Core Viewpoint - Shanghai aims to achieve a GDP growth rate of around 5% for 2025, with a focus on enhancing its status as an international economic, financial, trade, shipping, and technological innovation center [3][5][12]. Group 1: Economic Goals and Projections - The main expected economic targets for Shanghai in 2025 include a GDP growth of approximately 5%, a 2% increase in local public budget revenue, and R&D expenditure reaching 4.6% of GDP [3][12]. - The "15th Five-Year Plan" outlines an average annual GDP growth target of around 5%, with potential growth levels estimated between 4.6% and 5.2% [3][12]. Group 2: Development of the "Five Centers" - The report emphasizes the continuous enhancement of the "Five Centers," which include international economic, financial, trade, shipping, and technological innovation centers [5][7]. - Specific initiatives include supporting industries such as smart connected vehicles, marine economy, low-altitude economy, aerospace, and satellite internet [5][11]. Group 3: New Quality Productivity - The focus is on integrating technological and industrial innovation to foster new quality productivity, including accelerating the application of major technological achievements and promoting intelligent, green, and integrated industrial development [9][10]. - Shanghai's R&D expenditure as a percentage of GDP reached approximately 4.5% in 2025, with significant growth in key industries like integrated circuits, biomedicine, and artificial intelligence [9][10]. Group 4: Modern Industrial System - The "2+3+6+6" modern industrial system aims to establish a world-class high-end industrial cluster, with a focus on traditional industry transformation and the development of three leading industries: integrated circuits, biomedicine, and artificial intelligence [10][13]. - By 2030, the plan targets that the total output value of strategic emerging industries will account for over 50% of the total industrial output value [12][13]. Group 5: Future Industry Layout - The report highlights the importance of forward-looking layouts in future industries, including quantum technology, brain-computer interfaces, and bio-manufacturing, to enhance Shanghai's competitive edge [14][12]. - The establishment of a reasonable investment mechanism for manufacturing and the promotion of collaboration between industry, academia, and research in emerging fields are emphasized [14][13].

2026.02. 03 本文字数：1990，阅读时长大约3分钟 作者 | 第一财经 金叶子 具体包括加快重大科技成果高效转化应用；推进产业智能化、绿色化、融合化发展；一体推进教育科技人才发展几个方面。 例如，深化科技成果全部赋权改革，支持概念验证平台、中试平台、高质量孵化器提升服务能级。深入实施"人工智能+"行动，加强算力设施、行业语 料、垂类模型等布局建设，推动新一代智能终端、智能体等广泛运用，加快重点产业智能化改造，新增50家以上先进智能工厂。 2025经济总量位居全球城市第五的上海，划定新一年的发展目标。 上海市第十六届人大四次会议2月3日上午开幕。上海市市长龚正作《政府工作报告》（下称"报告"）。 报告称，建议今年全市经济社会发展的主要预期目标，是全市生产总值增长5%左右，地方一般公共预算收入增长2%，全社会研发经费支出相当于全市 生产总值的比例达到4.6%左右，城镇调查失业率5%以内，居民人均可支配收入增长与经济增长保持基本同步。 关于今年科技和产业工作的重点，报告提出，在2026年主要任务"持续提升 '五个中心'能级"方面，深化国际经济中心建设。积极支持智能网联新能源汽 车、海洋经济、低空经济、航 ...

2025经济总量位居全球城市第五的上海，划定新一年的发展目标。 支持智能网联新能源汽车、海洋经济、低空经济、航空航天、卫星互联网等产业发展。 而"着力推进科技创新和产业创新深度融合，培育发展新质生产力"，也是今年的主要任务之一。 对于今年重点任务中的智能网联新能源汽车、海洋经济、低空经济、航空航天、卫星互联网等产业，上 海也陆续出台了相关文件。 具体包括加快重大科技成果高效转化应用；推进产业智能化、绿色化、融合化发展；一体推进教育科技 人才发展几个方面。 例如，深化科技成果全部赋权改革，支持概念验证平台、中试平台、高质量孵化器提升服务能级。深入 实施"人工智能+"行动，加强算力设施、行业语料、垂类模型等布局建设，推动新一代智能终端、智能 体等广泛运用，加快重点产业智能化改造，新增50家以上先进智能工厂。 刚过去的2025年，上海全社会研发经费支出相当于全市生产总值的比例达到4.5%左右。集成电路、生 物医药、人工智能三大先导产业规模突破2万亿元。新建7家高质量概念验证平台和6家高质量孵化器， 技术合同成交额达到6496.8亿元、增长24.9%，全市日均新增科技企业超过320家。 根据此前公布的 "十五五"规划 ...

