The purpose of this paper is to reveal the pattern of passengers' transferring on occasion of a large crowd being stranded at transportation hubs (such as a bus station, railway station, airport, etc.) in climate disasters, and then propose the proper policy recommendations for the government to evacuate stranded passengers.
A model is established based on Bayesian network and influence diagram to catch the features of a passenger's decision‐making process, and the transition probabilities of passengers are revised on the basis of the theory of herd behaviors in information to describe the influence of group behaviors on passenger individuals. Subsequently, a multi‐agent model is developed in Repast platform in Java language, and simulation and analysis are also made.
The results of simulation show that it is possible to apply the theory of herd behaviors and the multi‐agent method in analyzing the effectiveness of government policies on evacuating stranded passengers in climate disasters.
The research of this paper has important practical significance for the government to developing policies to evacuating stranded passengers in climate disasters, and is a useful exploration to open up new methodologies for emergency management.
Shen, Y., Liu, S., Fang, Z. and Hu, M. (2012), "Modeling and simulation of stranded passengers' transferring decision‐making on the basis of herd behaviors", Kybernetes, Vol. 41 No. 7/8, pp. 963-976. https://doi.org/10.1108/03684921211257810Download as .RIS
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