PAVEMENT PERFORMANCE MODELLING FOR PMS

Abstract

The maintenance of flexible pavements is an essential requirement for the efficiency of a highway network. The magnitude of work involved in maintenance is very large but the funds available are not enough to meet the requirements. The need for efficient and effective management of the road network has thrown upon a challenge to the highway professionals of the country, as a whole. Pavement deterioration models, for prediction of pavement condition at a future date, form an important input in the pavement management system for i) assessing the state of condition of the pavements ii) deciding upon the optimal maintenance and rehabilitation treatments for a given operating situation and iii) planning and programming of short term and long term maintenance budgets. The structural and functional condition data will form the basis for the development of pavement deterioration models. The particular distress type as well as its severity and extent help to know the degree of pavement damage. It is well established that the most versatile approach to predict pavement deterioration is to model the major modes for distress individually because different distress types need different maintenance treatments. These distress parameters are roughness, cracking area, rut depth and pothole etc. In the present study the deterioration models developed in India, by CRRI, IIT Roorkee and Bangalore University and the deterioration models built in Highway Development and Management Tools [HDM-4} have been compared and tested making use of standard time series data of National Highways and State Highways. On the basis of this comparative study suitability of each model type for roughness, cracking area, rut iii depth and pothole prediction has been established. Performance of HDM-4 seems to be superior in comparison to other models. The distress prediction was found out using the suitable pavement deterioration models for sample stretches of National Highway — 58 and rational maintenance strategies are suggested.