Group 1 - The article discusses the recent policy measures issued by Guangdong province aimed at promoting high-quality development in transportation through artificial intelligence [4][5] - The policy encourages enterprises to focus on core technology breakthroughs and innovation in areas such as end-to-end remote driving, intelligent decision-making, and precise prediction and control [4][5] - The initiative aims to create high-quality data sets, toolchains, and algorithm libraries to facilitate the application of large models in autonomous driving [4][5] Group 2 - The article lists various companies involved in the development of key technologies related to autonomous driving, including 威帝股份, 凯众股份, and 大华股份 [6] - It highlights the importance of advanced systems such as steer-by-wire systems, vehicle-mounted cameras, and heads-up displays (HUD) in the context of intelligent driving [6]

Core Viewpoint - The "Mosu Zhixing" action plan aims to accelerate the transformation of intelligent connected technology innovation into industrial competitiveness, promoting the commercialization of high-level autonomous driving in Shanghai [1][3]. Group 1: Action Plan Overview - On January 7, 2023, three departments in Shanghai jointly issued the "Mosu Zhixing" action plan to seize opportunities in automotive intelligence development and foster a new ecosystem for intelligent connected vehicles [1]. - The plan emphasizes a model-driven approach, application demonstration, industrial collaboration, and policy support to advance the construction of the leading area for high-level autonomous driving [1][3]. Group 2: 2027 Goals - By 2027, China aims to establish a globally leading high-level autonomous driving area, with L4 technology implemented in rental and heavy truck scenarios, achieving over 6 million passenger trips and over 800,000 TEU in cargo [2]. - The plan includes the establishment of a digital twin training platform, with 2,000 square kilometers of open testing areas and over 5,000 kilometers of roads covering various scenarios [2]. Group 3: Diverse Application Scenarios - The action plan promotes the simultaneous advancement of passenger vehicles, commercial vehicles, and unmanned equipment [2]. - In the passenger vehicle sector, there will be organized intelligent taxi demonstration operations and pilot projects for L3 vehicles, while commercial vehicles will focus on technology applications in key urban areas and transport hubs [2]. Group 4: Innovation Ecosystem and Policy Support - The plan calls for the Shanghai Economic and Information Commission to advance key technology breakthroughs, cultivate quality enterprises, and promote collaboration in intelligent driving model research [3]. - It emphasizes the need for comprehensive support through policies, finance, talent, and regional collaboration to facilitate the development of the intelligent connected vehicle industry [3].

Core Viewpoint - Shanghai aims to accelerate the construction of a leading area for high-level autonomous driving by fostering industry-leading autonomous driving models and implementing the "Mosu Zhixing" action plan by 2027 [2][3] Group 1: Action Plan Overview - The action plan outlines the goal of achieving large-scale implementation of high-level autonomous driving applications by 2027, forming a competitive smart connected vehicle industry cluster [2] - The plan includes the exploration of innovative business models for L4-level autonomous driving technology in scenarios such as smart buses, taxis, and heavy trucks, with an open area of 2000 square kilometers and over 5000 kilometers of roads designated for autonomous driving [2][3] - The production ratio of new vehicles with combination driving assistance (L2) and conditional autonomous driving (L3) features is expected to exceed 90%, with L4 autonomous vehicles achieving mass production [2] Group 2: Infrastructure and Testing - Shanghai has opened 3173 testing roads with a total length of 5238.82 kilometers, covering about one-third of the city's area, with full-area openness in the Pudong New Area [3] - The city plans to gradually expand the autonomous driving open areas, focusing on key locations such as the Hongqiao hub, Pudong Airport, and Disneyland [2][3] Group 3: Data and Technology Development - The autonomous driving industry is currently in a "data-driven" phase, facing challenges such as high costs and difficulties in obtaining training data, insufficient scene distribution, and inadequate model testing [4] - Shanghai is promoting data sharing applications to support the training and iteration of benchmark intelligent driving models, including the deployment of data collection vehicles and the establishment of a secure data sharing mechanism [4] - A digital twin training ground for autonomous driving will be built, utilizing both real data collection and virtual generation to accumulate high-quality training datasets [4]

