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基于多智能体的虚拟化地铁站乘客行为仿真
引用本文:李泽群,闫丰亭,史志才,简玉梅,花常花,司勇占,项阳.基于多智能体的虚拟化地铁站乘客行为仿真[J].系统仿真学报,2020,32(12):2341-2352.
作者姓名:李泽群  闫丰亭  史志才  简玉梅  花常花  司勇占  项阳
作者单位:1.上海工程技术大学 电子电气工程学院,上海 201620; 2.上海立信会计金融学院 工商管理学院,上海 201620; 3.日照职业技术学院 通用航空学院,山东 日照 276800; 4.上海市信息安全综合管理技术研究重点实验室,上海 200240
基金项目:上海市信息安全综合管理技术研究重点实验室开放研究课题基金(AGK2019004)
摘    要:地铁站是典型的人群密度大的公共场所,根据人群行为特点以及基于人群行为特点的引导,可以有效培训人群应急疏散。采用多智能体的方法,通过度量地铁站建筑场景特点,分析乘客行为特征的影响因素,基于乘客从众心理规律,提出单Agent属性定义及约束规则,建立乘客Agent路径选择行为模型,在虚拟地铁站内为多智能体建立MAS(Multi-Agent System)行为决策系统,通过WebVR实验研究乘客从众行为以及决策行为的影响因素,为高峰期人员流动策略的制定提供理论依据,有效地缓解地铁站内人群拥挤现象。

关 键 词:多智能体  WebVR地铁站  乘客行为  应急决策  
收稿时间:2020-03-21

Multi-Agent Behavior Simulation for Metro Station Passenger
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.
Authors:Li Zequn  Yan Fengting  Shi Zhicai  Jian Yumei  Hua Changhua  Si Yongzhan  Xiang Yang
Institution:1. College of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China; 2. College of Business Administration,Shanghai Lixin Accounting and Finance College,Shanghai 201620,China; 3. General Aviation College of Rizhao Vocational and Technical College,Rizhao 276800,China; 4. Shanghai Key Laboratory of Integrated Administration Technologies for Information Security,Shanghai 201620,China
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.
Keywords:Multi-Agent  WebVR metro station  Passengers‘ behavior  Emergency decision  
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