Discounted Mean-Field Game model of a dense static crowd with variable information crossed by an intruder

Abstract

It was demonstrated in [Bonnemain et al., Phys. Rev. E 107, 024612 (2023)] that the anticipation pattern displayed by a dense crowd crossed by an intruder can be successfully described by a minimal Mean-Field Games model. However, experiments show that changes in the pedestrian knowledge significantly modify the dynamics of the crowd. Here, we show that the addition of a single parameter, the discount factor $\gamma$, which gives a lower weight to events distant in time, is sufficient to observe the whole variety of behaviors observed in the experiments. We present a comparison between the discounted MFG and the experimental data, also providing new analytic results and insight about how the introduction of $\gamma$ modifies the model.

19 pages, 9 figures, comments are welcome

References in corpus (4)

• Social Force Model for Pedestrian Dynamics
• Universal power law governing pedestrian interactions
• Mechanical response of dense pedestrian crowds to the crossing of intruders
• Body and mind: Decoding the dynamics of pedestrians and the effect of smartphone distraction by coupling mechanical and decisional processes

Cited by in corpus (2)

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