阻塞(统计)
瓶颈
人群
生存能力
行人
计算机科学
模拟
紧急疏散
感知
分布式计算
工程类
计算机安全
计算机网络
运输工程
神经科学
地质学
嵌入式系统
生物
海洋学
作者
Peter B. Luh,Christian T. Wilkie,Shi‐Chung Chang,Kerry L. Marsh,Neal Olderman
标识
DOI:10.1109/tase.2012.2200039
摘要
In building emergency evacuation, the perception of hazards can stress crowds, evoke their competitive behaviors, and trigger disorder and blocking as they pass through narrow passages (e.g., a small exit). This is a serious concern threatening evacuees' survivability and egress efficiency. How to optimize crowd guidance while considering such effects is an important problem. Based on advanced microscopic pedestrian models and simulations, this paper establishes a new macroscopic network-flow model where fire, smoke, and psychological factors can evoke a crowd's desire to escape—the desired flow rate. Disorder and blocking occur when the desired flow rate exceeds the passage capacity, resulting in a drastic decrease of crowd movement in a nonlinear and random fashion. To effectively guide crowds, a divide-and-conquer approach is developed based on groups to reduce computational complexity and to reflect psychological findings. Egress routes for individual groups are optimized by using a novel combination of stochastic dynamic programming and the rollout scheme. These routes are then coordinated so that limited passage capacities are shared to meet the total need for joint movement. Numerical testing and simulation demonstrate that, compared with a strategy of merely using nearest exits, our solution can evacuate more people more rapidly by preventing or mitigating potential disorder and blocking at bottleneck passages.
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