IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5379-d1100545.html
   My bibliography  Save this article

Reliability and Robustness Assessment of Highway Networks under Multi-Hazard Scenarios: A Case Study in Xinjiang, China

Author

Listed:
  • Weihua Zhu

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China)

  • Shoudong Wang

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China)

  • Shengli Liu

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China)

  • Xueying Gao

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China)

  • Pengchong Zhang

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Laboratory of Transport Safety and Emergency Technology, Beijing 100028, China)

  • Lixiao Zhang

    (State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China)

Abstract

The robustness and reliability capacities of highways are particularly critical when dealing with emergencies in order to ensure user safety following disaster events. Assessing the robustness and reliability of highways under multi-hazard scenarios and evaluating the impact of planning on them have become urgent topics. In this study, we use the Xinjiang Production and Construction Corps’ (XPCC) existing and planned arterial highway networks in China for research. Based on the multi-hazard information, we established and employed four attack strategies on the existing and planned arterial highway networks. The results show that the exposure susceptibility coefficient (ESC) strategy has a higher destruction capability than the random attack strategy, which is close to the greedy algorithm coefficient (GAC) strategy. In addition, attacks have negligible impacts on connectivity reliability and robustness but significantly affect travel time reliability and robustness. When the number of removed edges reaches 20 using the ESC strategy, the travel time reliability drops to 0.4 for the existing highway network. In addition, the planned highway network significantly improves the reliability and robustness with regard to multi-hazard scenarios, especially for travel time reliability. Travel time reliability is improved by 10% under the historical damage records coefficient (HDRC) and ESC attacks. Our study shows that planning promotes the construction of a resilient transportation system in multi-hazard scenarios, providing valuable information for resilient transportation construction.

Suggested Citation

  • Weihua Zhu & Shoudong Wang & Shengli Liu & Xueying Gao & Pengchong Zhang & Lixiao Zhang, 2023. "Reliability and Robustness Assessment of Highway Networks under Multi-Hazard Scenarios: A Case Study in Xinjiang, China," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5379-:d:1100545
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5379/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/5379/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carrion, Carlos & Levinson, David, 2012. "Value of travel time reliability: A review of current evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 720-741.
    2. Zhu, Weihua & Liu, Kai & Wang, Ming & Yan, Xiaoyong, 2018. "Enhancing robustness of metro networks using strategic defense," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1081-1091.
    3. Shams, Kollol & Asgari, Hamidreza & Jin, Xia, 2017. "Valuation of travel time reliability in freight transportation: A review and meta-analysis of stated preference studies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 228-243.
    4. Boakye, Jessica & Guidotti, Roberto & Gardoni, Paolo & Murphy, Colleen, 2022. "The role of transportation infrastructure on the impact of natural hazards on communities," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    6. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tao, Xuezong & Zhu, Lichao, 2020. "Meta-analysis of value of time in freight transportation: A comprehensive review based on discrete choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 213-233.
    2. Zhaoqi Zang & Richard Batley & Xiangdong Xu & David Z. W. Wang, 2022. "On the value of distribution tail in the valuation of travel time variability," Papers 2207.06293, arXiv.org, revised Dec 2023.
    3. Li, Zheng, 2018. "Unobserved and observed heterogeneity in risk attitudes: Implications for valuing travel time savings and travel time variability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 12-18.
    4. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    5. Fu, Jianhua & Zhang, Yongqing, 2020. "Valuation of travel time reliability: Considering the traveler's adaptive expectation with an indifference band on daily trip duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 337-353.
    6. Wardman, Mark, 2022. "Meta-analysis of price elasticities of travel demand in great britain: Update and extension," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 1-18.
    7. Bergström, Anna & Krüger, Niclas A., 2013. "Modeling passenger train delay distributions: evidence and implications," Working papers in Transport Economics 2013:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    8. Shang, Qingxue & Guo, Xiaodong & Li, Jichao & Wang, Tao, 2022. "Post-earthquake health care service accessibility assessment framework and its application in a medium-sized city," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Wen, Tao & Gao, Qiuya & Chen, Yu-wang & Cheong, Kang Hao, 2022. "Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    10. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    11. Xingyuan Li & Jing Bai, 2021. "A Ridesharing Choice Behavioral Equilibrium Model with Users of Heterogeneous Values of Time," IJERPH, MDPI, vol. 18(3), pages 1-22, January.
    12. Mengying Cui & David Levinson, 2018. "Accessibility analysis of risk severity," Transportation, Springer, vol. 45(4), pages 1029-1050, July.
    13. Engelson, Leonid & Fosgerau, Mogens, 2016. "The cost of travel time variability: Three measures with properties," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 555-564.
    14. Janson, Michael & Levinson, David, 2014. "HOT or not," Research in Transportation Economics, Elsevier, vol. 44(C), pages 21-32.
    15. Kent, Jennifer L. & Mulley, Corinne & Stevens, Nick, 2020. "Challenging policies that prohibit public transport use: Travelling with pets as a case study," Transport Policy, Elsevier, vol. 99(C), pages 86-94.
    16. Rimjha, Mihir & Hotle, Susan & Trani, Antonio & Hinze, Nicolas, 2021. "Commuter demand estimation and feasibility assessment for Urban Air Mobility in Northern California," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 506-524.
    17. Xinyuan Chen & Ruyang Yin & Qinhe An & Yuan Zhang, 2021. "Modeling a Distance-Based Preferential Fare Scheme for Park-and-Ride Services in a Multimodal Transport Network," Sustainability, MDPI, vol. 13(5), pages 1-14, March.
    18. Ali Nouri Qarahasanlou & Ali Zamani & Abbas Barabadi & Mahdi Mokhberdoran, 2021. "Resilience Assessment: A Performance-Based Importance Measure," Energies, MDPI, vol. 14(22), pages 1-16, November.
    19. Xiao, Yu & Fukuda, Daisuke, 2015. "On the cost of misperceived travel time variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 96-112.
    20. Jia Guo & Yusak Susilo & Constantinos Antoniou & Anna Pernestål Brenden, 2020. "Influence of Individual Perceptions on the Decision to Adopt Automated Bus Services," Sustainability, MDPI, vol. 12(16), pages 1-13, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5379-:d:1100545. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.