城市轨道交通安全韧性管理工程研究进展与展望
Research Progress and Prospects of Safety Resilience Management Engineering for Urban Rail Transit Systems
摘要: 城市轨道交通系统作为典型的复杂社会技术系统,其运行安全受到基础设施状态、外部环境扰动、组织管理行为以及人员决策过程等多重因素影响,传统以风险识别和事故控制为核心的安全管理范式已难以满足不确定性环境下系统持续稳定运行的需求。为系统梳理城市轨道交通安全韧性领域的研究进展、理论演化与未来发展方向,本文对国内外相关研究成果进行综合评述。在辨析韧性概念由工程恢复能力向动态适应能力演进的基础上,明确城市轨道交通安全韧性的内涵,即系统通过抵抗、吸收、恢复与适应等能力,在风险扰动过程中维持关键功能并实现持续优化的能力。围绕现有研究成果,本文从城市轨道交通网络韧性、安全韧性评价以及安全韧性因素作用机理三个方面展开系统梳理。研究发现,城市轨道交通韧性研究已形成融合交通工程、安全科学与管理科学的交叉研究领域。其中,网络韧性研究较为成熟,主要基于复杂网络理论分析系统结构脆弱性,并围绕网络优化与恢复策略提升系统抗扰能力;安全韧性评价研究逐渐由单一风险分析转向多维能力评估,但现有研究仍较多围绕火灾、暴雨等特定灾害情景展开,评价体系存在灾种适应性不足和指标体系碎片化问题;安全韧性作用机理研究进一步关注因素之间的关联关系与演化过程,但对复杂系统中动态适应行为、组织学习机制以及多层级因素耦合作用的解释仍显不足。总体来看,现有研究在安全与韧性融合、宏观网络与微观运行要素协同以及动态治理机制构建方面仍存在深化空间。未来研究应进一步推动城市轨道交通安全管理由传统风险控制范式向动态韧性治理范式转变,加强对人员、组织与技术系统协同适应机制的研究,构建面向全过程、多尺度和动态演化的安全韧性理论体系,为城市轨道交通系统安全治理能力提升提供理论支撑。
Abstract: As a typical complex socio-technical system, the operational safety of urban rail transit systems is affected by multiple factors, including infrastructure conditions, external environmental disturbances, organizational management behaviors, and human decision-making processes. The traditional safety management paradigm, which primarily focuses on risk identification and accident prevention, is insufficient to meet the requirements for continuous and stable system operation under uncertain environments. To summarize the research progress, theoretical evolution, and future development trends in the field of urban rail transit safety resilience, relevant studies conducted both domestically and internationally were systematically reviewed. Based on an analysis of the evolution of resilience concepts from engineering resilience to dynamic adaptive capability, the connotation of urban rail transit safety resilience was clarified. It refers to the capability of a system to maintain critical functions and achieve continuous optimization during risk disturbances through resistance, absorption, recovery, and adaptation. Existing studies were systematically reviewed from three perspectives: urban rail transit network resilience, safety resilience assessment, and the mechanisms underlying safety resilience factors. The results indicate that urban rail transit resilience research has developed into an interdisciplinary field integrating transportation engineering, safety science, and management science. Network resilience research has achieved relatively mature development, mainly focusing on system structural vulnerability analysis based on complex network theory and improvement of disturbance resistance through network optimization and recovery strategies. Safety resilience assessment has gradually evolved from single-risk analysis toward multidimensional capability evaluation; however, existing studies remain mainly focused on specific disaster scenarios, such as fires and heavy rainfall events, resulting in insufficient adaptability across different disaster types and fragmented indicator systems. Research on safety resilience mechanisms has increasingly emphasized the interactions and evolutionary processes among influencing factors; nevertheless, the explanations of dynamic adaptive behaviors, organizational learning mechanisms, and multi-level factor coupling effects in complex systems remain inadequate. Overall, further improvements are still required in the integration of safety and resilience, the coordination between macro-level networks and micro-level operational elements, and the development of dynamic governance mechanisms. Future research should promote the transformation of urban rail transit safety management from a traditional risk-control paradigm toward a dynamic resilience-governance paradigm, strengthen investigations into the synergistic adaptation mechanisms among personnel, organizations, and technical systems, and establish a safety resilience theoretical framework characterized by whole-process, multi-scale, and dynamic evolution, thereby providing theoretical support for improving the safety governance capability of urban rail transit systems.
