Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (12): 3597-3601.DOI: 10.11772/j.issn.1001-9081.2017.12.3597

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Modeling of high-density crowd emergency evacuation based on floor-field particle swarm optimization algorithm

WANG Chao, WANG Jian   

  1. CIMS Research Center, Tongji University, Shanghai 201804, China
  • Received:2017-04-07 Revised:2017-05-31 Online:2017-12-10 Published:2017-12-18
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (71573190).


王超, 王坚   

  1. 同济大学 CIMS研究中心, 上海 201804
  • 通讯作者: 王坚
  • 作者简介:王超(1989-),男,山东淄博人,博士研究生,主要研究方向:人群疏散建模与仿真、人群疏散信息物理系统;王坚(1961-),男,山东淄博人,教授,博士,主要研究方向:非常规突发事件应急管理、智能制造、大数据。
  • 基金资助:

Abstract: Aiming at the problems of congestion management and emergency evacuation of high-density crowd under the environment of unconventional emergencies, a four-layer crowd Evacuation Cyber-Physical System (E-CPS) framework was proposed, which contained sensing layer, transport layer, calculation layer and application layer. In the calculation layer of E-CPS framework, a Floor-Field Particle Swarm Optimization (PSO) (FF-PSO) crowd evacuation model was proposed by introducing static floor-field modeling rules into classical PSO. The FF-PSO evacuation model has the advantages such as simple rule and quick calculation of static floor-field, fast search and fast convergence of PSO. In addition, a new fitness function was designed and introduced into the proposed FF-PSO model to realize the dynamic adjustment of evacuation strategy. Numerical simulation and instance simulation were carried out to further verify the feasibility and effectiveness of the proposed FF-PSO model in congestion management. The instance simulation results of National Exhibition and Convention Center (Shanghai) show that 66 more pedestrians can be evacuated from the accident area per minute on average by the proposed model of introducing congestion management than the model of only considering the shortest distance. Furthermore, the evacuation time is saved by 19 min and the evacuation efficiency is improved by 13.4% by introducing congestion management.

Key words: Floor-Field (FF) model, Particle Swarm Optimization (PSO) model, high-density crowd, Cyber-Physical System (CPS), simulation and deduction

摘要: 针对非常规突发事件环境下高密度人群的拥挤管理和快速疏散问题,提出一种由感知层、传输层、计算层和应用层构成的多层结构人群疏散信息物理系统(E-CPS)体系框架。在E-CPS体系框架计算层中将静态地面场(FF)建模规则引入经典粒子群优化(PSO)模型,提出地面场PSO (FF-PSO)人群疏散模型,该模型同时具备静态场规则简单、计算快和PSO模型快速搜索、快速收敛的优点。此外,FF-PSO模型中构建了一种新的适应度函数,实现了疏散策略的动态选择,并通过数值仿真及实例仿真验证了FF-PSO模型在拥挤管理中的可行性和有效性。国家会展中心(上海)的实例仿真结果表明,考虑拥堵管理比仅考虑距离最短平均每分钟可多疏散66人,疏散时间节省19 min,疏散效率提升13.4%。

关键词: 地面场模型, 粒子群优化模型, 密集人群, 信息物理系统, 仿真推演

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