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-AgentSystem)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。
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.
作者
李泽群
闫丰亭
史志才
简玉梅
花常花
司勇占
项阳
Li Zequn;Yan Fengting;Shi Zhicai;Jian Yumei;Hua Changhua;Si Yongzhan;Xiang Yang(College of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;College of Business Administration,Shanghai Lixin Accounting and Finance College,Shanghai 201620,China;General Aviation College of Rizhao Vocational and Technical College,Rizhao 276800,China;Shanghai Key Laboratory of Integrated Administration Technologies for Information Security,Shanghai 201620,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2020年第12期2341-2352,共12页
Journal of System Simulation
基金
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)。
