Random walk in extreme conditions - an agent based simulation of suicide bombing

Abstract

This paper presents a Monte-Carlo simulation tool based on stationary multi-agent system. The agents are constrained by physical characteristics and mechanics of blast waves. The proposed tool examines the impact of blast waves in an event of suicide bombing on human body. The tool is capable of assessing the impact of crowd formation patterns and their densities on the magnitude of injury and number of casualties during a suicide bombing attack. While various attempts have been made to assess the impact of blast waves and its overpressure on buildings and animals, little has been done on crowd formation, crowd density and underlying geometry to mitigate the effects. Results indicated that the worst crowd formation is street (Zig-Zag) where 30% crowd can be dead and 45% can be injured, given typical explosive carrying capacity of a single suicide bomber. Row wise crowd formations was found to be the best for reducing the effectiveness of an attack with 18% crowd in lethal zone and 38% in injury zones. For a typical suicide bombing attack, we can reduce the number of fatalities by 12%, and the number of injuries by 7%. The simulation results were compared and validated by the real-life incidents and found to be in good agreement. Line-of-sight with the attacker, rushing towards the exit, and stampede were found to be the most lethal choices both during and after the attack. These findings, although preliminary, may have implications for emergency response and counter terrorism.