中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (3): 178-185.doi: 10.16265/j.cnki.issn1003-3033.2026.03.0548

• 公共安全与应急管理 • 上一篇    下一篇

基于单层建筑火灾的人员逃生疏散路径数值模拟*

张晓蕾1,2()   

  1. 1 中国安全生产科学研究院, 北京 100012
    2 中国矿业大学(北京) 应急管理与安全工程学院, 北京 100083
  • 收稿日期:2025-10-26 修回日期:2026-01-09 出版日期:2026-03-31
  • 作者简介:

    张晓蕾 (1984—),女,山西大同人,博士研究生,高级工程师,主要研究方向为安全生产与应急救援理论与技术。E-mail:

  • 基金资助:
    中国安全生产科学研究院基本科研业务专项资金资助(2025JBKY21)

Evacuation path numerical simulation for occupants in single-story building fires

ZHANG Xiaolei1,2()   

  1. 1 China Academy of Safety Science and Technology, Beijing 100012, China
    2 School of Emergency Management and Safety Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China
  • Received:2025-10-26 Revised:2026-01-09 Published:2026-03-31

摘要:

为解决我国城市化进程不断加速、人员密集场所日益增多的背景下,单层建筑火灾场景中人员疏散逃生高效性与安全性较低的问题,针对传统火灾疏散路径规划在效率与合理性方面的不足,构建基于A*算法的单层建筑火灾人员疏散模型;引入栅格化建模,并结合粒子群优化(PSO)算法,综合考虑烟雾浓度、高温环境、有害气体扩散以及人员密度等多重复杂因素对疏散过程的影响;基于建立的单层建筑火灾人员疏散模型,运用多变量函数关系量化各因素对人员移动速度的影响系数,从而实现对疏散过程的精准描述;开展数值模拟试验中,通过设置建筑内不同人数的工况,对比分析改进前后A*算法的性能差异。研究结果表明:相较于传统A*算法,改进模型在疏散时间上缩短20.9%,路径长度减少3.27%,可有效避免疏散路径陷入局部最优解以及人员误入死胡同等问题。

关键词: 人员疏散, 疏散路径, 粒子群优化(PSO)算法, 改进A*算法, 路径规划

Abstract:

To address the low efficiency and safety of personnel evacuation in fire scenarios amid China's accelerating urbanisation and the increasing number of densely populated venues, a single-story building fire evacuation model based on the A* algorithm was developed. A grid-based model was introduced and combined with the PSO algorithm to comprehensively account for multiple complex factors influencing the evacuation process, including smoke concentration, high-temperature environments, hazardous gas dispersion, and personnel density. Based on the single-story building fire evacuation model, multivariate functional relationships were used to quantify the influence coefficients of various factors on personnel movement velocity, thereby achieving a precise description of the evacuation process. During numerical simulation experiments, the performance of the original and improved A* algorithms was compared across scenarios with varying occupant numbers within the building. The results indicate that compared to the traditional A* algorithm, the improved model reduces evacuation time by 20.9% and path length by 3.27%. It can effectively prevent evacuation paths from falling into local optima and avoid occupants entering dead ends.

Key words: evacuation of occupants, evacuation path, particle swarm optimisation(PSO)algorithm, improved A* algorithm, path planning

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