪流中，每一项技术更新，都曾一度让市场兴奋不已。车企借机打出五花八 门的宣传牌，消费者会很容易感受到不同功能的迷惑性。 智能驾驶不是模糊概念的万金油话术，辅助驾驶与自动驾驶的区别，更不能在营销的取向下，以安全为 代价。 新能源车在过去几年突飞猛进地发展，除了带来全新的驾驶体验和运营模 ...

Core Viewpoint - The article highlights significant developments in the lithium battery and energy storage sectors, showcasing various companies' investments, partnerships, and technological advancements that are shaping the industry's future [6][10][11][14][19]. Group 1: Industry Events and Collaborations - The 8th Sodium Battery Summit and the 3rd Sodium Battery Anode and Cathode Materials Summit will be held on August 28, 2025, in Shenzhen, with over 500 participants expected [4]. - EVE Energy has entered a deep collaboration with Vbot to advance the mass production of embodied intelligent products [6]. - Zhongqi New Energy signed a memorandum for a 5GWh energy storage battery project with IndiGrid, marking a significant entry into the Indian energy storage market [9]. Group 2: Company Developments and Investments - Juhua Lithium Energy has initiated a lithium battery cell production base project in Tongshan, Hubei, with a total investment of 1.8 billion yuan [7][8]. - Double-Deng Co. is set to list on the Hong Kong Stock Exchange, with projected revenues of 4.26 billion yuan and 4.499 billion yuan for 2023 and 2024, respectively [10]. - Ganfeng Lithium has established a new company focused on battery manufacturing and recycling, indicating a strategic move in the battery supply chain [17][35]. Group 3: Technological Advancements - Researchers have developed lithium-ion batteries with energy densities exceeding 600Wh/kg, significantly improving performance metrics [13]. - A new high-temperature coating system has been launched to enhance battery manufacturing efficiency [32][33]. Group 4: Market Expansion and Production Capacity - Yichun Guoxuan's new project is expected to reach a production capacity of 30GWh annually, contributing significantly to the lithium battery market [20]. - Wanrun New Energy has completed a 120,000-ton lithium iron phosphate project in Shandong, responding to strong downstream demand [22][23]. - The establishment of a 40,000-ton anode material project by Gansu Ruizhi New Materials is underway, with a total investment of 6.6 billion yuan [27]. Group 5: Strategic Partnerships and Agreements - Chuangneng New Energy signed a strategic cooperation agreement with Shanshan Technology for over 10 billion yuan in anode material procurement [19]. - Envision signed agreements with multiple leading energy storage companies, marking a significant expansion in its market presence [14]. Group 6: Regulatory and Environmental Initiatives - Japan plans to enforce mandatory recycling of lithium batteries in smartphones and other devices starting in 2026, reflecting a growing emphasis on sustainability [37][38]. - A new battery recycling project in Henan aims to process 30,000 tons of used lithium batteries annually, focusing on material recovery [40].

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15个 方向 学习 路线 智能驾驶已经进入到了拼技术、拼成本的关键期。24年很多智驾公司没能挺过来，今年大环境稍微好了一些，但从业壁垒也越来越高。。。 最近一位工作六年的星友跟我说公司不打算续签了，想咨询下未来就业的建议。 柱哥好。我19年硕士毕业（普本985硕），在一家中小厂智驾公司工作到现在，公司最近通知我不续签了。所以来请教您~ 之前主要负责的是规划控制C++工程相关。平时在苏州上班，偶尔也会跑下上海，主要觉得苏州也没那么卷所以也苏州安家了。现在还有一段时间准备找工作， 能留苏州还是尽量留在苏州，逼不得已也可以考虑上海或者杭州。想请教您几个问题： （向峰哥和柱哥提问，欢迎加入 『自动驾驶之心知识星球』 ） 星主答： 智能驾驶已经熬过最艰难的时期，去年很多公司都没挺过来，但同时也有不少公司找到了自己的出路，像小鹏现在的形势就好了很多。价格战最近被国家叫停 了，但整体上业内还是很卷的，规控自从端到端量产后，确实受到了一定程度的冲击。 针对你的问题： "规控现在好转行么，还是说您建议继续做规则方向的后处理？" 1. 规控现在好转行么， ...

