Core Viewpoint - The Hong Kong Stock Exchange has officially accepted the listing application of Jiadu Technology Group Co., Ltd., a leader in AI-driven smart city transportation solutions in China [1] Group 1: Company Overview - Jiadu Technology focuses on providing a comprehensive range of products and services, including theoretical innovation, technology research, product development, solution application, and integrated services [1] - The company has developed extensive technical capabilities and accumulated vast amounts of real urban traffic data through years of strategic investment and specialized technology and solution development [1] Group 2: Industry Context - The acceleration of global urbanization has led to multiple challenges for traditional transportation systems, including fragmented system construction resulting in data silos, outdated management methods, low management efficiency, high construction and maintenance costs, and insufficient safety and reliability [1] - Traditional transportation products are increasingly unable to meet the demands of modern urban environments, highlighting the need for innovative solutions [1]

Group 1 - The core point of the article is that Jiadu Technology has submitted an application for H-share listing on the Hong Kong Stock Exchange, aiming to enhance its research and development capabilities and expand its global presence in the intelligent transportation sector [1][2] - Jiadu Technology focuses on the urban transportation industry, utilizing advanced technologies such as artificial intelligence, big data, and digital twins to drive intelligent upgrades in urban traffic systems [1] - The company has established two main business systems: smart rail transit and smart city transportation, positioning itself as a leading provider of AI-driven intelligent urban transportation products and solutions [1] Group 2 - The company plans to use the funds raised from the listing to enhance R&D, address customer pain points, and expand into high-value niche markets within the transportation industry [1] - Jiadu Technology aims to strengthen its localized customer management network and promote an integrated construction and operation model [1] - The company is committed to pursuing a global expansion strategy and seeking strategic cooperation and investment opportunities to support its internationalization efforts in AI technology and smart transportation [2]

Core Viewpoint - The transportation sector in China is advancing the development of a standardized intelligent transportation system to support the construction of a strong transportation nation [1][2]. Group 1: Standardization Efforts - The Ministry of Transport has released a draft for the "Intelligent Transportation System Standard System (2025)" for public consultation, aiming to establish a comprehensive framework for standardization in the intelligent transportation sector [1]. - The standardization efforts will focus on various applications, including passenger transport, freight logistics, electronic toll collection, vehicle-road collaboration, autonomous driving, traffic operation monitoring, and smart water transport [1][2]. - The standard system will address key issues in the intelligent transportation field, such as providing information services for safe and convenient travel and monitoring traffic operation status for government and management departments [2][4]. Group 2: Technological Integration - The integration of big data, the internet, artificial intelligence, and blockchain technologies is accelerating within the transportation industry, becoming a significant driver for high-quality development [3]. - Recent years have seen the establishment of standards by domestic and international organizations in areas such as autonomous driving, information interaction, and sustainable development, supporting the expansion of intelligent transportation applications [3][4]. - The rapid development of smart transportation during the "14th Five-Year Plan" period is supported by national policies, emphasizing the need for timely updates to standards in line with technological advancements [3][4]. Group 3: Future Directions - The standardization demand in the intelligent transportation sector is urgent due to the rapid technological iterations, with new technologies and applications requiring timely standard updates [4]. - Future efforts will focus on enhancing the application of advanced information technologies like big data and artificial intelligence in areas such as smart travel, smart logistics, and information security [4].

Core Viewpoint - The article emphasizes the strengthening of advanced information technology applications, such as big data and artificial intelligence, in the transportation sector to support the construction of a strong transportation nation in China [1][4]. Group 1: Standardization in Intelligent Transportation - The Ministry of Transport has released a draft for the "Intelligent Transportation System Standard System (2025)" for public consultation, aiming to establish a comprehensive standardization framework for intelligent transportation systems [1][2]. - The standardization efforts will focus on various areas including passenger travel, freight logistics, electronic toll collection, vehicle-road collaboration, autonomous driving, traffic operation monitoring, and smart water transport [1][2][4]. - The standard system will address key issues in the intelligent transportation sector, such as providing information services for safe and convenient travel and monitoring traffic operation status for government management [2][5]. Group 2: Integration of Advanced Technologies - The integration of technologies like big data, the internet, artificial intelligence, and blockchain is accelerating within the transportation industry, becoming a crucial driver for high-quality development [4][5]. - The standardization organizations are developing standards related to automated driving, information services for travelers, electronic toll collection, and traffic data management, among others [4][5]. - The urgency for standardization in the intelligent transportation field is highlighted due to the rapid technological advancements and the need for timely updates to standards [5]. Group 3: Future Focus Areas - Future efforts will prioritize the standardization of smart travel, smart logistics, digitalization of infrastructure, vehicle-road collaboration, and information security [5]. - The article notes that the average technology iteration cycle in this field is less than 3 to 5 years, indicating a pressing need for updated standards to keep pace with technological advancements [5].

