Volume 42 Issue 3
Jun.  2024
Turn off MathJax
Article Contents
Article Navigation >  Journal of Transport Information and Safety  > 2024  >  42(3): 102-113
ZHANG Jiefei, REN Gang, TANG Lei, DU Jianwei, GU Houyu, SONG Jianhua. A Review about Resilience Evaluation for Urban Multimodal Transportation Networks[J]. Journal of Transport Information and Safety, 2024, 42(3): 102-113. doi: 10.3963/j.jssn.1674-4861.2024.03.011
Citation: ZHANG Jiefei, REN Gang, TANG Lei, DU Jianwei, GU Houyu, SONG Jianhua. A Review about Resilience Evaluation for Urban Multimodal Transportation Networks[J]. Journal of Transport Information and Safety, 2024, 42(3): 102-113. doi: 10.3963/j.jssn.1674-4861.2024.03.011
shu

A Review about Resilience Evaluation for Urban Multimodal Transportation Networks

doi: 10.3963/j.jssn.1674-4861.2024.03.011
  • 1.

    School of Mining Engineering, Anhui University of Science and Technology, Huainan 232001, Anhui, China

  • 2.

    School of Transportation, Southeast University, Nanjing 211189, China

  • Received Date: 2023-10-09
    Available Online: 2024-10-21
    Abstract
  • To improve the development of research about transportation resilience, this paper, focusing on urban multimodal transportation networks, summarizes the relevant studies on resilience evaluation in the literature. The definition and connotation of resilience are introduced. The indicators for resilience evaluation are summarized from the perspectives of network topology, supply-demand characteristics, and coupling relationships. The research of model-driven and data-driven resilience evaluation methods are introduced. The advantages and disadvantages of these methods are summarized as well. Fourth, measures to improve the resilience of transportation network are discussed from the perspectives of network design, emergency evacuation, and network restoration. The resilience optimization models and algorithms are summarized as well. The research deficiencies and future development directions are discussed. The results show that: ① the resilience evaluation of composite networks fails to fully consider the coupling characteristics. Besides, resilience evaluation is imprecise to depict variable traffic demand and travelers' travel behavior. ② The determination of indicator weights depend more on subjective judgement in model-driven resilience evaluation. Data-driven resilience evaluation focus on data analysis and result display, but lacks in-depth analysis of resilience evolution. ③ The optimization models targeting resilience improvement need to be improved in multi-objective decision making, computational efficiency in large-scale networks, and reproduction of real scenes. From these results, the suggestions for the future research are as follows: ① in the development of the network and the selection of indicators, the dependence of the composite network needs to be fully considered. Besides, and the coupling characteristics between the systems need to be scientifically reflected in evaluation models. ② It is suggested to cooperate with multiple departments to establish a complete and shared database, to explore the network resilience evaluation methods which are driven by both data and model, and to design high-efficient algorithms to support the rapid and accurate calculation of the resilience indicators. ③ The static discrete resilience evaluation should be developed into dynamic continuous resilience monitor, based on which the temporal-spatial evolution of network resilience and the evolution mechanism of traffic network resilience must be analyzed. ④ The refined network resilience decision optimization should be strengthen to reproduce the real event scenarios in data analysis and model development. Besides, it is necessary to further explore the application of AI algorithm to deal with the application of large-scale network optimization.

     

    • FullText(HTML)
  • loading
    • References(57)
  • [1]
    GU Y, FU X, LIU Z, et al. Performance of transportation network under perturbations: reliability, vulnerability, and resilience[J]. Transportation Research Part E: Logistics and Transportation Review, 2020, 133: 101809. doi: 10.1016/j.tre.2019.11.003
    [2]
    MURRAY-TUITE P. A comparison of transportation network resilience under simulated system optimum and user equilibrium conditions[C]. IEEE 2006 Winter Simulation Conference, Monterey, USA: IEEE, 2006.
    [3]
    杨金顺, 孙洪运, 李林波, 等. 道路交通系统恢复力研究进展综述[J]. 交通信息与安全, 2014, 32(3): 87-93. doi: 10.3963/j.issn.1674-4861.2014.03.018

    YANG J S, SUN H Y, LI L B, et al. Review of road transportation system resilience research[J]. Journal of Transport Information and Safety, 2014, 32(3): 87-93. (in Chinese) doi: 10.3963/j.issn.1674-4861.2014.03.018
    [4]
    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.

