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Physics > Physics and Society
Title: Mean-Field Games Modeling of Anticipation in Dense Crowds
(Submitted on 2 Mar 2024 (v1), last revised 28 May 2024 (this version, v2))
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.
Submission history
From: Matteo Butano [view email][v1] Sat, 2 Mar 2024 10:40:50 GMT (411kb,D)
[v2] Tue, 28 May 2024 13:01:36 GMT (411kb,D)
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