Multi-Agent Behavior Simulation for Metro Station Passenger

doi:10.16182/j.issn1004731x.joss.20-FZ0431

Abstract

Abstract: Metro station is a typical public place with large crowd density.The characteristics of crowd behavior and the guidance based on the characteristics of crowd behavior can effectively train the crowd for emergency evacuation.Adopting the method of multi-agent and characteristics by measuring station building scene,analyzing the influence factors of passenger behavior characteristics,based on the passenger conformity rule,the single-agent passenger route choice behavior model is established.The multiple agents behavioral decision system in the virtual metro stations is established,the WebVR experiment is used to research the influencing factors of passenger herd behavior and decision-making behavior,which provides a theoretical basis for the emergency evacuation strategy during peak periods,and effectively alleviates crowd congestion in metro stations.

Key words: Multi-Agent, WebVR metro station, Passengers‘ behavior, Emergency decision

CLC Number:

TP306

Li Zequn, Yan Fengting, Shi Zhicai, Jian Yumei, Hua Changhua, Si Yongzhan, Xiang Yang. Multi-Agent Behavior Simulation for Metro Station Passenger[J]. Journal of System Simulation, 2020, 32(12): 2341-2352.

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