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 pavements 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