文章引用:王子旋. 城市轨道交通安全韧性管理工程研究进展与展望[J]. 管理科学与工程, 2026, 15(6): 1091-1102. https://doi.org/10.12677/mse.2026.156106

参考文献

[1] 马飞, 杨滢萱, 杨治杰, 等. 基于时空图神经网络的暴雨灾害下城市轨道交通客流恢复力评估方法[J/OL]. 交通运输工程学报, 1-17.
https://doi.org/10.19818/j.cnki.1671-1637.2026.229, 2026-04-10.
[2] Bai, Z., Zhang, P., Sun, L., Li, B. and Zhang, J. (2025) Fire Resilience Assessment and Application in Urban Rail Transit Systems. Systems, 13, Article No. 761.
https://doi.org/10.3390/systems13090761
[3] 潘昭宇. “十五五”时期城市轨道交通发展思路及重点任务[J]. 铁道运输与经济, 2026, 48(4): 115-125.
[4] Bi, W., Linkov, I. and MacAskill, K. (2025) Supporting Urban Sustainability through Resilient Rail Transit Systems. Cities, 167, Article ID: 106373.
https://doi.org/10.1016/j.cities.2025.106373
[5] Holling, C.S. (1996) Engineering Resilience versus Ecological Resilience. In: Schulze, P.C., Ed., Engineering within Ecological Constraints, National Academy Press, 31-44.
[6] Holling, C.S. (1973) Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics, 4, 1-23.
https://doi.org/10.1146/annurev.es.04.110173.000245
[7] Folke, C. (2006) Resilience: The Emergence of a Perspective for Social-Ecological Systems Analyses. Global Environmental Change, 16, 253-267.
https://doi.org/10.1016/j.gloenvcha.2006.04.002
[8] 杨钰莹, 郭海湘. 灾害链视角下城市韧性影响因素研究[J]. 中国安全科学学报, 2025, 35(11): 190-197.
[9] Tian, T., Liang, Y., Peng, Z., Cheng, Y. and Chen, K. (2023) Assessing the Dynamic Resilience of Urban Rail Transit Networks during Their Evolution Using a Ridership-Weighted Network. PLOS ONE, 18, e0291639.
https://doi.org/10.1371/journal.pone.0291639
[10] Elliott, J. (2016) Safety I and Safety II: The Past and Future of Safety Management. Ergonomics, 59, 859-860.
https://doi.org/10.1080/00140139.2015.1093290
[11] 樊燕燕, 牛瑞. 基于ISM-BN-FDNA的URT运营安全系统韧性评价[J]. 铁道科学与工程学报, 2026, 23(2): 888-901.
[12] 张翕然, 李正中, 张馨, 等. 城市轨道交通系统韧性研究现状及展望[J]. 交通信息与安全, 2024, 42(4): 1-11.
[13] Murray-Tuite, P.M. (2006) A Comparison of Transportation Network Resilience under Simulated System Optimum and User Equilibrium Conditions. Proceedings of the 2006 Winter Simulation Conference, Monterey, 3-6 December 2006, 1398-1405.
https://doi.org/10.1109/wsc.2006.323240
[14] 仇保兴. 构建韧性城市交通五准则[J]. 城市发展研究, 2017, 24(11): 1-8+149.
[15] Janić, M. (2015) Reprint of “Modelling the Resilience, Friability and Costs of an Air Transport Network Affected by a Large-Scale Disruptive Event”. Transportation Research Part A: Policy and Practice, 81, 77-92.
https://doi.org/10.1016/j.tra.2015.07.012
[16] Adjetey-Bahun, K., Birregah, B., Châtelet, E. and Planchet, J. (2016) A Model to Quantify the Resilience of Mass Railway Transportation Systems. Reliability Engineering & System Safety, 153, 1-14.
https://doi.org/10.1016/j.ress.2016.03.015
[17] Wang, N. and Yuen, K.F. (2022) Resilience Assessment of Waterway Transportation Systems: Combining System Performance and Recovery Cost. Reliability Engineering & System Safety, 226, Article ID: 108673.
https://doi.org/10.1016/j.ress.2022.108673
[18] 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.
