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

Shohel Amin, Umma Tamima, Luis Amador

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.
Original languageEnglish
Pages (from-to)45-61
Number of pages17
JournalTransportation Research Part A: Policy and Practice
Volume119
Early online date14 Nov 2018
DOIs
Publication statusPublished - Jan 2019

Fingerprint

Pavements
road
management
vulnerability
budget
damages
Decision support systems
Patient rehabilitation
Linear programming
Disasters
Deterioration
Roads
Coast
Pavement
Emergency response
Bangladesh
community
rehabilitation
disaster
programming

Bibliographical note

© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Keywords

  • Cyclone
  • Geo-physical risk
  • Maintenance
  • Optimization
  • Pavement deterioration
  • Vulnerability

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation
  • Management Science and Operations Research

Cite this

Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas. / Amin, Shohel; Tamima, Umma; Amador, Luis.

In: Transportation Research Part A: Policy and Practice, Vol. 119, 01.2019, p. 45-61.

Research output: Contribution to journalArticle

@article{295cfa8bbd7a4eecb3661d6ce34bd2ae,
title = "Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas",
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.",
keywords = "Cyclone, Geo-physical risk, Maintenance, Optimization, Pavement deterioration, Vulnerability",
author = "Shohel Amin and Umma Tamima and Luis Amador",
note = "{\circledC} 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Copyright {\circledC} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.",
year = "2019",
month = "1",
doi = "10.1016/j.tra.2018.11.001",
language = "English",
volume = "119",
pages = "45--61",
journal = "Transportation Research, Part A: Policy and Practice",
issn = "0965-8564",
publisher = "Elsevier",

}

TY - JOUR

T1 - Optimal pavement management: Resilient roads in support of emergency response of cyclone affected coastal areas

AU - Amin, Shohel

AU - Tamima, Umma

AU - Amador, Luis

N1 - © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

PY - 2019/1

Y1 - 2019/1

N2 - 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.

AB - 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.

KW - Cyclone

KW - Geo-physical risk

KW - Maintenance

KW - Optimization

KW - Pavement deterioration

KW - Vulnerability

UR - http://www.scopus.com/inward/record.url?scp=85056576551&partnerID=8YFLogxK

U2 - 10.1016/j.tra.2018.11.001

DO - 10.1016/j.tra.2018.11.001

M3 - Article

VL - 119

SP - 45

EP - 61

JO - Transportation Research, Part A: Policy and Practice

JF - Transportation Research, Part A: Policy and Practice

SN - 0965-8564

ER -