Core Viewpoint - The article discusses the implementation opinions on "Artificial Intelligence + Transportation" issued by the Ministry of Transport and six other departments, aiming to accelerate the innovative application of AI in the transportation sector by 2027 and 2030 [1][4]. Summary by Sections Overall Requirements - By 2027, AI will be widely applied in typical scenarios within the transportation industry, with a comprehensive transportation model system deployed and a number of landmark innovative projects established. By 2030, AI will be deeply integrated into the transportation sector, promoting a smart, comprehensive transportation network [6][7]. Increasing Key Technology Supply - The focus will be on overcoming common technologies such as dynamic scene perception, real-time positioning, and autonomous decision-making. There will be an emphasis on developing smart driving systems and remote driving cockpits, as well as encouraging the development of new equipment like drones and all-terrain vehicles [8][9]. Accelerating Innovation Scene Empowerment - The initiative includes supporting intelligent driving models and enhancing service scenarios in regions like Beijing-Tianjin-Hebei and the Yangtze River Delta. It also covers smart railways, smart shipping, and smart logistics, with specific requirements for optimizing standards and enhancing service quality [10][11][12]. Strengthening Core Element Guarantees - The plan emphasizes optimizing computing power supply, accelerating the construction of high-quality data sets, and promoting the integration of AI with new communication technologies and the Internet of Things [14]. Optimizing Industrial Development Ecology - The document outlines the need to enhance the incubation capacity of the industrial ecosystem, promote the establishment of innovation alliances, and support the development of key laboratories and testing platforms in the AI transportation sector [15][16]. Assurance Measures - The strategy includes government guidance and market leadership, establishing a coordinated development mechanism for AI in transportation, and enhancing safety management and regulatory frameworks [17].

Core Viewpoint - The implementation of artificial intelligence in the transportation sector is being accelerated, with a goal for widespread application by 2027 and deep integration by 2030, aiming to establish a leading position globally in smart transportation and logistics technologies [1]. Group 1: Key Deployments - Accelerate the research and development of intelligent driving systems and remote driving cockpits, particularly in regions like Beijing-Tianjin-Hebei and the Yangtze River Delta [2]. - Encourage the development of new equipment such as drones and all-terrain vehicles [3]. - Promote the opening of urban scenarios and road networks to facilitate the large-scale application of new delivery devices and intelligent delivery services [4][8]. - Establish high-quality datasets, algorithm libraries, and toolchains for the "AI + Transportation" initiative to support the construction of an intelligent comprehensive transportation network [4]. Group 2: Innovation Empowerment - Focus on enhancing key technology supply, accelerating innovation in smart products, and building a comprehensive transportation model to improve the intelligence level of the transportation system [6]. - Deploy seven key tasks across various transportation scenarios, including smart railways and logistics, to create replicable and scalable application cases [7]. - Utilize existing infrastructure like highway ETC gantries to explore multi-sensor integration for improved public travel experiences [7]. Group 3: Optimizing the Innovation Environment - Optimize computing power supply, accelerate the construction of high-quality datasets, and promote the development of ubiquitous network facilities to support AI applications in transportation [9][10]. - Strengthen the integration of computing resources and enhance data sharing among industry, academia, and research institutions [9]. - Establish a transportation big model innovation and industry alliance to foster collaboration among leading AI companies, industry players, and educational institutions [10].

Core Viewpoint - The implementation of artificial intelligence in the transportation sector is being accelerated, with a focus on innovation and application by 2027 and 2030, aiming for a comprehensive integration of AI technologies in transportation systems [2]. Group 1: Key Deployments - Accelerate the research and development of intelligent driving systems and remote driving cockpits, particularly in regions like Beijing-Tianjin-Hebei and the Yangtze River Delta [3]. - Encourage the development of new equipment such as drones and all-terrain vehicles [4]. - Promote urban scenarios and road network openness to facilitate the large-scale application of new delivery devices and intelligent delivery services [5]. Group 2: Enhancing Innovation Scenarios - Leverage the diverse application scenarios in transportation to deploy seven key tasks, including smart railways and intelligent logistics, to create replicable and scalable application cases [11]. - Support the aggregation of innovation resources in key regions and cautiously advance the demonstration application of intelligent driving technologies [11]. - Upgrade postal and express delivery infrastructure to establish an intelligent and efficient delivery network [11]. Group 3: Optimizing the Innovation Environment - Optimize computing power supply capabilities and accelerate the construction of high-quality datasets to support AI applications in transportation [12]. - Promote the integration of AI, next-generation communication, and IoT technologies to develop a comprehensive transportation data transmission network [13]. - Enhance the industrial ecosystem by improving incubation capabilities and establishing a multi-level talent training system [13][14].

