Multi-agent modeling of crowd dynamics under bombing attack cases

Abstract

Terrorist attacks are a catastrophic man-made emergent phenomenon. The current situation of international violent terrorism is severe. Public places with high-density crowds are more likely to be attacked by violent terrorists. To effectively reduce the number of casualties caused by violent terrorist incidents, it is crucial to take preventive management at the beginning of the incident. This paper analyzed the characteristics of the self-organization of crowds and terrorists in public places during a suicide bombing attack and conducted simulation experiments with an agent-based model. The simulation results show that unobstructed escape routes and controlling external sites will improve the evacuation efficiency of the crowd when a violent terrorist incident occurs; the pedestrian flow in public places affects the overall evacuation time; and timely and effective control of violent terrorists can reduce the number of casualties among the crowd. The optimized strategies obtained through experiments will help public security organs prevent violent terrorist incidents in public places and improve the efficiency of early disposal.