城市轨道交通车站运营人员行为对乘客应急疏散路径选择干预的虚拟现实仿真建模方法

VR Simulation Modeling for Intervention of Urban Rail Transit Station Staff Behavior on Passenger Emergency Evacuation Path Choice

[目的]为有效反映城市轨道交通车站运营人员行为对疏散的实时影响,解决目前VR(虚拟现实)环境中疏散路径规划采用预定义的静态路径法,而无法揭示乘客疏散对运营人员即时行为动态响应机理的问题,提出一种运营人员行为对乘客应急疏散路径选择干预的VR仿真建模方法。[方法]介绍了将车站物理空间描绘为路径算法可识别的抽象空间的环境建模方法,定义了能感知外部信息和自主决策的乘客智能体模型,制定了基于A算法的出口选择规则;在此基础上,考虑运营人员行为对环境的动态改变,综合实时的疏散路线长度、疏散时间和行人密度等因素,构建了动态路径规划模型;开发了VR仿真系统,以某大型综合枢纽车站为例进行仿真分析。[结果及结论]仿真分析结果表明,疏散仿真开始时,乘客智能体能根据出口选择制定全局路线,过程中能自主根据运营人员引起的动态障碍物状态变化进行实时的局部路径规划,并且随着场景内乘客数量的增加仍保持较高的响应性。说明所提方法能有效且高效地捕捉虚拟环境中的动态变化,并将其反映到乘客疏散的过程中,能为开展紧急疏散VR试验提供技术支持。

[Objective]To effectively reflect the real-time impact of urban rail transit station staff behavior on evacuation,and to solve the problem that the adoption of predefined static path method for evacuation route planning in VR(virtual reality)environment cannot reveal the dynamic response mechanism of passenger evacuation to station staff immediate behavior,a VR simulation modeling method is proposed to model the intervention of station staff behavior on passenger emergency evacuation path choice.[Method]The environment modeling method that depicts station physical space as an abstract space recognizable by path algorithm is introduced.The passenger intelligent agent model that can perceive external information and make decisions autonomously is defined,and the exit selection rules based on A algorithm are formulated.On this basis,a dynamic path planning model is constructed by considering the dynamic change of station staff behavior to the environment and integrating the real-time evacuation route length,the evacuation process time,and the density of pedestrians.A VR simulation system is developed to carry out simulation and analysis using a large-scale comprehensive hub station as example.[Result&Conclusion]Simulation analysis results show that at the beginning of evacuation simulation,the passenger intelligent agent can formulate global routes based on exist selection.During the process,it can autonomously perform real-time local path planning based on dynamic obstacle state changes caused by station staff,and maintain high responsiveness as the number of passengers in the scenario increases.It indicates that the proposed method can effectively and efficiently capture the dynamic changes in virtual environment and reflect them in the process of passenger evacuation,thereby providing technical support for conducting emergency evacuation VR experiments.