TIME
May 30th，15:00-17:00
LOCATION
ROOM 322
INTRODUCTION
With the integration of information and communication technology, vehicle automation, and artificial intelligence/machine learning (AI/ML), supported by high-performance computing (including cloud computing and edge computing), the field of traffic management is undergoing a transformation towards a more intelligent, sustainable, and equitable future. This necessitates a paradigm shift in traffic system analysis to better alleviate urban traffic congestion within the framework of smart transportation. This study focuses on the transformative role of smart travel information in smart traffic management to promote the development of intelligent traffic management theory and application. On the theoretical front, the study proposes a new framework based on behavioral game theory in behavioral economics to analyze the impact of AI/ML-driven heterogeneous information (including trip scheduling, route guidance, and trip time reliability) on dynamic traffic equilibrium. On the application side, the study explores how reinforcement learning can be applied to smart information extraction, integration, and customization. This provides a model for applying AI/ML to information design and vehicle route planning, thereby offering innovative solutions for traffic congestion alleviation. Based on this, the study constructs a bidirectional deep learning framework based on behavioral game theory, providing a testing, analysis, and evaluation platform for intelligent traffic management. In summary, this study offers a new research direction for advancing the development of intelligent, sustainable, and equitable transportation systems by establishing a theoretical foundation and pioneering AI/ML-driven applications.
ABOUT THE LECTURER
He Xiaozheng is currently an Associate Professor in the Department of Civil and Environmental Engineering at Rensselaer Polytechnic Institute in the United States. He also serves as the Assistant Director of the Center for Excellence in Sustainable Urban Freight Systems, which is funded by the Volvo Research and Educational Foundation, and is responsible for research on sustainable transportation. His main research areas include traffic system modeling, analysis, and computer simulation, covering traffic management modeling and algorithm design, infrastructure resilience analysis, new energy vehicle development planning, and vehicle networking modeling, analysis, and traffic flow control. Dr. He is a recipient of awards such as the American Society of Civil Engineers' Excellence in Teaching Award, the Best Paper at the IEEE Intelligent Transportation Systems Conference, and the National Science Foundation's Career Award.
Dr. He is currently an editorial board member of Transportation Research Part B, Deputy Editor-in-Chief of Frontiers in Future Transportation, Co-Chair of the Transportation Network Analysis and Optimization Technical Committee at the World Conference on Transportation Research, a member of the Transportation Network Modeling Committee of the Transportation Research Board, and a member of the New York State Intelligent Transportation Committee. He has long served as a judge for research projects for the National Science Foundation, the University Transportation Center of the U.S. Department of Transportation, the Hong Kong Research Grants Council, and the Chilean National Fund for Scientific and Technological Development. Dr. He has published over 110 academic works, more than 30 of which have been published in renowned journals such as Transportation Research, Transportation Science, and IEEE Transactions on Intelligent Transportation Systems.