An improved optimization model for crowd evacuation considering individual exit choice preference
An improved optimization model for crowd evacuation considering individual exit choice preference
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DOI：
10.1111/tgis.12984
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发表时间：
2022-09-04
影响因子：
2.4
通讯作者：
Zhao，Yuhui
中科院分区：
文献类型：
--
作者：
Gao，Fei;Du，Zhiqiang;Zhao，Yuhui
引导辅助人群疏散是将个体出口选择行为与管理者出口分配控制相结合的过程。了解个体出口选择偏好对优化全局出口分配规划具有重要意义。本研究提出了一种改进的人群疏散优化模型，将个人层面的出口选择偏好分析与系统层面的出口分配优化相结合，以代表更现实的人群疏散决策。首先，在一个混合logit模型中考虑了个体退出选择行为的影响因素，以预测特定情况下每个个体选择每个退出的概率。其次，设计了一种基于偏好的出口过滤策略，用于分析多尺度疏散单元中个人或群体的合理替代出口。最后，为寻求最优出口分配方案，采用多目标粒子群优化算法和改进的社会力模型对人群疏散过程进行仿真，并对具体出口分配方案的性能进行评价。对西安一个室外多出口场景的案例研究表明，该模型可以帮助管理者理解个体疏散行为的异质性。此外，它将支持在真实的生活情况下更可靠和现实的疏散决策，而不是通常实施最高策略的传统计划。
Guidance‐assisted crowd evacuation is a process of combining individual exit choice behavior with managers' exit assignment control. The knowledge of individual exit choice preference is of great significance for optimizing global exit assignment planning. This study proposes an improved optimization model for crowd evacuation by integrating the individual‐level exit choice preference analysis with system‐level exit assignment optimization to represent more realistic crowd evacuation decisions. First, the impact factors of individual exit choice behavior are considered in a mixed logit model to predict the probability of each individual choosing each exit in specific situations. Second, a preference‐based exit filtering strategy is designed to analyze the sensible alternative exits for individuals or groups in multi‐scale evacuation cells. Finally, to pursue optimal exit assignment planning, a multi‐objective particle swarm optimization algorithm and an improved social force model are adopted to simulate the process of crowd evacuation and evaluate the performance of the specific exit assignment plans. The case study of an outdoor multiple‐exit scenario in Xi'an, China, indicates that the proposed model can help managers to understand the heterogeneity of individual evacuation behaviors. Furthermore, it will support more reliable and realistic evacuation decisions in real‐life situations than conventional plans that typically implement the top‐nstrategy.