Comparison of pavement network management tools and its probabilistic of pavement engineering for Western Australia

Abstract

Since the Association of American State Highway Officials (AASHO) road test of 1956-62 at Ottawa in Illinois, enormous efforts have been devoted to improve the methodologies and engineering techniques of pavement performance predication. For instance, the successful implementation of the Network Optimization Systems (NOSs) in the Arizona Department of Transportation (ADOT) in the 1980-82 was one of a tremendous effort that represented advancement in predication methodology and engineering technique by using Markov Chain-Process based to define the transition process of pavement network condition. The main role of this paper is to evaluate and analysis the pavement network performance of Western Australia (WA) and also applied the existing pavement management tools relevant to WA road networks. Two approaches were used to evaluate and analysis the pavement network of WA. First, the current pavement performance data was used to assess the State road networks and then, predict the future from the past and current pavement network data. Second, the Probabilistic network – Markov-Chain Process and Chapman-Kolmogorov method was used to predict the pavement behavior in Western Australia. The results showed that the pavement performance of the predicting model using probabilistic network process (i.e. Linear) perform well in all categories as compared to the past 30 years LRDM data inventory. This study will draw into appropriate and effective pavement engineering management system to account for proper pavement design, preliminary planning, future pavement M & R networks, service life and functionality.