Markov deterioration hazard model for road network deterioration forecast for national road networks in Lao PDR

Name: Souvikhane Hanpasith

Organization : Osaka University. Graduate School of Engineering

Email : souvikhane@gmail.com

Name: Sasai, Kotaro

Organization : Osaka University. Graduate School of Engineering

Email : k.sasai@civil.eng.osaka-u.ac.jp

Name: Kaito, Kiyoyuki

Organization : Osaka University. Graduate School of Engineering

Email : kaito@ga.eng.osaka-u-ac.jp

keyword: Markov hazard model

LCSH: Road construction industry -- Management

LCSH: Roads -- Deterioration

Abstract: The primary objectives of road management systems are to estimate short- and long-term budget demands and establish a priority list of projects under fiscal constraints. Understanding road network deterioration is critical for predicting future conditions and developing appropriate maintenance and rehabilitation strategies. Various factors affect the deterioration speeds of road surfaces including traffic volume and environmental conditions, which are also the main uncertainties in developing the deterioration model, particularly for the Lao road management system. This paper aims to develop a road deterioration forecasting model using a Markov deterioration hazard model for prediction of the deterioration process for the national road network in Lao PDR using the international roughness index. The Markov deterioration hazard model estimates the hazard rates which are used to determine the Markov transition probabilities between the pavement’s condition states defined on a discrete scale during inspection time. Then, the estimated transition probabilities can be used to forecast and predict life expectancy. The Markov deterioration hazard model is also capable of handling roughness condition data containing irregular inspection intervals. The empirical study used historical roughness index records to develop the model, incorporating traffic volume and pavement type data from the Lao national road maintenance system. The data set from the Lao road management system was composed of 22 road sections totaling 2,769 km in length. The results reveal the service life expectancy of two core networks, core network 1 and core network 2, to be 9.28 and 7.51 years, respectively. The analyses on deterioration process and life expectancy help the Lao road management system improve its road maintenance strategy, determine the maintenance period, and prioritize road network sections for maintenance. Furthermore, this study's results could support decision-making in terms of performance-based road contracts for maintenance

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2023

Modified: 2024-04-02

Issued: 2024-04-02

BibliograpyCitation : In Chulalongkorn University. 5th International Conference on Civil and Building Engineering Informatics (ICCBEI 2023) (pp.342-351). Bangkok : Chulalongkorn University

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