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Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas

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  • Amin, Shohel
  • Tamima, Umma
  • Amador-Jiménez, Luis E.

Abstract

Roads in poor road condition disrupt emergency operations in disaster-prone areas during emergency periods. Prolonged inundation of pavements from storm surge accelerates deterioration of pavements and increases maintenance cost. The objective of this study is to propose an optimized decision support system for pavement maintenance and rehabilitation (M&R) operations guided by geo-physical risk and community vulnerabilities. A case study of regional highways, arterial and collector roads at the district of Barguna, in Bangladesh is selected given the frequency of cyclones and storm surges in this area. A geo-physical risk and vulnerability (GEOPHRIV) index was estimated for each road’s segment by integrating the geo-physical risk; community, structure and infrastructure vulnerabilities; and damage indices. Linear programming was applied to optimize M&R strategies to ensure good pavement condition for all roads at a minimum M&R budget. Lifecycle optimization of M&R operations estimated that USD 2.49 million is the minimum annual budget that ensures having good average road’s condition in the study area. Most of the annual M&R budget will be invested for overlay and resealing treatments on the roads at high and medium GEOPHRIV areas. This study helps transportation authorities to identify deteriorated pavement sections, maintain the pavement periodically to prevent or minimize damage before storm surge, and allocate resources for M&R operations.

Suggested Citation

  • Amin, Shohel & Tamima, Umma & Amador-Jiménez, Luis E., 2019. "Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 45-61.
  • Handle: RePEc:eee:transa:v:119:y:2019:i:c:p:45-61
    DOI: 10.1016/j.tra.2018.11.001
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Weike & Tian, Xiaoli & Yu, Ao, 2020. "Is high-speed rail a catalyst for the fourth industrial revolution in China? Story of enhanced technology spillovers from venture capital," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.

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