A Bayes network based model of stranded passengers transfering among transportation hubs in climate disaster

Aiming to the case of large number of people being stranded at the major transportation hubs (such as bus station, railway stations, airports, etc.) in climate disasters, we developed a model to describe passengers' delay and transfer among transportation hubs. The authors believe that the weather, traffic node status (open or closed), the service status (normal, delayed or canceled), estimated wait time and estimated transfer cost are the main factor in decision-making of passengers. Bayesian network and influence diagram are used in model to simulate passenger's decision-making process. The research of this paper establish a theoretical foundation for further study of stranded passengers distribution and transfer pattern at traffic hubs, then for giving the propose to the government emergency management decision-making.