Emerging connected and automated vehicle technologies present unique challenges and opportunities in the modeling of nonlocal inter-vehicle interactions and their effects on traffic flows. This talk investigates a particular nonlocal traffic flow model, revealing that asymptotic stability of traffic flow is attainable under suitable assumptions on nonlocal information utilization. Simultaneously, we present a family of numerical schemes for the model that demonstrate robustness with respect to changes in the nonlocal horizon parameter. With suitable discretization of the nonlocal integral, the convergence of numerical solutions is shown to lead towards the weak entropy solution of the respective local model as both the mesh size and the nonlocal horizon parameter approach zero. The findings may serve to inform the development of future driving algorithms for connected vehicles.

报告人简介：Dr. Kuang Huang is a Research Assistant Professor in the Department of Mathematics at The Chinese University of Hong Kong. He completed his undergraduate studies at the School of Mathematics and Statistics at Wuhan University in 2017 and obtained his Ph.D. from the Department of Applied Physics and Applied Mathematics at Columbia University in 2022. His research interests include nonlocal models and their applications in traffic flow modeling, mean field games, and physics-informed and data-driven modeling of dynamical systems.