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Dynamic Evaluation of Road Network Resilience to Traffic Accidents: An Emergency Management Perspective for Sustainable Cities in China

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  • Gang Yu

    (SILC Business School, Shanghai University, Shanghai 201800, China
    Shanghai Urban Construction Group Research Center for Building Industrialization, Shanghai University, Shanghai 200072, China)

  • Jiayi Xie

    (SILC Business School, Shanghai University, Shanghai 201800, China
    Shanghai Urban Construction Group Research Center for Building Industrialization, Shanghai University, Shanghai 200072, China)

  • Vijayan Sugumaran

    (Center for Data Science and Big Data Analytics, Oakland University, Rochester, MI 48309, USA
    Department of Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, MI 48309, USA)

Abstract

When assessing road network resilience, emergency management behavior should be considered, as this represents the road network’s capacity to adapt to and recover from traffic accidents. Given the timeliness and variability of emergency management behavior, deterministic approaches seem inadequate to represent real road network performance. Thus, this paper innovatively designs an emergency management perspective-based dynamic evaluation method of road network resilience to traffic accidents. Firstly, based on four stages of emergency management, a road network resilience evaluation index system encompassing resilience capabilities, resilience attributes and traffic accident emergency management ability indicators is constructed. Afterwards, the gray relational technique for order preference by similarity to the ideal solution (GRA-TOPSIS) evaluation method based on combination weighting, which integrates factor analysis with hesitant intuitionistic fuzzy expert scoring, is designed to quantify resilience. Finally, the obstacle degree model is utilized for identifying resilience constraints as the input of a long short-term memory (LSTM) model to predict the resilience variation trend. The fast road network of Shanghai in China is adopted as a case study, and the results indicate that road network resilience embodies significant spatial distribution characteristics. Road length, number of tractors, perception and response and disposal time of traffic accidents cast notable effects on resilience. Additionally, some roads are forecast to show descending resilience. The proposed method is valuable for helping policymakers identify current and potential vulnerable roads and to formulate proposals to effectively improve the resilience of urban agglomerations and promote sustainable cities.

Suggested Citation

  • Gang Yu & Jiayi Xie & Vijayan Sugumaran, 2024. "Dynamic Evaluation of Road Network Resilience to Traffic Accidents: An Emergency Management Perspective for Sustainable Cities in China," Sustainability, MDPI, vol. 16(17), pages 1-28, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7385-:d:1465298
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    References listed on IDEAS

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    1. Thamer Alslamah & Yousef Mohammad Alsofayan & Mahmudul Hassan Al Imam & Monerah Abdullah Almazroa & Adil Abalkhail & Ibrahim Alasqah & Ilias Mahmud, 2023. "Emergency Medical Service Response Time for Road Traffic Accidents in the Kingdom of Saudi Arabia: Analysis of National Data (2016–2020)," IJERPH, MDPI, vol. 20(5), pages 1-11, February.
    2. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    3. Nogal, M. & Honfi, D., 2019. "Assessment of road traffic resilience assuming stochastic user behaviour," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 72-83.
    Full references (including those not matched with items on IDEAS)

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