Modeling and simulation of stranded passengers´ transferring decision-making on the basis of herd behavior

According to the case of large crowd being stranded at transportation hubs (such as bus station, railway station, airport, etc.) in climate disasters, a model is designed to represent passengers´ transferring among transportation hubs on the basis of herd behavior. Bayesian network and influence diagram are used in model to capture essential features of the passenger´s decision-making process, then considering the influence of group behavior on the individuals, the transition probabilities of passengers are revised with passengers´ accuracy of belief and group information. A multi-agent simulation model is developed in Repast platform in Java language. Through the simulation data, the influence of herd behavior over stranded passengers´ transferring mode and system performance in different policies are analyzed, some policy recommendations for the government are proposed.