基于涟漪扩散算法的应急疏散路径优化方法研究

doi:10.16097/j.cnki.1009-6744.2024.01.025

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (1): 253-261.DOI: 10.16097/j.cnki.1009-6744.2024.01.025

基于涟漪扩散算法的应急疏散路径优化方法研究

胡小兵^*1a，袁莉燕^1b，李航^1a，赵宇勃^1c，张勇²，李奇轩²

1. 中国民航大学，a. 体系安全与智能决策实验室，b. 电子信息与自动化学院，c. 中欧航空工程师学院，天津 300300； 2. 河北省高速公路京雄筹建处，河北保定071000

收稿日期:2023-09-27 修回日期:2023-11-18 接受日期:2023-12-04 出版日期:2024-02-25 发布日期:2024-02-14
作者简介:胡小兵(1975- )，男，四川人，教授，博士
基金资助:
中央高校基本科研业务费(3122019057)；河北省交通运输厅科技项目(JX-202002)

Optimization of Emergency Evacuation Route Based on Ripple-spreading Algorithm

HU Xiaobing^*1a, YUAN Liyan^1b, LI Hang^1a, ZHAO Yubo^1c, ZHANG Yong², LI Qixuan²

1a. Laboratory of Complex System Safety and Intelligent Decisions, 1b. College of Electronic Information and Automation, 1c. Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China; 2. Hebei Province Highway Jingxiong Preparatory Office, Baoding 071000, Hebei, China

Received:2023-09-27 Revised:2023-11-18 Accepted:2023-12-04 Online:2024-02-25 Published:2024-02-14
Supported by:
The Fundamental Research Funds for the Central Universities of China (3122019057)；Science and Technology Project of Hebei Provincial Department of Transportation (JX-202002)

摘要/Abstract

摘要： 针对大型公共场所内人群应急疏散路径优化问题，本文提出一种考虑容量限制的多起点多终点涟漪扩散算法(Capacity Constrained Ripple Spreading Algorithm, CCRSA)。该算法通过动态更新各链接在各时刻的剩余最大通行容量，容量不足时添加涟漪在节点的等待行为，一次性得出多个起点到多个终点的包含等待时间的疏散时间最短路径；并使用路径寻优规则确定优先疏散路径，分配疏散人员数量，实行差异化疏散，提高路网中各链接的利用率。使用大量具有不同节点数量、不同待疏散人数的随机路网与北京颐和园实际路网案例对算法进行测试，并设置了疏散时间、人员实际/理想疏散时间标准差、程序运行时间这3个评价标准。实验结果表明：与传统的应急疏散路径规划算法相比，CCRSA平均可减少13.07%的人群疏散时间，以较高运行效率得到更加满足各疏散人员期望的疏散方案。

关键词: 交通工程, 人群应急疏散, 涟漪扩散算法, 多对多路径优化, 容量动态更新

Abstract: This study proposes a capacity constrained ripple spreading algorithm (CCRSA) aimed at optimizing emergency evacuation routes in expansive public spaces during crowd emergencies. This algorithm dynamically updates the remaining maximum traffic capacity of each link at each moment, and adds ripple waiting behavior at nodes when the capacity is insufficient. It identifies the shortest evacuation path considering waiting times from multiple starting points to various destinations simultaneously. Subsequently, path optimization rules determine priority evacuation routes and allocate the number of evacuees, thereby achieving differentiated evacuation and enhancing the utilization of different routes within the road network. The algorithm is tested across numerous randomized road networks featuring different number of nodes and evacuees, and an actual road network scenario at the Summer Palace in Beijing. Three evaluation criteria, evacuation time, standard deviation between actual and ideal evacuation times per individual, and program running time, are established. The experimental findings demonstrate that CCRSA, in comparison to conventional emergency evacuation path planning algorithms, reduces evacuation time by an average of 13.07% and generates evacuation plans that better align with the expectations of evacuees while exhibiting enhanced program efficiency.

Key words: traffic engineering, crowd emergency evacuation, ripple-spreading algorithm, many-to-many path optimization, capacity dynamic update

中图分类号:

U491

胡小兵, 袁莉燕, 李航, 赵宇勃, 张勇, 李奇轩. 基于涟漪扩散算法的应急疏散路径优化方法研究[J]. 交通运输系统工程与信息, 2024, 24(1): 253-261.

HU Xiaobing, YUAN Liyan, LI Hang, ZHAO Yubo, ZHANG Yong, LI Qixuan. Optimization of Emergency Evacuation Route Based on Ripple-spreading Algorithm[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(1): 253-261.

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http://www.tseit.org.cn/CN/Y2024/V24/I1/253

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基于涟漪扩散算法的应急疏散路径优化方法研究

Optimization of Emergency Evacuation Route Based on Ripple-spreading Algorithm

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