Core Viewpoint - The article discusses the challenges and advancements in the deployment of Visual-Language-Action (VLA) models in autonomous driving, emphasizing the integration of 3D spatial understanding with global semantic comprehension. Group 1: Challenges in VLA Deployment - The difficulties in deploying VLA models include multi-modal alignment, data training, and single-chip deployment, but advancements in new chip technologies may alleviate these challenges [2][3][5]. - The alignment issue between Visual-Language Models (VLM) and VLA is gradually being resolved with the release of advanced models like GPT-5, indicating that the alignment is not insurmountable [2][3]. Group 2: Technical Innovations - The VLA model incorporates a unique architecture that combines 3D local spatial understanding with 2D global comprehension, enhancing its ability to interpret complex environments [3][7]. - The integration of diffusion models into VLA is a significant innovation, allowing for improved trajectory generation and decision-making processes [5][6]. Group 3: Comparison with Competitors - The gradual transition from Level 2 (L2) to Level 4 (L4) autonomous driving is highlighted as a strategic approach, contrasting with competitors who may focus solely on L4 from the outset [9][10]. - The article draws parallels between the strategies of different companies in the autonomous driving space, particularly comparing the approaches of Tesla and Waymo [9][10]. Group 4: Future Developments - Future iterations of the VLA model are expected to scale in size and performance, with potential increases in parameters from 4 billion to 10 billion, while maintaining efficiency in deployment [16][18]. - The company is focused on enhancing the model's reasoning capabilities through reinforcement learning, which will play a crucial role in its development [13][51]. Group 5: User Experience and Functionality - The article emphasizes the importance of user experience, particularly in features like voice control and memory functions, which are essential for a seamless interaction between users and autonomous vehicles [18][25]. - The need for a robust understanding of various driving scenarios, including complex urban environments and highway conditions, is crucial for the model's success [22][23]. Group 6: Data and Training - The transition from VLM to VLA necessitates a complete overhaul of data labeling processes, as the requirements for training data have evolved significantly [32][34]. - The use of synthetic data is acknowledged, but the majority of the training data is derived from real-world scenarios to ensure the model's effectiveness [54]. Group 7: Regulatory Considerations - The company is actively engaging with regulatory bodies to ensure that its capabilities align with legal requirements, indicating a proactive approach to compliance [35][36]. - The relationship between technological advancements and regulatory frameworks is highlighted as a critical factor in the deployment of autonomous driving technologies [35][36].

重庆"萝卜快跑"无人驾驶出租车载人坠沟事件带来的舆论冲击还未褪去，近日又传出"武汉高架桥上法 拉利自燃，后方萝卜快跑无人驾驶出租车直冲到跟前才识别换道"的视频。 尽管"萝卜快跑"官方客服在坠沟事件后声称："安全是我们萝卜快跑无人驾驶乘用车第一准则。目前商 业化试点总营运里程已超过1亿公里，从未发生责任事故。"但事实是，去年7月，其车辆在武汉街头就 发生了与行人相撞的事故；2023年7月，在变道时与后方车辆发生剐蹭。 萝卜快跑一个月内接连两次发生事故，将整个无人驾驶行业再次推到舆论的风口浪尖。 今年7月底，萝卜快跑在佛山启动试运营，一批本地自媒体博主与南方财经记者亲身体验时，也遭遇行 驶途中突然停车、呼叫无应答、导航不精准等状况。 真实场景中频现"技术失灵"，暴露出萝卜快跑的技术成熟度与大规模商业化落地的要求之间，仍存在差 距；也暴露出无人驾驶行业面临的共性矛盾——当商业化扩张速度远超技术安全冗余度时，Robotaxi是 否有必要"狂奔"入场？ 频现"技术失灵" 7月16日，佛山市交通运输局发布《关于智能网联汽车远程示范应用区域、时段的公告（第一批）》， 公告萝卜快跑（佛山）科技有限公司智能网联汽车远程示范应用 ...