    ZHANG J F, REN G, MA J F, et al. Decision-making method of repair sequence for metro network based on resilience evaluation[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(4): 14-20. (in Chinese)
    [5]
    ZHOU Y M, WANG J W, YANG H. Resilience of transportation systems: concepts and comprehensive review[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20 (12): 4262-4276. doi: 10.1109/TITS.2018.2883766
    [6]
    WOODS D. Four concepts for resilience and the implications for the future of resilience engineering[J]. Reliability Engineering and System Safety, 2015, 141: 5-9. doi: 10.1016/j.ress.2015.03.018
    [7]
    MATTSSON L, JENELIUS E. Vulnerability and resilience of transport systems: a discussion of recent research[J]. Transportation Research Part A: Policy and Practice, 2015, 81: 16-34. doi: 10.1016/j.tra.2015.06.002
    [8]
    SOLTANI-SOBH A, HEASLIP K, KHOURY J E. Estimation of road network reliability on resiliency: an uncertain based model[J]. International Journal of Disaster Risk Reduction, 2015, 14: 536-544. doi: 10.1016/j.ijdrr.2015.10.005
    [9]
    ZHANG D M, DU F, HUANG H W, et al. Resiliency assessment of urban rail transit networks: Shanghai metro as an example[J]. Safety Science, 2018, 106: 230-243. doi: 10.1016/j.ssci.2018.03.023
    [10]
    IP W H, WANG D W. Resilience evaluation approach of transportation networks[C]. International Joint Conference on Computational Sciences and Optimization, Wuhan, China: Wuhan University, 2009.
    [11]
    ZHANG W L, WANG N Y. Resilience-based risk mitigation for road networks[J]. Structural Safety, 2016, 62: 57-65. doi: 10.1016/j.strusafe.2016.06.003
    [12]
    DONOVAN B, WORK D B. Empirically quantifying city-scale transportation system resilience to extreme events[J]. Transportation Research Part C: Emerging Technologies, 2017, 79: 333-346. doi: 10.1016/j.trc.2017.03.002
    [13]
    CHEN J Q, LIU J, PENG Q Y, et al. Resilience assessment of an urban rail transit network: a case study of Chengdu subway[J]. Physica A: Statistical Mechanics and its Applications, 2022, 586: 126517. doi: 10.1016/j.physa.2021.126517
    [14]
    ZHAO T T, ZHANG Y. Transportation infrastructure restoration optimization considering mobility and accessibility in resilience measures[J]. Transportation Research Part C: Emerging Technologies, 2020, 117: 102700. doi: 10.1016/j.trc.2020.102700
    [15]
    ZHU C L, WU J P, LIU M Y, et al. Cyber-physical resilience modelling and assessment of urban roadway system interrupted by rainfall[J]. Reliability Engineering & System Safety, 2020, 204: 107095.
    [16]
    马壮林, 程会媛, 邵逸恒, 等. 大客流干扰下多层公交－地铁网络的韧性评估[J]. 中国公路学报, 2024, 37(6): 256-278.