Core Viewpoint - The article discusses the significant policy boost for the autonomous driving sector in Shanghai, highlighting the "Mosu Zhixing" action plan aimed at accelerating the transformation of autonomous driving technology into industrial competitiveness [1][2]. Group 1: Action Plan Overview - The "Mosu Zhixing" action plan outlines a strategy based on "model-driven leadership, application demonstration, industrial collaboration, and policy support" to promote innovation in autonomous driving technology [2]. - The plan includes nine key tasks across three main areas: promoting the application of autonomous driving equipment, enhancing data monitoring platforms, and expanding open areas for autonomous driving [2][3]. Group 2: Goals and Targets - By 2027, the plan aims for large-scale implementation of high-level autonomous driving scenarios, with public service platforms supporting industry innovation and achieving international leadership in key technologies and industrial scale [3]. - The plan targets over 6 million passenger trips and more than 80,000 TEU in cargo transport through L4-level autonomous driving technology in smart public transport, taxis, and heavy trucks [5]. Group 3: Infrastructure and Ecosystem Development - The action plan emphasizes the establishment of a digital twin training ground for autonomous driving and aims to create a comprehensive industrial ecosystem covering vehicles, components, data, maps, safety, and services [5][9]. - It proposes to expand the autonomous driving open area to 2,000 square kilometers, with over 5,000 kilometers of roads featuring diverse types and scenarios [5]. Group 4: Financial and Innovation Support - The plan encourages social capital investment in smart connected vehicles and key component startups, supporting quality enterprises in accessing multi-tiered capital markets [5]. - It also highlights the need for innovative insurance products that align with the advancements in autonomous driving technology [5][7]. Group 5: Industry Collaboration and Technology Development - The action plan calls for deepening commercial vehicle demonstration scenarios and advancing the operational model from "platooning with human oversight" to "fully unmanned" operations [7]. - It aims to foster collaboration between universities, research institutions, and key enterprises to accelerate the industrial application of cutting-edge technologies like autonomous driving models [9].

Core Viewpoint - The "Mosu Zhixing" Action Plan aims to establish Shanghai as a leading area for high-level autonomous driving by 2027, focusing on technology innovation, application demonstration, and industry collaboration [2]. Group 1: Development Goals - The plan outlines a vision for large-scale implementation of Level 4 autonomous driving applications, targeting over 6 million passenger trips and 80,000 TEU in cargo transport by 2027 [2]. - It aims to create a comprehensive ecosystem for smart connected vehicles, achieving international competitiveness in key technologies and industry scale [2]. Group 2: Key Tasks - **Diverse Application Scenarios**: - Expand passenger vehicle applications through organized smart taxi operations and pilot projects for Level 3 autonomous vehicles [3]. - Enhance commercial vehicle applications in key locations like airports and train stations, transitioning to fully unmanned operations [3]. - Promote the deployment of autonomous equipment in urban inspection, logistics, and municipal services [3]. - **High-Energy Innovation Elements**: - Establish a digital twin training ground for autonomous driving, accumulating extensive data for model training [4]. - Develop a unified data monitoring platform for smart connected vehicles to ensure real-time operational oversight [4]. - Gradually expand open areas for autonomous driving, focusing on major urban zones and transport hubs [4]. - **Innovative Industry Ecosystem**: - Implement key technology research initiatives for advanced hardware and software solutions in autonomous driving [6]. - Build a world-class automotive industry cluster in regions like Pudong and Jiading, focusing on smart connected vehicles and key components [6]. - Strengthen testing and validation capabilities for autonomous systems through dedicated laboratories and simulation technologies [6]. Group 3: Support Measures - **Policy Support**: - Enhance data management mechanisms and establish a comprehensive safety assurance system for autonomous driving [7]. - **Financial Support**: - Encourage investment in startups focused on smart connected vehicles and support established companies in accessing diverse financing channels [7]. - **Talent Development**: - Promote talent acquisition in the smart connected vehicle sector and foster collaboration between enterprises and educational institutions [7]. Group 4: Regional Collaboration - Streamline testing and application management across the city, ensuring data sharing and coordinated operations [8]. - Foster collaboration within the Yangtze River Delta region to enhance testing capabilities and facilitate large-scale applications [8].

Group 1 - The article emphasizes the increasing demand for corporate training and job counseling in the autonomous driving sector, highlighting the need for diverse training programs ranging from technology updates to industry development summaries [2][4]. - There is a notable interest from individuals seeking guidance, particularly those struggling with resume enhancement and project experience [3]. - The company is inviting professionals in the autonomous driving field to collaborate on various initiatives, including technical services, training, course development, and research guidance [4][5]. Group 2 - The primary focus areas for collaboration include roles such as autonomous driving product managers, 4D annotation/data closure, world models, VLA, large models for autonomous driving, reinforcement learning, and end-to-end solutions [5]. - The job description indicates that the training collaboration targets both B-end (enterprises, universities, research institutes) and C-end (students, job seekers) audiences [6]. - Interested parties are encouraged to reach out for further consultation via WeChat [7].