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作者:

Yang, Xiaoxia (Yang, Xiaoxia.) | Zhang, Rui (Zhang, Rui.) | Li, Yongxing (Li, Yongxing.) | Pan, Fuquan (Pan, Fuquan.)

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EI Scopus SCIE

摘要:

The optimization of passenger evacuation path in subway station under emergencies directly affects the evacuation efficiency. Aiming at the evacuation scenario of passengers in subway station under multiple fires, a path planning method based on multi-objective robust optimization is established in this paper. The shortest total evacuation time, the minimum total risk and the minimum total congestion cost are taken as the objectives where the robustness of travel time and risk is also considered. NSGA-II algorithm is used to solve the model, the optimal Pareto solution under a certain robust control parameter is obtained according to the principle of minimizing the total cost function, and the overall optimization degree of route is obtained by using the evaluation index. Taking Qingdao May 4th Square subway station of China as a verification example, a fire diffusion model is built by using Pyrosim, and a passenger evacuation system is built by using Pathfinder. The multi-objective robust path optimization model of passenger evacuation is applied to the built passenger evacuation system under fires. The simulation results show that the overall optimization degree of route can reach 12.8% , when the time and risk robust control parameters are 30 and 30, respectively. The method can be used to guide the passenger evacuation in subway stations under multiple hazard sources and improve the safety index of passenger travel.

关键词:

passenger evacuation evacuation network efficiency fire multiobjective robust optimization path planning Subway station

作者机构:

  • [ 1 ] [Yang, Xiaoxia]Qingdao Univ Technol, Sch Informat & Control Engn, Qingdao 266520, Peoples R China
  • [ 2 ] [Zhang, Rui]Qingdao Univ Technol, Sch Mech & Automot Engn, Qingdao 266520, Peoples R China
  • [ 3 ] [Pan, Fuquan]Qingdao Univ Technol, Sch Mech & Automot Engn, Qingdao 266520, Peoples R China
  • [ 4 ] [Li, Yongxing]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China

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来源 :

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

ISSN: 1524-9050

年份: 2022

期: 11

卷: 23

页码: 21915-21931

8 . 5

JCR@2022

8 . 5 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:49

JCR分区:1

中科院分区:1

被引次数:

WoS核心集被引频次: 33

SCOPUS被引频次: 39

ESI高被引论文在榜: 0 展开所有

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