|369-Limitations of Current Traffic Models and Strategies to Address Them|
主讲人：Dr. Daiheng Ni
Dr. Daiheng Ni is a tenured Professor in the Department of Civil and Environmental Engineering at University of Massachusetts Amherst, USA. His research interests include: Traffic Flow Theory and Simulation, Connected Vehicle Technology, Intelligent Transportation Systems (ITS), and Air Traffic Modelling and Control. He has published over 100 journal articles and conference papers in the above areas. He was previously a Member and now a Friend of Transportation Research Board (TRB) Committee on Traffic Flow Theory and Characteristics (AHB45). He is the author of textbook Traffic Flow Theory: Characteristics, Experimental Methods, and Numerical Techniques (1st edition, ISBN 9780128041345, eBook ISBN: 9780128041475) published by Elsevier in 2015. He teaches graduate and undergraduate courses including: CEE 310 Introduction to Transportation, CEE 411/511 Traffic Engineering, CEE 520/521 Traffic Flow Theory and Simulation I/II, and CEE 590I Signalized Intersections.
Traffic flow modeling has evolved over a few decades with numerous models at the macroscopic and microscopic levels being proposed. It appears that traffic flow modeling has been adequately addressed and it is natural to ask if there is still any gap to fill or any room to improve. After examining existing models and comparing them against ideal outcomes, we identified four limitations in both traffic flow theory and simulation, namely (1) the lack of model consistency among macroscopic models and between microscopic and macroscopic models, (2) the lack of model flexibility to admit driver heterogeneity, (3) the lack of model capability to look ahead into the near future, and (4) the lack of model expandability beyond one dimensional traffic. Strategies to address these limitations are proposed with emphasis on general approaches rather than proposing specific models.