Core Insights - The meeting focused on accelerating the construction of a modern industrial system through technological innovation, emphasizing the integration of technology and industry as a key driver for development [1][2][3] Group 1: Technological Innovation - Technological innovation is identified as the driving force and key variable in building a modern industrial system, essential for transforming old and new growth drivers and addressing industrial transformation challenges [1][2] - Guangdong aims to lead in overcoming critical technological challenges and producing significant technological achievements, with a focus on enhancing supply chains and implementing the "Zhuo Yue" plan for basic research [2] Group 2: Industry Collaboration - The strategy includes strengthening the collaboration between enterprises, academia, and research institutions, utilizing a "chain leader" approach to foster a robust ecosystem of technology-driven enterprises [2] - The government is encouraged to refine policies and support mechanisms to ensure that innovation efforts are effectively delivered to enterprises, enhancing their capacity for technological advancement [3] Group 3: Future Technology and Talent Development - There is a forward-looking emphasis on quantum technology and other future fields, aiming to position Guangdong as a leader in new industries and competitive arenas [2] - The meeting highlighted the importance of cultivating a high-level talent ecosystem through joint training programs between universities and enterprises, ensuring a steady supply of skilled professionals [2]

Group 1 - YingShi Innovation's founder Liu Jingkang apologized for a viral video showing cash being thrown at employees during a team-building event, clarifying it was meant to celebrate the launch of their A1 drone after extensive overtime work [3] - Weibo's official account denied rumors about IP location being precise to the city level, emphasizing that the platform's IP location display aims to reduce impersonation and misinformation [5] - DeepSeek's reported $700 million Series C funding was labeled as false by multiple investors, with claims that the company had not previously raised funds before entering this round [6] Group 2 - Xia Haijun, former CEO of Evergrande, was reported to be hiding in California, with evidence showing his wife holds assets worth $24 million in the U.S. [11][14] - JD.com completed the acquisition of Hong Kong's Jia Bao supermarket, aiming to enhance its supply chain and retail presence in the Greater Bay Area [15] - Meta's market capitalization surpassed $2 trillion for the first time, making it the sixth U.S. company to reach this milestone [21] Group 3 - WeChat denied rumors about a palm payment service franchise, stating it is still in the internal testing phase and warning users against scams [17] - Amazon founder Jeff Bezos's mother passed away at 78, with her early investment in Amazon contributing to the family's wealth [19] - Tencent Cloud launched CloudBase AI CLI, a tool that can reduce coding workload by 80% for developers [28] Group 4 - The National Bureau of Statistics reported significant growth in the manufacturing value of smart drones and vehicle equipment, with increases of 80.8% and 21% respectively in July [30] - Li Lai announced a $1.3 billion deal with AI pharmaceutical company Superluminal to accelerate drug development for obesity and heart diseases [26] - WeRide secured a multi-million dollar investment from Grab to deploy L4 Robotaxis in Southeast Asia [27]

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15个 方向 学习 路线 扩散模型作为生成式AI的重要技术，近年来在自动驾驶领域展现出广泛的应用前景。该模型凭借其强大的 多模态建模能力，能够从复杂数据分布中生成多样性强、符合物理约束的结果，为自动驾驶系统提供新的 解决方案。 总结来说，扩散模型在自动驾驶领域可显著提升数据多样性、增强感知系统鲁棒性，并有效辅助决策模块 处理各类不确定性，为下一代自动驾驶技术发展提供重要支撑。可以说扩散模型已经成为自动驾驶基础模 型重要的一环，今天自动驾驶之心就为大家总结一下扩散模型在自动驾驶基础模型中的相关工作，本文全 部文章已汇总至 『自动驾驶之心知识星球』 ，欢迎加入和我们一起打造自动驾驶的未来~ 在感知层面，基于扩散模型的三维占用预测方法显著优于传统判别方法，尤其在处理遮挡或低可见度区 域时表现突出，生成的占用特征能有效支持下游规划任务。 同时，条件扩散模型被应用于驾驶场景的 精准图像翻译，帮助系统更好地理解和适应各种道路环境。 在预测与决策方面，稳定扩散模型可高效完成车辆轨迹预测任务，生成高精度的其他车辆运动轨迹预测 结果，显著提升自动驾驶系 ...