来看6大重要部署： 京津冀、长三角辅助驾驶应用提速。 9月26日，交通运输部等七部门印发《关于"人工智能+交通运输"的实施意见》（下称《意见》），加快推 动人工智能在交通运输领域规模化创新应用。 《意见》提出，到2027年，人工智能在交通运输行业典型场景广泛应用，综合交通运输大模型体系落地部 署，普及应用一批智能体，建成一批"人工智能+交通运输"标志性创新工程；到2030年，人工智能深度融 入交通运输行业，智能综合立体交通网全面推进，智慧交通与智慧物流领域关键核心技术自主可控，总体 水平居世界前列。 1.加快智能驾驶系统、远程驾驶座舱等产品研发。支持京津冀、长三角、粤港澳大湾区、成渝地区等地 进一步集聚创新资源，依法依规、稳慎推进智能辅助驾驶技术示范应用。 2.鼓励无人机、全地形车等新装备的研制。 3.鼓励城市加大场景和路网开放，推动新型快递配送设备规模化应用，推广末端智能配送服务。 4.打造"人工智能+交通运输"高质量数据集、算法库、工具链，为建设智能综合立体交通网提供技术底 座。 5.加快智能驾驶、智慧航运等重点领域标准规范制修订。 6.鼓励企业牵头围绕新产品、新技术、新业态，在生产制造、测试评估、智能交 ...

Core Viewpoint - The implementation of "Artificial Intelligence + Transportation" is a key initiative to foster new economic drivers and update old ones in China, with a focus on accelerating breakthroughs in basic research and promoting emerging industries like intelligent driving as new engines for economic growth [1][2]. Group 1: Goals and Objectives - By 2027, AI is expected to be widely applied in typical scenarios within the transportation sector, with the establishment of a comprehensive transportation AI model system and the development of several landmark innovative projects [2]. - By 2030, AI will be deeply integrated into the transportation industry, advancing smart comprehensive transportation networks and achieving a leading position in key technologies within the smart transportation and logistics sectors [2]. Group 2: Key Tasks - The implementation plan outlines four main tasks: increasing the supply of key technologies, accelerating innovation in application scenarios, strengthening core element guarantees, and optimizing the industrial development ecosystem [2][4]. - In increasing key technology supply, the plan emphasizes breakthroughs in common technologies such as dynamic scene perception, real-time precise positioning, and autonomous decision-making in complex environments [2]. Group 3: Innovation in Smart Products - The plan calls for accelerated innovation in smart products, including the development of intelligent driving systems, remote driving cockpits, and advanced monitoring technologies for highways [3]. - It encourages the research and development of new equipment such as drones and all-terrain vehicles, as well as upgrades to smart railway equipment and intelligent scheduling systems [3]. Group 4: Core Element Guarantees - The plan highlights the need to optimize computing power supply, accelerate the construction of high-quality data sets, and promote the development of ubiquitous network facilities [4]. - It emphasizes the integration of AI, next-generation communication, and IoT technologies to support the development of transportation infrastructure and service networks [4]. Group 5: Industrial Ecosystem Optimization - The plan aims to enhance the incubation capacity of the industrial ecosystem by forming alliances for transportation AI models and integrating leading companies, industry enterprises, and academic institutions [5]. - It also focuses on improving the governance mechanism for AI applications in transportation, addressing data risk prevention, and establishing monitoring and emergency response systems [5].

《实施意见》主要部署了加大关键技术供给、加速创新场景赋能、加强核心要素保障、优化产业发展生 态4方面任务。 其中，在加大关键技术供给方面，《实施意见》提出，开展应用技术攻关。着力突破动态场景感知与理 解、实时精准定位与导航、面向复杂环境的自主决策与群智协同等共性技术。 交通领域智能产品也"在路上"。《实施意见》提出，加快智能产品创新。加快智能驾驶系统、远程驾驶 座舱等产品研发。强化公路高性能夜视监控、结构检测等新技术、新装备研发应用。鼓励无人机、全地 形车等新装备的研制。推动智慧列车装备、智慧重载、新一代通信信号装备、列车智能调度系统等铁路 装备升级。加强智能船用设备、智能船舶和海上智能搜救装备研发。积极开展智能摊铺和压实机、造塔 机、造桥机、智能巡检机器人等施工和维养装备研发。推进智能搬运装卸、仓储配送、智能安检等设施 设备研发。 在加速创新场景赋能方面，《实施意见》从组合辅助驾驶、智能铁路、智慧航运、智慧民航、智慧邮 政、智能建养、联程联运与智慧物流等领域部署7项重点任务。 （资料图） 其中，关于组合辅助驾驶，《实施意见》提出，开展智能驾驶大模型、成套测评技术提升行动，拓展服 务场景。支持京津冀、长三角、 ...