Simulation model of pedestrian flow based on multi-agent system and Bayesian Nash equilibrium

Computer-based simulation is a means of exploring complex systems and has become the mainstream method of pedestrian research. In this research, a multi-agent simulation model of pedestrian flow will be established using a multi-agent system (MAS) and Bayesian Nash equilibrium. MAS is used to simulate the crowd movement and the interaction between pedestrians, and Bayesian Nash equilibrium is adopted to analyze the decision-making process of pedestrians. In contrast to previous pedestrian flow simulation modeling methods, this study adopts multi-agent modeling to realize the complete heterogeneity of pedestrians, so as to achieve more accurate simulation and make the research conclusions closer to reality. To be specific, we attempt to determine the cell side length and simulation time step of an initial model parameterized using a dataset of actual pedestrian movements. It allows more than one pedestrian to be in the same cell and stipulates that the utility of pedestrians decreases with the growing number of pedestrians in the cell. The Bayesian Nash equilibrium is applied to analyze the decision-making process of pedestrians and collision avoidance rules and interaction rules of agents are also formulated. A number of areas of further research are discussed.