Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium. (15th January 2019)

• Record Type: Journal Article
• Authors: Liao, Can; Zhu, Kejun; Guo, Haixiang; Tang, Jian
• Other Names: Duch Jordi Academic Editor.
• Is Part Of: Complexity. Volume 2019(2019)
• Publication Date: 2019-01-15
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2019/7942483
• Languages: English
• ISSNs: 1076-2787

Abstract

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.