[19] 范维澄. 以安全韧性城市建设推进公共安全治理现代化[J]. 人民论坛·学术前沿, 2022(Z1): 14-24.
[20] 汪洋, 黄金辉, 付姗姗, 等. 系统安全的思维转型: 风险与韧性的比较研究[J]. 中国安全科学学报, 2018, 28(1): 62-68.
[21] 黄浪, 吴超, 杨冕, 等. 韧性理论在安全科学领域中的应用[J]. 中国安全科学学报, 2017, 27(3): 1-6.
[22] 李瑞奇, 黄弘, 周睿. 基于韧性曲线的城市安全韧性建模[J]. 清华大学学报(自然科学版), 2020, 60(1): 1-8.
[23] 颜红艳, 宁海, 易欣. 基于Delphi-IAHP-SPA-GCM的城市轨道交通项目运维韧性评价[J]. 铁道科学与工程学报, 2025, 22(8): 3680-3690.
[24] Zhang, X., Miller-Hooks, E. and Denny, K. (2015) Assessing the Role of Network Topology in Transportation Network Resilience. Journal of Transport Geography, 46, 35-45.
https://doi.org/10.1016/j.jtrangeo.2015.05.006
[25] Zhang, D., Du, F., Huang, H., Zhang, F., Ayyub, B.M. and Beer, M. (2018) Resiliency Assessment of Urban Rail Transit Networks: Shanghai Metro as an Example. Safety Science, 106, 230-243.
https://doi.org/10.1016/j.ssci.2018.03.023
[26] Berche, B., von Ferber, C., Holovatch, T. and Holovatch, Y. (2009) Resilience of Public Transport Networks against Attacks. The European Physical Journal B, 71, 125-137.
https://doi.org/10.1140/epjb/e2009-00291-3
[27] Berche, B., Ferber, C.V., Holovatch, T. and Holovatch, Y. (2012) Transportation Network Stability: A Case Study of City Transit. Advances in Complex Systems, 15, Article ID: 1250063.
https://doi.org/10.1142/s0219525912500634
[28] Chen, J., Liu, J., Peng, Q. and Yin, Y. (2022) Resilience Assessment of an Urban Rail Transit Network: A Case Study of Chengdu Subway. Physica A: Statistical Mechanics and Its Applications, 586, Article ID: 126517.
https://doi.org/10.1016/j.physa.2021.126517
[29] 侯本伟, 游丹, 范世杰, 等. 基于网络效率的城市轨道交通网络抗震韧性评估[J]. 清华大学学报(自然科学版), 2024, 64(3): 509-519.
[30] 杨向飞, 童冬冬, 张静芳. 基于复杂网络的城市轨道交通网络韧性分析[J]. 中国铁路, 2025(11): 141-150.
[31] Chopra, S.S., Dillon, T., Bilec, M.M. and Khanna, V. (2016) A Network-Based Framework for Assessing Infrastructure Resilience: A Case Study of the London Metro System. Journal of The Royal Society Interface, 13, Article ID: 20160113.
https://doi.org/10.1098/rsif.2016.0113
[32] 马飞, 赵成勇, 孙启鹏, 等. 重大公共卫生灾害主动限流背景下城市轨道交通网络集成韧性[J]. 交通运输工程学报, 2023, 23(1): 208-221.
[33] Li, M., Wang, H. and Wang, H. (2019) Resilience Assessment and Optimization for Urban Rail Transit Networks: A Case Study of Beijing Subway Network. IEEE Access, 7, 71221-71234.
https://doi.org/10.1109/access.2019.2919105
[34] Lu, Q. (2018) Modeling Network Resilience of Rail Transit under Operational Incidents. Transportation Research Part A: Policy and Practice, 117, 227-237.
https://doi.org/10.1016/j.tra.2018.08.015
[35] Xu, Z., Chopra, S.S. and Lee, H. (2022) Resilient Urban Public Transportation Infrastructure: A Comparison of Five Flow-Weighted Metro Networks in Terms of the Resilience Cycle Framework. IEEE Transactions on Intelligent Transportation Systems, 23, 12688-12699.
https://doi.org/10.1109/tits.2021.3116667
[36] Wang, J., Liao, F., Wu, J., Sun, H., Wang, W. and Gao, Z. (2023) Measurement of Functional Resilience of Transport Network: The Case of the Beijing Subway Network. Transport Policy, 140, 54-67.
https://doi.org/10.1016/j.tranpol.2023.06.016
[37] Bruneau, M., Chang, S.E., Eguchi, R.T., Lee, G.C., O’Rourke, T.D., Reinhorn, A.M., et al. (2003) A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthquake Spectra, 19, 733-752.
https://doi.org/10.1193/1.1623497
[38] 吕彪, 管心怡, 高自强. 地铁网络服务韧性评估与最优恢复策略[J]. 交通运输系统工程与信息, 2021, 21(5): 198-205+221.