    MA Z L, CHENG H Y, SHAO Y H, et al. Resilience assessment of multilayer bus-metro network under large passenger flow interference[J]. China Journal of Highway and Transport, 2024, 37(6): 256-278. (in Chinese)
    [17]
    NOGAL M, O'CONNOR A, MARTINEZ- PASTOR B, et al. Novel probabilistic resilience assessment framework of transportation networks against extreme weather events[J]. Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2017, 3(3): 04017004.
    [18]
    GAUTHIER P, FURNO A, EL F N E. Road network resilience: how to identify critical links subject to day-to-day disruptions[J]. Transportation Research Record, 2018, 2672(1): 54-65. doi: 10.1177/0361198118792115
    [19]
    ZHANG X G, MAHADEVAN S, SANKARARAMAN S, et al. Resilience-based network design under uncertainty[J]. Reliability Engineering & System Safety, 2018, 169: 364-379.
    [20]
    KOC E, CETINER B, ROSE A, et al. Craft: comprehensive resilience assessment framework for transportation systems in urban areas[J]. Advanced Engineering Informatics, 2020, 46: 101159. doi: 10.1016/j.aei.2020.101159
    [21]
    ZHU Y, XIE K, OZBAY K, et al. Data-driven spatial modeling for quantifying network wide resilience in the aftermath of hurricanes Irene and Sandy[J]. Transportation Research Record, 2017, 2604: 9-18. doi: 10.3141/2604-02
    [22]
    MUDIGONDA S, OZBAY K, BARTIN B. Evaluating the resilience and recovery of public transit system using big data: case study from New Jersey[J]. Journal of Transportation Safety and Security, 2019, 11(5): 491-519. doi: 10.1080/19439962.2018.1436105
    [23]
    马飞, 苟慧艳, 杨梦楠, 等. 考虑灰色攻击的多制式区域轨道交通网络韧性评估[J]. 中国安全科学学报, 2023, 33(12): 148-159.

    MA F, GOU H Y, YANG M N, et al. Resilience assessment of multi-modal regional rail transit networks considering grey attack[J]. China Safety Science Journal, 2023, 33(12): 148-159. (in Chinese)
    [24]
    QI X Y, MEI G, PICCIALLI F. Resilience evaluation of urban bus-subway traffic networks for potential applications in IOT-based smart transportation[J]. IEEE Sensors Journal, 2021, 21(22): 25061-25074. doi: 10.1109/JSEN.2020.3046270
    [25]
    LIU Z Z, CHEN H, LIU E, et al. Evaluating the dynamic resilience of the multi-mode public transit network for sustainable transport[J]. Journal of Cleaner Production, 2022, 348: 131350. doi: 10.1016/j.jclepro.2022.131350
    [26]
    VODOPIVEC N, MILLER-HOOKS E. Transit system resilience: quantifying the impacts of disruptions on diverse populations[J]. Reliability Engineering and System Safety, 2019, 191: 106561. doi: 10.1016/j.ress.2019.106561
    [27]
    TANG J Q, HEINIMANN H, HAN K, et al. Evaluating resilience in urban transportation systems for sustainability: a systems-based Bayesian network model[J]. Transportation Research Part C: Emerging Technologies, 2020, 121: 102840. doi: 10.1016/j.trc.2020.102840
    [28]
    SAADAT Y, AYYUB B M, ZHANG Y J, et al. Resilience of metro rail networks: quantification with Washington, D.C. as a case study[J]. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering, 2019, 5(4): 041011. doi: 10.1115/1.4044038
    [29]
    SAADAT Y, AYYUB B M, ZHANG Y J, et al Resilience-based strategies for topology enhancement and recovery of metrorail transit networks[J]. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A: Civil Engineering, 2020, 6(2): 04020017. doi: 10.1061/AJRUA6.0001057
    [30]
    ZHU Y, OZBAY K, XIE K, et al. Using big data to study resilience of taxi and subway trips for hurricanes Sandy and Irene[J]. Transportation Research Record, 2016, 2599: 70-80. doi: 10.3141/2599-09
    [31]
    WANG H W, PENG Z R, WANG D S, et al. Evaluation and prediction of transportation resilience under extreme weather events: a diffusion graph convolutional approach[J]. Transportation Research Part C: Emerging Technologies, 2020, 115: 102619. doi: 10.1016/j.trc.2020.102619
    [32]
    ZHANG M, LIU Y F, XIAO Y X, et al. Vulnerability and resilience of urban traffic to precipitation in China[J]. International Journal of Environmental Research and Public Health, 2021, 18(23): 12342. doi: 10.3390/ijerph182312342
    [33]
    DAS R. Approach for measuring transportation network resiliency: a case study on Dhaka, Bangladesh[J]. Case Studies on Transport Policy, 2020, 8(2): 586-592. doi: 10.1016/j.cstp.2020.04.001
    [34]
    MILLER-HOOKS E, ZHANG X D, FATURECHI R. Measuring and maximizing resilience of freight transportation networks[J]. Computers and Operations Research, 2012, 39(7): 1633-1643. doi: 10.1016/j.cor.2011.09.017
    [35]
    LI Z L, JIN C, HU P, et al. Resilience-based transportation network recovery strategy during emergency recovery phase under uncertainty[J]. Reliability Engineering & System Safety, 2019, 118: 503-514.
    [36]
    吕彪, 高自强, 管心怡, 等. 基于日变交通配流的城市道路网络韧性评估[J]. 西南交通大学学报, 2020, 55(6): 1181-1190

