The Proceedings of 2025 International Conference on Artificial Intelligence and Autonomous Transportation
Description
This book reflects the latest research trends, methods and experimental results in the field of Artificial Intelligence and Autonomous Transportation, which covers abundant state-of-the-art research theories and ideas. As a vital research area that is highly relevant to current developments in a number of technological domains, the topics covered include Autonomous Transportation Systems, Autonomous Transportation Management and Control Technology, Autonomous Transportation Equipment Technology, Vehicular Networking and Information Security, Emerging Technologies and Future Mobility, Intelligent water transportation technology, Cross-Domain Transportation Technology, and so on. The goal of the proceedings is to provide a major interdisciplinary forum for researchers, engineers, academics, and industry professionals to present the most innovative research and development in the field of Artificial Intelligence and Autonomous Transportation. Engineers and researchers from academia, industry, and government also explore an insight view of the solutions that combine ideas from multiple disciplines in this area. The book serves as an excellent reference work for researchers and graduate students working in the areas of rail transportation, electrical engineering, and information technology.
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Persons
Jia Limin
Jia Limin, Beijing Jiaotong University, No.3 Shangyuancun Haidian District Beijing , China, lmjia@bjtu.edu.cn
Jia Liming is a professor at Beijing Jiaotong University, a member of the National Carbon Neutrality Technology Expert Committee, a vice president of the China Electrotechnical Society, and a supervisor of the China Intelligent Transportation Association. He was awarded the Special Allowance of the State Council of China, the "Millions of Talent Projects" National candidates, the National Outstanding Scientific and Technical Workers.
Yinong Zhang
Yinong Zhang, Beijing Union University, No. 97 Beisihuan East Road, Chao Yang District, Beijing, P.R. China, zdhtyinong@buu.edu.cn
Yinong Zhang is a professor at Beijing Union University. The main research fields are complex process modeling, intelligent control, fault diagnosis and safety evaluation."
Fei Dou
Fei Dou, Beijing Union University, No. 97 Beisihuan East Road, Chao Yang District, Beijing, P.R. China, 20250001@buu.edu.cn
Fei Dou is a professor of engineering at Beijing Union University. The main research fields are rail transit operation organization, emergency management and safety evaluation.
Zehao Jiang
Zehao Jiang, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan, China, jiangzehao@hust.edu.cn
Zehao Jiang is an associate professor at Huazhong University of Science and Technology, IEEE Member. His research interests include the traffic design, infrastructure requirements for autonomous vehicles, and low-altitude economy.
Zhao Yang
Zhao Yang, Chang'an University, Middle-section of Nan'er Huan Road, Beilin District, Xi'an, ShaanXi Province, China, zyang27@chd.edu.cn
Zhao Yang is an assistant professor at Chang'an University, IEEE Member. His research interests include the autonomous driving system and transportation LLM.
Content
Methods for State Sensing and Early Warning of Operating Conditions.- Research on Workload Balance-oriented Method of Yard Planning for Fully Automated Container Terminal .- Multimodal Trajectory Prediction for Autonomous Driving on Unstructured Roads using Deep Convolutional Network.- Study on driving risk through unsignalized intersection.- An Engineering Evaluation Methodology of Heterogeneous Network for Highway Infrastructure Monitoring Data Transmission Based on Graph Theory.- Adaptive background residual correlation filters for UAV tracking.- Integrated Travel Service Scheme for ComprehensiveTransportation Hub.- The Research and Application of Gridded Tide Data Service.- Research on Model-Free Adaptive Iterative Learning Control of Quadrotor Aerial Vehicle.- A Parameter Adaptive Model Predictive Control for Virtual Coupling.