EFFECT OF VARIOUS PARAMETERS ON PERFORMANCE OF PMGSY ROADS

Abstract

Pavement deterioration models, which simulate the deterioration process of pavement conditions and provide forecasting of pavement condition over time, play a pivotal role in pavement management systems. Good pavement management systems require the collection of substantial amounts of road conditions data over time, to assist in the development of pavement deterioration models. Pavement management system also required proper methodology to decide the priority after evaluating the road condition of a network. So maintenance management model is required to combine the individual pavement condition indicator. To develop pavement deterioration model, deflection and roughness measurements were carried out on 18 sections of PMGSY roads of Uttarakhand and Uttar Pradesh states. Out of these 18 sections, on 17 sections data was collected last year also. Using these last two years data set of pavement performance indicator, pavement deterioration models are developed. Regression analysis and Artificial Neural Network (ANN) were used to develop the models. Best model was chosen based on the coefficient of multiple determination R2 and residual sum of squares (SSE). Paried t-test is carried out for the validation purpose of chosen best models. These models can predict the deflection and roughness value of a road at a given data of pavement age, CBR of subgrade, traffic and Pavement thickness. Maintenance Priority Index was also developed using three parameters named as deflection, roughness and traffic to decide the priority of road for maintenance work.