Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium

Can Liao, Kejun Zhu, Haixiang Guo and Jian Tang

Complexity, 2019, vol. 2019, 1-15

Abstract:

Current research on pedestrian flows has mainly focused on evacuation optimization during or after emergencies; however, crowd management before emergencies has received little attention. This paper examines the management of a Safe Pedestrian Flow Rate, in which the Bayesian-Nash Equilibrium mimics pedestrians’ decision-making, and a multiagent system is employed to reproduce pedestrians’ interactions. In the model, the pedestrian tunnel is divided into cells, with each pedestrian in a cell receiving a utility depending on the distance to the exit and the number of pedestrians in the cell. Then, each pedestrian uses the Bayesian-Nash Equilibrium to search for the target cell with maximum expected utility, moves in, and makes next decision until exiting the tunnel. The simulation model is calibrated and validated from a real scenario. Finally, from the experimental data collected from different simulation scenarios, this research reaches the conclusion that the Safe Pedestrian Flow Rate increases by about 2.96ped/s as the tunnel width expanded by 1m. This paper offers a novel method for reducing potential losses caused by crowd emergencies and can be a valuable reference for managing pedestrian flows and designing public places.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:7942483

DOI: 10.1155/2019/7942483

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