|Table of Contents|

A multi-objective route optimization method for passenger evacuations at subway stations during a fire outbreak(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2023年05期
Page:
192-209
Research Field:
交通运输规划与管理
Publishing date:
2023-11-10

Info

Title:
A multi-objective route optimization method for passenger evacuations at subway stations during a fire outbreak
Author(s):
YANG Xiao-xia1 ZHANG Rui2 LI Yong-xing3 QU Da-yi4
(1. School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, Shandong, China; 2. School of Civil Engineering, Qingdao University of Technology, Qingdao 266520,Shandong, China; 3. Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology,Beijing 100124, China; 4. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, Shandong, China)
Keywords:
traffic planning route planning multi-objective optimization passenger evacuation fire subway station
PACS:
U231.92
DOI:
10.19818/j.cnki.1671-1637.2023.05.013
Abstract:
A passenger evacuation network at subway stations was established, the degrees of network nodes were analyzed to identify key nodes, and a modified walking evacuation network was proposed after node failures. A time prediction model for passengers traveling through the gate and stair/escalator nodes was designed based on the support vector regression algorithm, and its prediction performance was analyzed. A quantitative relationship between the number of passengers and travel time was obtained. Three objective functions, namely the total evacuation time including the node and road section travel time, the total road risk, and the total congestion cost, were established. A multi-objective route optimization model for passenger evacuation at subway stations during a fire outbreak was constructed, and a solution method of optimization model was proposed based on the genetic algorithm. The evacuation movement of passengers at subway stations during a fire outbreak was simulated, and the evacuation efficiencies under the Pareto solution of the route optimization model was analyzed,then the optimization degree of the route optimization strategy was evaluated. A WeChat applet for passenger dynamic guidance was designed, providing a possible solution for the timely release of evacuation route recommendation information. Research results indicate that the mean absolute error of the passenger travel time prediction model at the nodes for the validation set can be as low as 0.000 375, and the robust indicator value is up to 0.999 334, indicating a high degree of consistency between predicted data and real data. The average relative error between the field collected data at the gate and the simulated data is 4.9%. The significance values of normality test, homogeneity test of variance, and independent sample test are all greater than 0.05, verifying that the PathFinder software can simulate passenger movements accurately. Compared with the normal evacuation without optimization strategies, the optimization degrees of the route optimization model under three sets of Pareto solutions are 16.7%, 15.9%, and 18.0%, respectively. Therefore, corresponding evacuation optimization strategies can be selected based on specific evacuation scenarios, risk factors, service quality requirements, and other indicators. 7 tabs, 20 figs, 31 refs.

References:

