A Stochastic Approach for Simulating Human Behaviour During Evacuation Process in Passenger Trains

In this paper we present a stochastic approach for modelling passenger performances during evacuation process in passenger trains. The paper is divided into two parts. The first part describes the identification of variables and data collection. This process allows obtaining statistical samples of predefined random variables (personal responses, non-emergency actions, walking speeds, etc.). Then, statistical methods to determine the input and outputs for a stochastic analysis are proposed. In the second part, results from EvacTrain^®, a stochastic model for passenger trains, were compared with other evacuation models and an announced evacuation drill. Results suggest that predicted evacuation times can be strongly dependent on the activities of individuals whose actions interrupt the continuous movement of other passengers within the aisle and the time spent by each passenger to negotiate the train steps. The advantages of using a stochastic approach for modelling passenger behaviours are discussed.