    LYU B, GAO Z Q, GUAN X Y, et al. Resilience assessment of urban road network based on day-to-day traffic assignment[J]. Journal of Southwest Jiaotong University, 2020, 55(6): 1181 -1190. (in Chinese)
    [37]
    吕彪, 高自强, 刘一骝. 道路交通系统韧性及路段重要度评估[J]. 交通运输系统工程与信息, 2020, 20(2): 114-121

    LYU B, GAO Z Q, LIU Y Y. Evaluation of road transportation system resilience and link importance[J]. Journal of Transportation System Engineering and Information Technology, 2020, 20(2): 114-121. (in Chinese)
    [38]
    吕彪, 谢智宇, 康宇翔, 等. 基于动态分流元胞传输模型的城市道路网络韧性评估[J]. 交通运输系统工程与信息, 2022, 22(6): 134-143, 211.

    LYU B, XIE Z Y, KANG Y X, et al. Resilience assessment of urban road network based on day-to-day traffic assignment[J]. Journal of Transportation System Engineering and Information Technology, 2022, 22(6): 134-143, 211. (in Chinese)
    [39]
    LIU K Z, ZHAI C H, DONG Y. Optimal restoration schedules of transportation network considering resilience[J]. Structure and Infrastructure Engineering, 2020, 17(8): 1141-1154.
    [40]
    XU Z Z, CHOPRA S S, LEE H. Resilient urban public transportation infrastructure: a comparison of five flow-weighted metro networks in terms of the resilience cycle framework[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 12688-12699. doi: 10.1109/TITS.2021.3116667
    [41]
    WEI M, FANG S J, CHEN S, et al. Resilience assessment of road networks in the extremely severe disaster areas of the Wenchuan earthquake[J]. Frontiers in Earth Science, 2022, 10: 834302. doi: 10.3389/feart.2022.834302
    [42]
    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): 198-221

    LYU B, GUAN X Y, GAO Z Q. Evaluation and optimal recovery strategy of metro network service resilience[J]. Journal of Transportation System Engineering and Information Technology, 2021, 21(5): 198-221. (in Chinese)
    [43]
    TANG YC, BI W, VARGA L, et al. An integrated framework for managing fire resilience of metro station system: identification, assessment, and optimization[J]. International Journal of Disaster Risk Reduction, 2022, 77: 103037. doi: 10.1016/j.ijdrr.2022.103037
    [44]
    CHEN H R, ZHOU R Y, CHEN H, et al. Static and dynamic resilience assessment for sustainable urban transportation systems: a case study of Xi'an, China[J]. Journal of Cleaner Production, 2022, 368: 133237. doi: 10.1016/j.jclepro.2022.133237
    [45]
    ZHANG X, MILLER-HOOKS E, DENNY K. Assessing the role of network topology in transportation network resilience[J]. Journal of Transport Geography, 2015, 46: 35-45. doi: 10.1016/j.jtrangeo.2015.05.006
    [46]
    ZHANG Z, WOLSHON B, MURRAY- TUITE P. A conceptual framework for illustrating and assessing risk, resilience, and investment in evacuation transportation systems[J]. Transportation Research Part D: Transport and Environment, 2019, 77: 525-534. doi: 10.1016/j.trd.2019.08.016
    [47]
    WANG Y, WANG J W. Measuring and maximizing resilience of transportation systems for emergency evacuation[J]. IEEE Transactions on Engineering Management, 2020, 67(3): 603-613. doi: 10.1109/TEM.2019.2949098
    [48]
    MARZUOLI A, BOIDOT E, COLOMAR P, et al. Improving disruption management with multimodal collaborative decision-making: a case study of the Asiana crash and lessons learned[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(10): 2699-2717. doi: 10.1109/TITS.2016.2536733
    [49]
    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.

