东北大学学报(自然科学版) ›› 2021, Vol. 42 ›› Issue (11): 1656-1662.DOI: 10.12068/j.issn.1005-3026.2021.11.019

• 管理科学 • 上一篇    下一篇

基于动态情绪驱动的人员应急疏散模型

李佳洋1, 唐加福1,2, 郭恩铭3   

  1. (1. 东北大学 工商管理学院, 辽宁 沈阳110819; 2. 东北财经大学 管理科学与工程学院, 辽宁 大连116025; 3. 东北大学 计算机科学与工程学院, 辽宁 沈阳110169)
  • 修回日期:2021-02-08 接受日期:2021-02-08 出版日期:2021-11-19 发布日期:2021-11-19
  • 通讯作者: 李佳洋
  • 作者简介:李佳洋(1979-),女,辽宁锦州人,东北大学博士研究生; 唐加福(1965-),男,湖南东安人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(71601126); 辽宁省自然科学基金资助项目(20170540654).

Crowd Emergency Evacuation Model Based on Dynamic Emotion Drive

LI Jia-yang1, TANG Jia-fu1,2, GUO En-ming3   

  1. 1. School of Business Administration, Northeastern University, Shenyang 110819, China; 2. School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, China; 3. School of Computer Science and Engineering, Northeastern University, Shenyang 110619, China.
  • Revised:2021-02-08 Accepted:2021-02-08 Online:2021-11-19 Published:2021-11-19
  • Contact: LI Jia-yang
  • About author:-
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摘要: 针对应急疏散中人员的动态疏散行为,将情绪感知及传染机制引入行人运动策略,以SIS(susceptible-infectious-susceptible)模型为基础构造了人员情绪更新函数,提出了情绪感知域界定,改进了元胞自动机的动态场.通过仿真实验对所构建动态情绪驱动人员疏散运动模型的性能开展分析,验证了该模型符合个体运动的动态特征.同时探讨了动态行为切换的情绪强度阈值、感染系数和平静系数等因素对疏散过程的影响.结果表明:个体情绪强度阈值决定了系统的个体最终状态,而感染系数和平静系数影响状态变化速率,进而影响疏散时间.该研究为疏散人群管理提供理论依据.

关键词: 情绪感知, 疏散模型, 动态行为, SIS模型, 元胞自动机

Abstract: Aiming at the crowd dynamic behavior in emergency evacuation, emotion perception and infection mechanism are combined into behavior decision-making. Based on the susceptible-infectious-susceptible model (SIS model), emotion updating function is constructed in order to improve the dynamic field and transition probability of cellular automata. By analyzing the performance of the constructed model, it is verified that the emergency evacuation model conforms to the dynamic characteristics of crowd flow. Moreover, through simulation experiments, the effect of system parameters is analyzed on dynamic behavior switching, and the impacts of such parameters of dynamic behavior switching as emotional intensity threshold, infection coefficient, and calmness coefficient are explored. The results show that the individual emotional intensity threshold determines the individual final state of the system. The infection and calmness coefficients affect the rate of state change and evacuation time. This research provides a theoretical basis for the management of evacuated crowd.

Key words: emotion perception, evacuation model, dynamic behavior, SIS(susceptible-infectious-suseptible) model, cellular automata

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