Investigation of the Probability of a Safe Evacuation to Succeed in Subway Fire Emergencies Based on Bayesian Theory

Abstract

Emergency evacuation in subway fires is one of the hot issues in public safety. Based on Bayesian theory, a dynamic evacuation risk analysis model considering both psychological and behavioral responses of evacuees was proposed in this contribution. A subway fire scene was modeled using the Event Tree Analysis (ETA) according to the questionnaire survey at Nanjing Xinjiekou station. In this fire scenario, three control events (the fire alarm, the exhaust system and the evacuation route) were related to fire evacuation control and two control events (active escape and passive escape), which were specifically defined, were related to personnel characteristics. Subsequently, the probability of the final state of each scene was calculated by Monte Carlo simulation. Combined with the statistics of accidents and safe evacuation of subway fire cases from 1976 to 2013, the posterior probability distribution of safety evacuation was obtained after real-time dynamic updating of its precursor probability through Bayesian theory. Results show that the posterior probability of safety evacuation to succeed is around 0.8. This indicates that there is still a probability of 0.2 resulting in injury or fatalities in subway accidents even though most passengers are safely evacuated. It also suggests that utilization of 0.2 as the safety threshold would be an appropriate choice.