[1]杨晓霞,张 蕊,李永行,等.火灾爆发时地铁站乘客疏散多目标路径优化方法[J].交通运输工程学报,2023,23(05):192-209.[doi:10.19818/j.cnki.1671-1637.2023.05.013]
　YANG Xiao-xia,ZHANG Rui,LI Yong-xing,et al.A multi-objective route optimization method for passenger evacuations at subway stations during a fire outbreak[J].Journal of Traffic and Transportation Engineering,2023,23(05):192-209.[doi:10.19818/j.cnki.1671-1637.2023.05.013]
点击复制

火灾爆发时地铁站乘客疏散多目标路径优化方法()
分享到：

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

卷:
第23卷
期数:
2023年05期
页码:
192-209
栏目:
交通运输规划与管理
出版日期:
2023-11-10

文章信息/Info

Title:
A multi-objective route optimization method for passenger evacuations at subway stations during a fire outbreak
文章编号:
1671-1637(2023)05-0192-18
作者:
杨晓霞1; 张 蕊2; 李永行3; 曲大义4
(1.青岛理工大学 信息与控制工程学院,山东 青岛 266520; 2.青岛理工大学 土木工程学院,山东 青岛 266520; 3.北京工业大学 交通工程北京市重点实验室,北京 100124; 4.青岛理工大学 机械与汽车工程学院,山东 青岛 266520)
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)
关键词:
交通规划;  路径规划;  多目标优化;  乘客疏散;  火灾;  地铁站
Keywords:
traffic planning;  route planning;  multi-objective optimization;  passenger evacuation;  fire;  subway station
分类号:
U231.92
DOI:
10.19818/j.cnki.1671-1637.2023.05.013
文献标志码:
A
摘要:
建立了一种地铁站乘客疏散网络,分析了网络节点的度以辨识关键节点,提出了节点失效后的修正走行疏散网络; 设计了基于支持向量回归算法的闸机、楼梯/扶梯节点处乘客通行时间预测模型,分析了模型的预测性能,得到了乘客数量与通行时间的定量关系; 建立了包括节点和路段通行时间的总疏散时间、总路段风险和总拥挤成本3个目标函数,构建了一种火灾爆发时地铁站乘客疏散多目标路径优化模型,提出了基于遗传算法的优化模型求解方法; 模拟了火灾爆发时地铁站乘客的疏散运动,分析了路径优化模型帕累托解下的疏散效率,评估了路径优化策略的优化程度; 设计了乘客动态引导微信小程序,为疏散路径推荐信息的及时发布提供了一种可能方案。研究结果表明:验证集中节点处乘客通行时间预测模型的平均绝对误差低至0.000 375,稳健指标值可高达0.999 334,说明预测数据与真实数据吻合程度高; 闸机处实际采集数据与仿真数据的平均相对误差为4.9%,正态性检验、方差齐性检验和独立样本检验的显著值都大于0.05,验证了PathFinder软件可较为真实地模拟乘客运动; 与正常疏散无优化策略相比,路径优化模型3组帕累托解下的优化程度分别为16.7%、15.9%、18.0%,因此,根据具体疏散场景、危险系数、服务质量要求等指标可选用相应的疏散优化策略。
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.

参考文献/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.

相似文献/References:

[1]鲜于建川,隽志才,朱泰英.后悔理论视角下的出行选择行为[J].交通运输工程学报,2012,12(03):67.
　XIANYU Jian-chuan,JUAN Zhi-cai,ZHU Tai-ying.Travel choice behavior based on regret theory view[J].Journal of Traffic and Transportation Engineering,2012,12(05):67.
[2]赵建有,周孙锋,崔晓娟,等.基于模糊线性回归模型的公路货运量预测方法[J].交通运输工程学报,2012,12(03):80.
　ZHAO Jian-you,ZHOU Sun-feng,CUI Xiao-juan,et al.Predictive method of highway freight volume based on fuzzy linear regression model[J].Journal of Traffic and Transportation Engineering,2012,12(05):80.
[3]胡 卉,程 菱,宣登殿,等.容量限制与运输模式联合选择的综合客运枢纽布局模型[J].交通运输工程学报,2012,12(04):59.
　HU Hui,CHENG Ling,XUAN Deng-dian,et al.Comprehensive passenger hub layout model of combined selection for capacity limitation and transportation mode[J].Journal of Traffic and Transportation Engineering,2012,12(05):59.
[4]蔚欣欣,陆化普,李阳阳,等.随机供给与随机需求的交通网络设计模型[J].交通运输工程学报,2012,12(04):67.
　YU Xin-xin,LU Hua-pu,LI Yang-yang,et al.Design model of traffic network based on stochastic supply and stochastic demand[J].Journal of Traffic and Transportation Engineering,2012,12(05):67.
[5]龙雪琴,关宏志,秦焕美.城市道路最大出行距离计算模型[J].交通运输工程学报,2012,12(04):75.
　LONG Xue-qin,GUAN Hong-zhi,QIN Huan-mei.Calculation model of maximum travel distance on urban road[J].Journal of Traffic and Transportation Engineering,2012,12(05):75.
[6]张卫华,杨 博,陈俊杰.基于复杂网络的城市路网结构分析方法[J].交通运输工程学报,2012,12(05):64.
　ZHANG Wei-hua,YANG Bo,CHEN Jun-jie.Analysis method of urban road network structure based on complex network[J].Journal of Traffic and Transportation Engineering,2012,12(05):64.
[7]杨忠振,邬珊华,罗红红,等.道路网单向交通优化设计模型[J].交通运输工程学报,2012,12(05):72.
　YANG Zhong-zhen,WU Shan-hua,LUO Hong-hong,et al.Optimization design model of one-way traffic for road network[J].Journal of Traffic and Transportation Engineering,2012,12(05):72.
[8]徐亚华,冯立光.公共交通优先发展现状及战略规划[J].交通运输工程学报,2010,10(06):64.
　XU Ya-hua,FENG Li-guang.Situation and strategy planning of public transit priority development[J].Journal of Traffic and Transportation Engineering,2010,10(05):64.
[9]陈 荔,马荣国.基于支持向量机的都市圈客运量预测模型[J].交通运输工程学报,2010,10(06):75.
　CHEN Li,MA Rong-guo.Prediction model of passenger transport volume in metropolitanregion based on support vector machine[J].Journal of Traffic and Transportation Engineering,2010,10(05):75.
[10]霍娅敏,陈坚,李啸虎,等.城市建设项目交通影响后评价模型[J].交通运输工程学报,2012,12(01):79.
　HUO Ya-min,CHEN Jian,LI Xiao-hu,et al.Traffic impact post-evaluation model of urban construction project[J].Journal of Traffic and Transportation Engineering,2012,12(05):79.

备注/Memo

备注/Memo:
收稿日期:2023-05-10
基金项目:国家自然科学基金项目(62373209,62003182,52272311)
作者简介:杨晓霞(1988-),女,山东烟台人,青岛理工大学副教授,工学博士,从事智能交通研究。
通讯作者:曲大义(1973-),男,山东青岛人,青岛理工大学教授,工学博士。
更新日期/Last Update: 2023-11-10