On a mean field game approach modeling congestion and aversion in pedestrian crowds

In this paper we present a new class of pedestrian crowd models based on the mean field games theory introduced by Lasry and Lions in 2006. This macroscopic approach is based on a microscopic model, that considers smart pedestrians who rationally interact and anticipate the future. This leads to a forward-backward structure in time. We focus on two-population interactions and validate the modeling with simple examples. Two complementary classes of problems are addressed, namely the case of crowd aversion and the one of congestion. In both cases we describe the model and present numerical solvers (based on the optimization formulation and the partial differential equations respectively). Finally we present numerical tests involving anticipation phenomena and complex group behaviors such as lane formation.

► We present a new approach of crowd motion modeling that is based on mean field games. ► Pedestrians are modeled as smart entities that optimize their strategy. ► Main novelties are the forward-backward structure describing the crowd dynamics, and the individuals’ expectations. ► We discuss interactions between two crowds, focusing on aversion and congestion. ► We provide numerical solvers; first numerical results confirm the expected behavior like lane formation.