中文摘要：

针对现有人群疏散模型较少考虑“异质”群体运动混乱程度对疏散结果影响的问题,提出了基于多智能体和熵的介观人群疏散模型,介观模型包括上层宏观多目标路径优化模型和下层微观人群疏散模型.模型引入信息论中熵的概念,构建反映人群运动混乱程度的疏散熵,将个体速度和位置分布映射为疏散熵图,疏散熵图会对个体的疏散行为产生影响.上层模型采用网络最快流模型构建基于疏散熵的动态多目标疏散路径算法,为个体提供全局疏散优化路径;下层模型包括基于熵的小群体聚集行为模型和引导行为模型等.仿真结果表明,一定数量的引导者对疏散效率起着重要作用.当引导者数量增加时,群体恐慌程度降低,群体中拥挤行为和避障行为次数减少,使疏散过程更加有序且疏散熵值降低.

英文摘要：

Existing evacuation models consider less the influence of heterogeneous crowds motion on evacuation efficiency. In this paper, a new mesoscopic evacuation model based on multi-agent and entropy is proposed. The mesoscopic model includes the upper macro multi-objective evacuation path optimization model and lower microscopic pedestrian evacuation model. The concept of evacuation entropy is introduced to construct the evacuation entropy map which reflects the degree of crowds movement disorder and can affect individual behavior. The upper model is a multi-objective optimization model based on quickest flow model, which calculates the global optimal evacuation path for individual. The lower model includes entropy-based grouping behavior model and leading behavior model. The simulation experimental results show that leaders in crowds have significant impact on evacuation efficiency. When the number of leaders increase in crowds, the number of crowded behavior, obstacle avoidance behavior and crowd panic level are reduced. The proposed model can make the evacuation process more orderly and reduce evacuation entropy.