A Robust Mean-field Game of Boltzmann-Vlasov-like Traffic Flow

A Robust Mean-field Game of Boltzmann-Vlasov-like Traffic Flow

Title : A Robust Mean-field Game of Boltzmann-Vlasov-like Traffic Flow
Authors : Amoolya Tirumalai and John S. Baras
Conference : 2022 American Control Conference (ACC2022) pp. 556-561 , Atlanta, GA
Date: June 08 - June 10, 2022

Historically, traffic modeling approaches have taken either a particle-like (microscopic) approach, or a gaslike (meso- or macroscopic) approach. Until recently with the introduction of mean-field games to the controls community, there has not been a rigorous framework to facilitate passage between controls for the microscopic models and the macroscopic models. We begin this work with a particle-based model of autonomous vehicles subject to drag, unknown disturbances, noise, and a speed limit in addition to the control.  We formulate a robust stochastic differential game on the particles.We pass formally to the infinite-particle limit to obtain a robust mean-field game PDE system. We solve the meanfield game PDE system numerically and discuss the results. In particular, we obtain an optimal control which increases the bulk velocity of the traffic flow while reducing congestion.

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