安全

为系统评估不同恐慌状态下的群体疏散效应，本文以大型商场与地铁站台为研究对象，采用改进的SIR传染病模型描述恐慌传播动力学，引入信息熵理论量化群体决策有序性。设置不同恐慌强度、人员密度、出口布局和信息透明度条件，系统分析恐慌对疏散时间、流动特征及路径选择的影响，并通过“路径选择熵”指标揭示群体决策趋同性。结果显示：在重度恐慌状态下，商场与地铁站台疏散时间分别增加47.3%和62.8%,地铁场景下路径选择熵由2.81 bits降至1.56 bits并出现中段次生拥堵；信息透明度由0.2提升至0.8时，重度恐慌状态下地铁站台疏散时间减少29%;在商场与地铁站台2类场景下，当总出口宽度相同时，均匀布局较集中布局疏散效率提升约22%。研究成果可为公共场所应急疏散预案优化与风险防控提供理论支撑。

To systematically evaluate crowd evacuation effects under different panic states, this study takes large shopping malls and metro platforms as the research objects.It employs an enhanced SIR epidemic model to describe panic propagation dynamics and introduces information entropy theory to quantify crowd decision-making order. Different conditions of panic intensity, occupant density, exit layout, and information transparency are set to systematically analyze the impacts of panic on evacuation time, flow characteristics, and route selection, and the “path-choice entropy” indicator is used to reveal the convergence of group decisions. The results indicate that during severe panic scenarios, evacuation times at shopping malls and subway platforms increased by 47.3 % and 62.8 % respectively. In subway environments, path selection entropy decreased from 2.81 bits to 1.56 bits, accompanied by secondary congestion in the middle section. When information transparency increases from 0.2 to 0.8, the evacuation time under severe panic on metro platforms decreases by 29 %.In the two scenarios of shopping mall and subway platform, when the total exit width is the same, the evacuation efficiency of uniform layout is about 22 % higher than that of centralized layout. The research results can provide theoretical support for the optimization of emergency evacuation plan and risk prevention and control in public places.