[1]陈玺阳,刘晨辉,刘　令,等.基于韧性理论的地铁线路局部中断事件应急策略[J].郑州大学学报(工学版),2025,46(03):82-89.[doi:10.13705/j.issn.1671-6833.2024.06.010]
　CHEN Xiyang,LIU Chenhui,LIU Ling,et al.An Emergency Strategy for Subway Disruption Based on Resilience Theory[J].Journal of Zhengzhou University (Engineering Science),2025,46(03):82-89.[doi:10.13705/j.issn.1671-6833.2024.06.010]
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基于韧性理论的地铁线路局部中断事件应急策略()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
46
期数:
2025年03期
页码:
82-89
栏目:
出版日期:
2025-05-13

文章信息/Info

Title:
An Emergency Strategy for Subway Disruption Based on Resilience Theory
文章编号:
1671-6833(2025)03-0082-08
作者:
陈玺阳1;  刘晨辉1; 2; 3; 4;  刘　令5;  彭海波2; 6;  张　望2; 6
1.湖南大学 土木工程学院,湖南 长沙 410082;2.湖南省地理空间信息工程技术研究中心, 湖南 长沙 410007; 3.重庆大学 山地城镇与新技术教育部重点实验室,重庆 400045;4.湖南大学 综合交通研究中心,湖南 长沙 410082;5.长沙市规划勘测设计研究院,湖南 长沙 410007;6.湖南省第三测绘院,湖南 长沙 410007
Author(s):
CHEN Xiyang1;  LIU Chenhui1; 2; 3; 4;  LIU Ling5;  PENG Haibo2; 6;  ZHANG Wang2; 6
1.College of Civil Engineering, Hunan University, Changsha 410082, China; 2.Hunan Geospatial Information Engineering and Technology Research Center, Changsha 410007, China; 3.Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing 400045, China; 4.Transportation Research Center, Hunan University, Changsha 410082, China; 5.Changsha Planning & Design Survey Research Institute, Changsha 410007,China; 6.The Third Surveying and Mapping Institute of Hunan Province, Changsha 410007, China
关键词:
城市轨道交通;  韧性评估;  恢复策略;  客流损失;  多项式回归
Keywords:
urban rail transit;  resilience assessment;  recovery strategy;  passenger flow loss;  polynomial regression
分类号:
U292.7U298.5
DOI:
10.13705/j.issn.1671-6833.2024.06.010
文献标志码:
A
摘要:
在地铁延误与中断事件频发的背景下,针对常见应急策略的缺点,提出了一种基于韧性理论的地铁线路局部中断事件应急策略。首先,从理论上分析了突发事件下的地铁线路性能演化过程;其次,利用线路连通率、抗延误指数与客流保有率等指标构建了地铁线路韧性评估模型;最后,针对常见的地铁线路单侧轨道局部中断事件,以提升地铁线路韧性为目标提出了一种多区间单轨双向运行应急策略。该策略将事故路段相反方向的可运行轨道划分为若干区间,每个区间内有一辆列车以单轨双向运行模式运行。对工作日早高峰长沙地铁4号线进行实例分析,评价所提策略的有效性,结果表明:在面临突发事件时,大部分乘客的等待时间集中于5~7 min,乘客等待率在10 min内会下降至50%以下;与传统的小交路运行方案和单轨双向运行方案相比,多区间单轨双向运行方案的客流保有率分别提升了42.4%与12.7%,线路韧性分别提升145%和50%。
Abstract:
To tackle frequent subway delays and interruptions, to address the shortcomings of common emergency strategies, in this study, an emergency strategy for localized subway line interruptions was proposed based on resilience theory. Firstly, the evolution process of subway line performance during emergencies were thoretically analyzed. Subsequently, a resilience evaluation model for subway lines was constructed using indicators such as line connectivity, delay resistance index, and passenger retention rate. Finally, aiming to enhance subway line resilience, a multi-section single-track bidirectional operation emergency strategy was proposed for common incidents of partial interruption on one side of subway tracks. This strategy divided the operable track in the opposite direction of the accident site into several sections, with a train operating in a single-track bidirectional mode within each section. To assess the effectiveness of the proposed strategy, a case study was conducted on the Line 4 of the Changsha subway during weekday morning peak hours. The results indicated that during emergencies, the majority of passengers experienced wait times concentrated within 5-7 minutes, with passenger waiting rates dropping below 50% within 10 minutes. Compared to traditional shuttle operation and single-track bidirectional operation schemes, the multi-section single-track bidirectional operation scheme improved passenger retention rates by 42.4% and 12.7%, respectively, with a corresponding increase in line resilience of 145% and 50%.

参考文献/References:

[1]中国城市轨道交通协会. 城市轨道交通2022年度统计和分析报告[R/OL].(2023-03-31)[2024-01-05]. https:∥mp.weixin.qq.com/s? __biz=MzI3NzMwODY3OQ ==&mid=2247556041&idx=1&sn=599ad2f2a5b5 d8692a3ceee2b34a44e1&chksm=a703ff2e681d7e0552c9 c9a46e565f64e3d33db91942ba3f2a74b4e74f54cb8b404be 87e0e64&scene=27. 

