广东:推动自动驾驶大模型落地

Core Viewpoint - Guangdong Province has officially issued a set of policies aimed at promoting high-quality development in transportation through artificial intelligence, establishing a comprehensive support system for smart transportation development [2] Group 1: Policy Measures - The policy includes 14 concrete measures to create a full-chain system of "core element supply - innovative scenario empowerment - work mechanism guarantee" [2] - It aims to accelerate the pilot application of intelligent connected vehicles and support the establishment of demonstration application recognition in free trade zones and administrative regions [2][5] Group 2: Data and Technology Support - The measures focus on three main areas: data supply, computing power and algorithm support, and key technology breakthroughs [3] - Guangdong will enhance data governance in the transportation sector, creating a standardized resource directory that includes key areas such as highways, railways, and ports [3] - The province will utilize data centers to support the orderly construction of computing power and deploy edge computing nodes in critical locations to form a collaborative system [3][4] Group 3: Application Scenarios - Eight innovative application scenarios are outlined to transition AI technology from the laboratory to practical use, including remote driving and intelligent decision-making [5][6] - The policy supports the construction of a national "vehicle-road-cloud integration" application pilot city in Guangzhou and Shenzhen, promoting the testing of autonomous driving in logistics scenarios [6] Group 4: Smart Infrastructure Development - The measures propose the integration of AI and domestic BIM technology in smart road construction, enhancing maintenance through unmanned inspections and data analysis [6] - The policy aims to transform road network management from "visible and measurable" to "intelligent research and prevention" [6] Group 5: Enhancing Transportation Efficiency - The integration of AI in rail transport will facilitate the optimization of passenger flow prediction and dynamic capacity allocation [7] - The development of a comprehensive monitoring system for waterways will enhance navigation efficiency and information exchange [7] Group 6: Emergency and Logistics Applications - AI will be applied in civil aviation for flight flow management and airport operations, optimizing resource allocation and enhancing safety [8] - The logistics sector will benefit from AI in demand integration and capacity allocation, improving multi-modal transport efficiency [9]