[39] Aparicio, J.T., Arsenio, E., Santos, F.C. and Henriques, R. (2022) LINES: muLtImodal traNsportation rEsilience analySis. Sustainability, 14, Article No. 7891.
https://doi.org/10.3390/su14137891
[40] Chen, J., Liu, J., Du, B., Peng, Q. and Yin, Y. (2022) Resilience Assessment of an Urban Rail Transit Network under Short-Term Operational Disturbances. IEEE Transactions on Intelligent Transportation Systems, 23, 24841-24853.
https://doi.org/10.1109/tits.2022.3195937
[41] Chen, J., Liu, J., Peng, Q. and Yin, Y. (2022) Strategies to Enhance the Resilience of an Urban Rail Transit Network. Transportation Research Record: Journal of the Transportation Research Board, 2676, 342-354.
https://doi.org/10.1177/03611981211037888
[42] 张洁斐, 任刚, 马景峰, 等. 基于韧性评估的地铁网络修复时序决策方法[J]. 交通运输系统工程与信息, 2020, 20(4): 14-20.
[43] 黄莺, 刘梦茹, 魏晋果, 等. 基于韧性曲线的城市地铁网络恢复策略研究[J]. 灾害学, 2021, 36(1): 32-36.
[44] Zhang, J., Ren, G. and Song, J. (2022) Resilience-Based Restoration Sequence Optimization for Metro Networks: A Case Study in China. Journal of Advanced Transportation, 2022, Article ID: 8595356.
https://doi.org/10.1155/2022/8595356
[45] 张雯婕, 胡军红, 闻成维, 等. 考虑网络韧性的城市轨道交通故障恢复研究[J]. 中国安全科学学报, 2023, 33(4): 179-186.
[46] Li, Z., Yin, J., Chai, S., Tang, T. and Yang, L. (2023) Optimization of System Resilience in Urban Rail Systems: Train Rescheduling Considering Congestions of Stations. Computers & Industrial Engineering, 185, Article ID: 109657.
https://doi.org/10.1016/j.cie.2023.109657
[47] Ju, Y., Yuan, H., Li, Z., Gan, M. and Chen, Y. (2022) Multilayer Structures and Resilience Evaluation for Multimode Regional Rail Transit System. IET Intelligent Transport Systems, 16, 843-859.
https://doi.org/10.1049/itr2.12179
[48] 宋英华, 李玉枝, 霍非舟, 等. 城区内涝条件下城市公交-地铁双层交通网络的脆弱性分析[J]. 安全与环境工程, 2021(2): 114-120.
[49] Baggag, A., Abbar, S., Zanouda, T. and Srivastava, J. (2018) Resilience Analytics: Coverage and Robustness in Multi-Modal Transportation Networks. EPJ Data Science, 7, 1-21.
https://doi.org/10.1140/epjds/s13688-018-0139-7
[50] 汤洪霞, 马桂芸, 杨淼, 等. 突发事件情景下公交-地铁复合网络韧性评估及修复策略优化[J/OL]. 铁道标准设计, 1-10.
https://doi.org/10.13238/j.issn.1004-2954.202510270005, 2026-09-13.
[51] 黄亚江, 李书全, 项思思. 基于AHP-PSO模糊组合赋权法的地铁火灾安全韧性评估[J]. 灾害学, 2021, 36(3): 15-20+40.
[52] 夏侯遐迩, 颜紫璇, 罗扬, 等. 面向设计的地铁车站防火安全韧性评价[J]. 中国安全生产科学技术, 2022, 18(12): 169-176.
[53] 刘敬严, 陈佳, 田静, 等. 韧性理念下地铁火灾灾害风险二维云模型预警[J]. 灾害学, 2023, 38(3): 43-47+74.
