“AI+交通运输”！七部门，最新部署！

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][2]. Group 1: Key Deployments - Accelerate the research and development of intelligent driving systems and remote driving cockpits, supporting innovation resource aggregation in key regions [3][8]. - Encourage the development of new equipment such as drones and all-terrain vehicles [4]. - Promote the opening of urban scenarios and road networks to scale up the application of new delivery devices and intelligent delivery services [5][9]. - Build high-quality datasets, algorithm libraries, and toolchains for "Artificial Intelligence + Transportation" to support the construction of an intelligent comprehensive transportation network [5][10]. - Expedite the formulation and revision of standards and norms in key areas like intelligent driving and smart shipping [6][10]. - Encourage enterprises to lead the development of standards around new products, technologies, and business models [6]. Group 2: Accelerating Innovation - The transportation sector is identified as a key area for AI application due to its diverse scenarios and rich data. The opinions outline systematic deployments to enhance key technology supply, accelerate innovation scene empowerment, and optimize the industrial development ecosystem [7]. - Specific tasks include the development of intelligent driving systems, smart rail equipment, and intelligent shipping devices, as well as the establishment of a comprehensive transportation model [8]. - The article emphasizes the importance of creating replicable and scalable application cases in various fields such as assisted driving, smart railways, and intelligent logistics [8]. Group 3: Optimizing the Innovation Environment - The opinions propose optimizing computing power supply, accelerating the construction of high-quality datasets, and promoting ubiquitous network infrastructure [10][11]. - It highlights the need for a robust data resource system and a reliable traffic data transmission network to support AI applications [10]. - The establishment of a transportation big model innovation and industry alliance is encouraged to integrate leading AI companies, industry enterprises, and academic institutions [11].