China Urban Rail Transit Association. Statistical and analysis report on urban rail transit in 2022 [R/OL]. (2023-03-31) [2024-01-05]. https:∥mp.weixin. qq. com/s? __biz =MzI3NzMwODY3OQ= =&mid= 2247556041&idx = 1&sn = 599ad2f2a5b5d8692a3cee e2b34a44e1&chksm=a703ff2e681d7e0552c9c9a46e565f 64e3d33db91942ba3f2a74b4e74f54cb8b404be87e0e64&s cene=27. 
[2]ZHANG S Y, LO H K. Metro disruption management: optimal initiation time of substitute bus services under uncertain system recovery time[J]. Transportation Research Part C: Emerging Technologies, 2018, 97: 409-427. 
[3]PERELMUTER M. Quantifying passenger impact of disruptions on metro lines[D]. Boston:Massachusetts Institute of Technology, 2020. 
[4]杨琦, 张雅妮, 周雨晴, 等. 复杂网络理论及其在公共交通韧性领域的应用综述[J]. 中国公路学报, 2022, 35(4): 215-229. 
YANG Q, ZHANG Y N, ZHOU Y Q, et al. A review of complex network theory and its application in the resilience of public transportation systems[J]. China Journal of Highway and Transport, 2022, 35(4): 215-229. 
[5]NAN C, SANSAVINI G. A quantitative method for assessing resilience of interdependent infrastructures[J]. Reliability Engineering & System Safety, 2017, 157: 35-53. 
[6]交通运输部. 交通强国建设评价指标体系[EB/OL]. [2024-01-05]. https:∥xueshu.baidu.com/usercenter/ paper/show? paperid = 1v560tx0aa2m0ef0rn0r0vm 0dn325416&site=xueshu_se. 
Ministry of Transport. Evaluation index system for the construction of a strong transportation country[EB/OL]. [2024-01-05] https:∥xueshu.baidu. com/usercenter/ paper/show? paperid=1v560tx0aa2m0ef0rn0r0vm0dn32 5416&site=xueshu_se. 
[7]ADNAN M, PEREIRA F C, AZEVEDO C L, et al. Evaluating disruption management strategies in rail transit using SimMobility mid-term simulator: a study of Singapore MRT North-East line[C]∥ Transportation Research Board 96th Annual Meeting. Washington DC: TRB, 2017:1-16. 
[8]YANG J F, JIN J G, WU J J, et al. Optimizing passenger flow control and bus-bridging service for commuting metro lines[J]. Computer-Aided Civil and Infrastructure Engineering, 2017, 32(6): 458-473. 
[9]WANG Y, ZHOU Y, YANG H, et al. Integrated optimization of bus bridging service design and passenger assignment in response to urban rail transit disruptions[J]. Transportation Research Part C: Emerging Technologies, 2023, 150: 104098. 
[10] ITANI A, ABOUDINA A, DIAB E, et al. Managing unplanned rail disruptions: policy implications and guidelines towards an effective bus bridging strategy[J]. Transportation Research Record: Journal of the Transportation Research Board, 2019, 2673(4): 473-489. 
[11] NGO N S. Urban bus ridership, income, and extreme weather events[J]. Transportation Research Part D: Transport and Environment, 2019, 77: 464-475. 
[12]陈昕. 基于多源数据的城市地铁系统运营事故特征分析与延误时间预测[D]. 南京: 东南大学, 2022. 
CHEN X. Unplanned disruptions characteristics analysis and operational delay prediction in urban railway systems based on multi-source data[D].Nanjing: Southeast University, 2022. 
[13] ZHANG S, CHENG Y Q, CHEN K M, et al. A general metro timetable rescheduling approach for the minimisation of the capacity loss after random line disruption[J]. Transportmetrica A: Transport Science, 2024, 20(3): 1-25. 
[14] PAN S Z, YAN H, HE J, et al. Vulnerability and resilience of transportation systems: a recent literature review [J]. Physica A: Statistical Mechanics and Its Applications, 2021, 581: 126235. 
[15] GUO J W, XIE Z Q, LI Q L, et al. Railway passenger flow recognition algorithm for terminal station based on cost theory and automatic frequency control[J]. IEEE Access, 2020, 8: 26885-26892. 
[16]WU J R, LU S G, GE Y E. Identifying factors impacting customers′ perceived waiting time in high density passenger flow waiting areas[J]. Procedia-social and Behavioral Sciences, 2013, 96: 1801-1811. 
[17]戴延泽, 占曙光. 考虑碳排放的城轨开行大小交路方案分析[J]. 铁道科学与工程学报, 2022, 19(12): 3546-3556. 
DAI Y Z, ZHAN S G. Analysis of full-length and shortturn routing of urban rail transit considering carbon emission[J]. Journal of Railway Science and Engineering, 2022, 19(12): 3546-3556.
[18]新民晚报. 上海地铁2号线故障5小时 500多名乘客走出隧道[EB/OL]. [2024-01-05]. https:∥m.haiwainet. cn/middle/456689/2015/0311/content _ 28510864_1.html. 
Xinmin Evening News.More than 500 passengers walked out of the tunnel in 5 hours after the failure of Shanghai Metro Line 2[EB/OL]. [2024-01-05]. https:∥m. haiwainet.cn/ middle/ 456689/ 2015/ 0311/ content _ 28510864_1. html. 
[19] CHEN E H, YE Z R, WANG C, et al. Subway passenger flow prediction for special events using smart card data [J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(3): 1109-1120. 
[20] XING J D, YIN X L, ZHANG J, et al. Resilience modeling and improvement of metro systems considering statistical behaviors of passenger mobility[J]. International Journal of Disaster Risk Reduction, 2023, 96: 103975.

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更新日期/Last Update: 2025-05-22