A Cellular Automaton Model To Calculate Evacuation Resilience Performance In Tunnel Fire

Tunnels connect traffic from on the ground and underground, and play a crucial role to solve traffic overload and congestion. During the operation, fire is a huge threat resulting from vehicle collisions or self-ignition to occupants and their evacuation is one of the main issues to solve these years. Though several technical installations, control systems and smart firefighting technologies are applied to guide and protect evacuation safety, it is not completely clear how to measure the evacuation safety scientifically and accurately especially when more elements are to be considered in the whole evacuation systems. To fill this gap, the concept of evacuation resilience is proposed in this study. The evacuation resilience presents the ability of evacuation from the threat of fire and could be measured by the total evacuation time, successful percentage compared to the evacuation conditions without fire. To point out, it not only evaluates the initial evacuation performance of occupants but also evaluates the optimized evacuation performance with the help of both external guidance and social influence. To obtain the evacuation resilience performance, a cellular automaton model was built and applied to calculate occupants' evacuation performance in fire as a demonstration. The resilience was then calculated by the comparison of evacuation in fire and without fire and a score was given correspondingly. The study is a fundamental attempt to propose evacuation resilience both qualitatively and quantitatively and is expected to attract more related research in the future to improve evacuation safety furthermore.