A three-stage evacuation decision-making and behavior model for the onset of an attack

Pedestrian behavior models have successfully reproduced human movement in many situations. However, few studies focus on modeling human behavior in the context of terrorist attacks. Terrorist attacks commonly occur in crowded public areas and result in a large number of casualties. This paper proposes a three-stage model to reproduce a series of complex behaviors and decision-making processes at the onset of an attack, when pedestrians generally do not have clear targets and have to deal with fuzzy information from the attack. The first stage of the model builds a Bayesian belief network to represent the pedestrians’ initial judgment of the threat and their evacuation decisions. The second stage focuses on pedestrians’ global assessment of the situation through an analogy with diffusion processes. The third stage uses a cost function to reproduce the trade-offs of distance, safety, and emotional impact when considering a path to take. The model is validated using a video from the November 2015 Paris attack. The behavioral characteristics and trajectories of three pedestrians extracted from the video are reproduced by the simulation results based on the model. The research can be used to set rules when performing risk analysis and strategic defensive resource allocation of terrorist attacks using agent-based simulation methods.