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.
@article{arxiv.2403.01168,
title = {Mean-Field Games Modeling of Anticipation in Dense Crowds},
author = {Matteo Butano and Cécile Appert-Rolland and Denis Ullmo},
journal= {arXiv preprint arXiv:2403.01168},
year = {2024}
}
Comments
2 figures, 10 pages. arXiv admin note: text overlap with arXiv:2302.08945