Special Session Ⅸ
AI-Empowered Transportation System Analysis, Management, and Control
(AI赋能交通系统分析、管理与控制)
Chair: | Co-chair: |
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Liang Zheng | Ning Zhu |
Central South University, China | University of Science and Technology of China, China |
Keywords: | Topics: |
· Artificial Intelligence (人工智能) · Smart Transportation (智慧交通) · Large Models (大模型) · Traffic Management and Control (交通管控) | · Traffic Scene Perception Technologies and Methods based on Large Models (基于大模型的交通场景感知技术与方法) · Traffic Scene Cognition Technologies and Methods based on Large Models (基于大模型的交通场景认知技术与方法) · AI-based Control Methods for Intelligent Driving Vehicles (基于人工智能的智能驾驶车辆管控方法) · AI-based Control Strategies for Connected Intersections (基于人工智能的网联交叉口控制方法) · AI-Driven Traffic Management and Optimization Technologies (基于人工智能的交通管控与优化技术) · Data-Driven Methods for Traffic Prediction and State Estimation in Road Networks (基于数据驱动的路网交通预测与估计方法) · Frontiers and Exemplary Applications of AI in Intelligent Transportation Systems (人工智能技术在智能交通系统中的应用前沿与优秀案例) |
Summary:
· Artificial intelligence (AI) technologies have the potential to revolutionize transportation research and technological systems, driving comprehensive advancements in traffic sensing, analysis, and control. These developments are key enablers for the construction and evolution of smart cities, making AI a focal point of interest for both academia and industry. Against this backdrop, it is imperative to synthesize the latest theoretical advancements and practical applications of AI in the transportation domain, and to establish paradigms for its use in traffic analysis and control.
· 人工智能技术能够为交通研究与技术体系带来变革，推动交通感知、交通分析、交通管控等交通领域各个分支的全面升级，促进智慧城市的建设与发展，是学术界和产业界共同关注的热点。在此背景下，亟需总结人工智能技术在交通领域的理论方法与实践应用中的最新研究成果，提炼人工智能在交通分析与管控中的应用范式。
Submission Deadline: 2025.7.31