Mean-Field Games Modeling of Anticipation in Dense Crowds

Matteo Butano; Cécile Appert-Rolland; Denis Ullmo

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arXiv · 2403.01168

Mean-Field Games Modeling of Anticipation in Dense Crowds

Matteo Butano·Cécile Appert-Rolland·Denis Ullmo

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Abstract

Understanding and modeling pedestrian dynamics in dense crowds is a complex yet essential aspect of crowd management and urban planning. In this work, we investigate the dynamics of a dense crowd crossed by a cylindrical intruder using a Mean-Field Game (MFG) model. By incorporating a discount factor to account for pedestrians' limited anticipation and information processing, we examine the model's ability to simulate two distinct experimental configurations: pedestrians facing the obstacle and pedestrians giving their back to the intruder. Through a comprehensive comparison with experimental data, we demonstrate that the MFG model effectively captures essential crowd behaviors, including anticipatory motion and collision avoidance.

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Matteo Butano, Cécile Appert-Rolland, Denis Ullmo. 2024-03-02. Mean-Field Games Modeling of Anticipation in Dense Crowds. https://arxiv.org/abs/2403.01168

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