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

机译:基于群体行为的滞留旅客转乘决策建模与仿真

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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.
机译:针对气候灾难中大批人群滞留在交通枢纽(例如汽车站,火车站,机场等)的情况,设计了一种模型来表示基于群体行为的旅客在交通枢纽之间的转移。在模型中使用贝叶斯网络和影响图来捕获乘客决策过程的基本特征,然后考虑群体行为对个人的影响,根据乘客的信念和群体信息的准确性来修改乘客的转移概率。在Repast平台中使用Java语言开发了多主体仿真模型。通过仿真数据,分析了不同政策下羊群行为对滞留旅客转移方式和系统性能的影响,并提出了一些针对政府的政策建议。

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