    ZHANG W J, HU J H, WEN C W, et al. Research on urban rail failure recovery considering network resilience[J]. China Safety Science Journal, 2023, 33(4): 179-186. (in Chinese)
    [50]
    路庆昌, 刘鹏, 徐标, 等. 运营事件下基于韧性的地铁网络保护决策优化[J]. 交通运输工程学报, 2023, 23(3): 209-220.

    LU Q C, LIU P, XU B, et al. Resilience-based protection decision optimization for metro network under operational incidents[J]. Journal of Traffic and Transportation Engineering, 2023, 23(3): 209-220. (in Chinese)
    [51]
    程静, 卢群, 吴同政, 等. 地铁网络级联失效恢复策略韧性评估方法[J]. 交通信息与安全, 2023, 41(4): 173-184. doi: 10.3963/j.jssn.1674-4861.2023.04.018

    CHENG J, LU Q, WU T Z, et al. A method for evaluating recovery strategies for cascade failures of metro networks[J]. Journal of Transport Information and Safety, 2023, 41(4): 173-184. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2023.04.018
    [52]
    ZHANG N, ALIPOUR A, CORONEL L. Application of novel recovery techniques to enhance the resilience of transportation networks[J]. Transportation Research Record, 2018, 2672(1): 138-147. doi: 10.1177/0361198118797510
    [53]
    GUO J N, DU Q, HE Z G, et al. A method to improve the resilience of multimodal transport network: location selection strategy of emergency rescue facilities[J]. Computers & Industrial Engineering, 2021, 161: 107678.
    [54]
    LIAO T Y, HU T Y, KO Y N. A Resilience optimization model for transportation networks under disasters[J]. Natural Hazards, 2018, 93(1): 469-489. doi: 10.1007/s11069-018-3310-3
    [55]
    SOMY S, SHAFAEI R, RAMEZANIAN R. Resilience-based mathematical model to restore disrupted road-bridge transportation networks[J]. Structure and Infrastructure Engineering, 2022, 18(9): 1334-1349. doi: 10.1080/15732479.2021.1906711
    [56]
    李兆隆, 金淳, 胡畔, 等. 基于弹复性的交通网络应急恢复阶段策略优化[J]. 系统工程理论与实践, 2019, 39(11): 2828-2841 doi: 10.12011/1000-6788-2018-0729-14

    LI Z L, JIN C, HU P, et al. Resilience-based recovery strategy optimization in emergency recovery phase for transportation networks[J]. Systems Engineering Theory & Practice, 2019, 39(11): 2828-2841. (in Chinese) doi: 10.12011/1000-6788-2018-0729-14
    [57]
    MAO X H, ZHOU J B, YUAN C W, et al. Resilience-based optimization of post disaster restoration strategy for road networks[J]. Journal of Advanced Transportation, 2021, 2021 (8): 1-15.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(6)  / Tables(2)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (123) PDF downloads(9) Cited by()
    Proportional views
    Related

    Copyright Editorial Office of Transport Information and Safety鄂ICP备05003336号-2

    Address：No. 1178，Heping Avenue, Wuchang, Wuhan, CHINA (430063)

    Tel：027-86580355 Email：jtjsj@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return