[54] 汤青慧, 刘硕, 刘文杰. 基于改进变权物元可拓模型的地铁车站火灾安全韧性评价[J]. 安全与环境学报, 2024, 24(4): 1346-1355.
[55] Jiao, L., Zhu, Y., Huo, X., Wu, Y. and Zhang, Y. (2023) Resilience Assessment of Metro Stations against Rainstorm Disaster Based on Cloud Model: A Case Study in Chongqing, China. Natural Hazards, 116, 2311-2337.
https://doi.org/10.1007/s11069-022-05765-2
[56] 祝连波, 王世笛, 林陵娜, 等. 基于博弈论组合赋权-物元可拓模型的地铁车站抗涝韧性评估研究[J]. 灾害学, 2023, 38(3): 1-6+42.
[57] 陈娜, 郭浩然, 张志鹏, 等. 基于H-OWA算子和投影寻踪的地铁站水灾安全韧性评估[J]. 中国安全科学学报, 2023, 33(4): 148-154.
[58] Guo, D.S., Yang, X.X., Yang, J.C., Wu, H., Meng, F. and Chen, R. (2026) Assessing Subway Station Flood Risks with a Resilience Framework: Combining Weighting Methods and Two-Dimensional Cloud Model. Tunnelling and Underground Space Technology, 168, Article ID: 107170.
https://doi.org/10.1016/j.tust.2025.107170
[59] Xu, F., Fang, D., Chen, B. and Wang, H. (2024) Resilience Assessment of Subway System to Waterlogging Disaster. Sustainable Cities and Society, 113, Article ID: 105710.
https://doi.org/10.1016/j.scs.2024.105710
[60] 王起全, 冯炜翔, 杨松立. 基于SD-MEE模型的地铁拥挤踩踏事故韧性评估[J]. 中国安全科学学报, 2025, 35(12): 187-195.
[61] 霍小森, 舒鑫宇, 焦柳丹. 突发公共卫生事件下城市轨道交通系统适灾韧性评估[J]. 都市快轨交通, 2023, 36(5): 152-158+164.
[62] 杜修力, 张洋, 缪惠全, 等. 韧性城市视角下地铁系统安全运营评价指标体系[J]. 自然灾害学报, 2023, 32(3): 1-13.
[63] 赵冬月, 陈乾, 聂士斌, 等. 多事件下城市生命线系统运营期安全韧性评估方法[J]. 清华大学学报(自然科学版), 2025, 65(4): 732-741.
[64] Hong, J., Jiang, R., Feng, C. and Li, X. (2026) Identification and Quantitative Evaluation of Disaster Resilience for Urban Metro Systems. Natural Hazards, 122, Article No. 112.
https://doi.org/10.1007/s11069-025-07788-x
[65] Wei, Y., Liang, J., Deng, Y., Dou, F., Ning, Y., Zhou, D., et al. (2023) Resilience Assessment of Beijing Subway Lines under Extreme Precipitation Weather. Applied Sciences, 13, Article No. 3964.
https://doi.org/10.3390/app13063964
[66] Yin, J., Ren, X., Liu, R., Tang, T. and Su, S. (2022) Quantitative Analysis for Resilience-Based Urban Rail Systems: A Hybrid Knowledge-Based and Data-Driven Approach. Reliability Engineering & System Safety, 219, Article ID: 108183.
https://doi.org/10.1016/j.ress.2021.108183
[67] 黄亚江, 李书全, 李益锌, 等. 基于DEMATEL-ISM-ANP的地铁运营安全韧性综合评价[J]. 中国安全科学学报, 2022, 32(6): 171-177.
[68] 李华, 乔峥元. 地铁站抗涝韧性影响因素识别与分层研究[J]. 安全与环境学报, 2023, 23(5): 1457-1464.
[69] 申玲, 唐令怡, 廖洁. 基于CN-FRAM的公共交通设备设施系统运营安全韧性度量[J]. 中国安全科学学报, 2024, 34(3): 45-54.
[70] Qin, R., Zhang, X., Shi, C., Zhao, Q., Yu, T., Xiao, J., et al. (2025) Identifying Critical Fire Risk Transmission Paths in Subway Stations: A PSR-DEMATEL-ISM Approach. Fire, 8, Article No. 332.
https://doi.org/10.3390/fire8080332