An agent-based simulation model of pedestrian evacuation based on Bayesian Nash Equilibrium

Close

Release Notes

An agent-based evacuation simulation model of pedestrian flow was developed by introducing BNE to realistically simulate individual decision-making process and pedestrian behaviours in an emergency evacuation. The model aims to combine Bayesian game theory and an agent-based approach at an individual level, to provide an experimental environment of pedestrian flows to support research on crowd management and evacuation planning. It was hypothesized that a BNE approach was able to positively affect individual evacuations during model simulation because of its capacity to predict future congestion levels. A series of simulation experiments were conducted with different parameter configurations to understand whether and how BNE affects pedestrian emergency evacuations.

This model consists of Three behavioural models: Shortest Route (SR), Random Follow (RF) and BNE. The behavioural models were used to generate four moving patterns (i.e. model configurations): SR, RF, BNE mixed with SR, and BNE mixed with RF, which can be selected by the chooser “moving-pattern”. The number of agents, the percentage of BNE users and other parameters can be adjusted by the corresponding sliders.