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Assessing Critical Road Sections: A Decision Matrix Approach Considering Safety and Pavement Condition

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  • Asnake Adraro Angelo

    (Department of Civil Engineering, Division of Global Architecture, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Japan
    Addis Ababa City Roads Authority, Sar Bet, Pushkin RA, Addis Ababa P.O. Box 9206, Ethiopia)

  • Kotaro Sasai

    (Department of Civil Engineering, Division of Global Architecture, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Japan)

  • Kiyoyuki Kaito

    (Department of Civil Engineering, Division of Global Architecture, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Japan)

Abstract

Identifying critical road sections that require prompt attention is essential for road agencies to prioritize monitoring, maintenance, and rehabilitation efforts and improve overall road conditions and safety. This study suggests a decision matrix with a hierarchical structure that factors in the pavement deterioration rate, infrastructure safety, and crash history to identify these sections. A Markov mixed hazard model was used to assess each section’s deterioration rate. The safety of the road sections was rated with the International Road Assessment Program star rating protocol considering all road users. Early detection of sections with fast deterioration and poor safety conditions allows for preventive measures to be taken and to reduce further deterioration and traffic crashes. Additionally, including crash history data in the decision matrix helps to understand the possible causes of a crash and is useful in developing safety policies. The proposed method is demonstrated using data from 4725 road sections, each 100 m, in Addis Ababa, Ethiopia. The case study results show that the proposed decision matrix can effectively identify critical road sections which need close attention and immediate action. As a result, the proposed method can assist road agencies in prioritizing inspections, maintenance, and rehabilitation decisions and effectively allocate budgets and resources.

Suggested Citation

  • Asnake Adraro Angelo & Kotaro Sasai & Kiyoyuki Kaito, 2023. "Assessing Critical Road Sections: A Decision Matrix Approach Considering Safety and Pavement Condition," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7244-:d:1133835
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    References listed on IDEAS

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    Cited by:

    1. Liang Zhang & Zhongxiang Huang & Aiwu Kuang & Jie Yu & Mingmao Cai, 2024. "Estimation of Crash Modification Factors (CMFs) in Mountain Freeways: Considering Temporal Instability in Crash Data," Sustainability, MDPI, vol. 16(12), pages 1-22, June.
    2. Xunqian Xu & Siwen Wang & Fengyi Kang & Shue Li & Qi Li & Tao Wu, 2024. "Multi-Attribute Decision-Making Method in Preventive Maintenance of Asphalt Pavement Based on Optimized Triangular Fuzzy Number," Sustainability, MDPI, vol. 16(7), pages 1-20, March.

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