[1] 中国城市轨道交通协会.城市轨道交通2021年度统计和分析报告[R].北京:中国城市轨道交通协会,2021.
China Association of Metros. 2021 Statistical and analysis report on urban rail transit[R]. Beijing: China Association of Metros, 2021.(in Chinese)
[2] YANG X X, ZHANG R, LI Y X, et al. Passenger evacuation path planning in subway station under multiple fires based on multiobjective robust optimization[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 21915-21931.
[3] YU H, WANG Y M, QIU P Y, et al. Analysis of natural and man-made accidents happened in subway stations and trains: based on statistics of accident cases[C]∥EDP Sciences. 2018 International Conference on Functional Materials and Chemical Engineering. Paris: EDP Sciences, 2019: 01031.
[4] 陈阳光.基于BIM的地铁车站火灾疏散研究[D].成都:西南交通大学,2023.
CHEN Yang-guang. Research on fire evacuation of subway station based on BIM[D]. Chengdu: Southwest Jiaotong University, 2023.(in Chinese)
[5] 王胜闯.突发火灾下地铁站内人群疏散模型与仿真研究[D].沈阳:沈阳大学,2022.
WANG Sheng-chuang. Study on crowd evacuation model and simulation in subway station under sudden fire[D]. Shenyang: Shenyang University, 2022.(in Chinese)
[6] 黄 昕,靳 健,林作忠,等.基于A*算法的深部地下空间火灾疏散路径动态规划[J].北京工业大学学报,2021,47(7):702-709.
HUANG Xin, JIN Jian, LIN Zuo-zhong, et al. Dynamic evacuation path planning for fire disaster of deep underground space based on A* algorithm[J]. Journal of Beijing University of Technology, 2021, 47(7): 702-709.(in Chinese)
[7] CHOI M, CHI S. Optimal route selection model for fire evacuations based on hazard prediction data[J]. Simulation Modelling Practice and Theory, 2019, 94: 321-333.
[8] 陈一洲,尹浩东,孙 旋,等.基于实时毒气影响的人群疏散路径优化研究[J].安全与环境学报,2018,18(6):2316-2321.
CHEN Yi-zhou, YIN Hao-dong, SUN Xuan, et al. Optimalization for the crowd masses evacuation route based on the study of the impact of real-time gas leakage[J]. Journal of Safety and Environment, 2018, 18(6): 2316-2321.(in Chinese)
[9] SHEN Yang, WANG Qing-song, YAN Wei-gang, et al. An evacuation model coupling with toxic effect for chemical industrial park[J]. Journal of Loss Prevention in the Process Industries, 2015, 33: 258-265.
[10] AZADEH A, FARROKHI-ASL H. The close-open mixed multi depot vehicle routing problem considering internal and external fleet of vehicles[J]. Transportation Letters—The International Journal of Transportation Research, 2017, 11(2): 78-92.
[11] 姜学鹏,张 帆,陈欣格.地铁隧道火灾人员疏散可靠度研究[J].消防科学与技术,2020,39(1):9-13.
JIANG Xue-peng, ZHANG Fan, CHEN Xin-ge. Reliability research of human evacuation in subway tunnel fire[J]. Fire Science and Technology, 2020, 39(1): 9-13.(in Chinese)
[12] YANG X X, YANG Y, QU D Y, et al. Multi-objective optimization of evacuation route for heterogeneous passengers in the metro station considering node efficiency[J]. IEEE Transactions on Intelligent Transportation Systems, DOI: 10.1109/TITS.2023.3292912.
[13] LI X L, WANG H, YI S W, et al. Disaster-and-evacuation-aware backup datacenter placement based on multi-objective optimization[J]. IEEE Access, 2019, 7: 48196-48208.
[14] 刘恒旭.基于蚁群算法的地铁站火灾多目标疏散路径优化研究[D].西安:西安建筑科技大学,2018.
LIU Heng-xu. Optimization of multi-target evacuation paths for subway stations based on ant colony algorithm[D]. Xi'an: Xi'an University of Architecture and Technology, 2018.(in Chinese)
[15] HOSSEINI O, MAGHREBI M, MAGHREBI M F. Determining optimum staged-evacuation schedule considering total evacuation time, congestion severity and fire threats[J]. Safety Science, 2021, 139: 105211.
[16] 种法雯.大型公共建筑室内火灾应急疏散路径仿真及优化研究[D].马鞍山:安徽工业大学,2018.
CHONG Fa-wen. Simulation and optimization of emergency evacuation routes for indoor fires in large public buildings[D]. Maanshan: Anhui University of Technology, 2018.(in Chinese)
[17] TSUKAHARA M, KOSHIBA Y, OHTANI H. Effectiveness of downward evacuation in a large-scale subway fire using Fire Dynamics Simulator[J]. Tunnelling and Underground Space Technology, 2011, 26(4): 573-581.
[18] 王 婷,杜慕皓,唐永福,等.基于BIM的火灾模拟与安全疏散分析[J].土木建筑工程信息技术,2014,6(6):102-108.
WANG Ting, DU Mu-hao, TANG Yong-fu, et al. Analysis on fire model and safety evacuation based on BIM[J]. Journal of Information Technology in Civil Engineering and Architecture, 2014, 6(6): 102-108.(in Chinese)
[19] LI M X, ZHU S B, WANG J H, et al. Research on fire safety evacuation in a university library in Nanjing[J]. Procedia Engineering, 2018, 211: 372-378.
[20] 邹馨捷,萨木哈尔·波拉提,郝 明,等.基于Pyrosim和PathFinder的高校学生宿舍火灾人员疏散安全性模拟分析[J].安全与环境工程,2020,27(4):195-200.
ZOU Xin-jie, BOLATI S, HAO Ming, et al. Personnel evacuation safety simulation analysis of college student dormitory fire based on Pyrosim and PathFinder[J]. Safety and Environmental Engineering, 2020, 27(4): 195-200.(in Chinese)
[21] ZHANG H, LONG H C. Simulation of evacuation in crowded places based on BIM and Pathfinder[J]. Journal of Physics: Conference Series, 2021, 1880(1): 012010.
[22] 王 莉.基于PATHFINDER的公共场所人员疏散行为规律及仿真模拟[J].西安科技大学学报,2017,37(3):358-364.
WANG Li. Evacuation behavior and simulation of large public places based on PATHFINDER[J]. Journal of Xi'an University of Science and Technology, 2017, 37(3): 358-364.(in Chinese)
[23] SUN D J, GUAN S. Measuring vulnerability of urban metro network from line operation perspective[J]. Transportation Research Part A: Policy and Practice, 2016, 94: 348-359.
[24] FELICIANI C, NISHINARI K. Measurement of congestion and intrinsic risk in pedestrian crowds[J]. Transportation Research Part C: Emerging Technologies, 2018, 91: 124-155.
[25] DAAMEN W. Modelling passenger flows in public transport facilities[D]. Delft: Netherlands Research School for Transport, 2004.
[26] JIN T, YAMADA T. Irritating effects of fire smoke on visibility[J]. Fire Science and Technology, 1985, 5(1): 79-90.
[27] GU B, SHENG V S, WANG Z J, et al. Incremental learning for V-support vector regression[J]. Neural Networks, 2015, 67: 140-150.
[28] YANG Xiao-xia, ZHANG Rui, PAN Fu-quan, et al. Stochastic user equilibrium path planning for crowd evacuation at subway station based on social force model[J]. Physica A: Statistical Mechanics and its Applications, 2022, 594: 127033.
[29] MA Chang-xi, WANG Chao, XU Xue-cai. A multi-objective robust optimization model for customized bus routes[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(4): 2359-2370.
[30] YANG Xiao-xia, YANG Yi, LI Yong-xing, et al. Path planning for guided passengers during evacuation in subway station based on multi-objective optimization[J]. Applied Mathematical Modelling, 2022, 111: 777-801.
[31] GUO Kai, ZHANG Li-mao. Simulation-based passenger evacuation optimization in metro stations considering multi-objectives[J]. Automation in Construction, 2022, 133: 104010.

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Last Update: 2023-11-10