PERFORMANCE STUDY OF PMGSY ROADS

Abstract

The Government of India launched the Pradhan Mantri Gram Sadak Yojana (PMGSY) to give connectivity to rural roads. Huge investment has been made on rural connectivity, large kilometers of roads constructed in recent years under these programme. Majority of these roads are provided with flexible pavements. Flexible pavements are affected by load of moving vehicle, climate and other environmental factors. Limited funds have been preventing the authorities from performing periodic maintenance and the rural road network in the country is deteriorating at faster rate. Deterioration models are helpful in identifying the future improvement needs of a road and to carry at economic analysis of various alternatives available for improvement. To study the performance and to determine the rate of deterioration, 17 sections in the states of Uttarakhand and Uttar Pradesh with varying conditions of the subgrade soil, pavement materials, traffic, terrain, and environment were selected. The data have been collected for deflection by using Benkelman beam, roughness by Merlin. The deterioration prediction models for deflection and roughness are developed using artificial neural networks (ANN) and linear regression. The independent variables used in developing these models are age of the pavement, traffic, CBR, and thickness of pavement. Pavement Serviceability Rating (PSR) and Riding Comfort Index (RCI) are given based on visual inspection of test sections. From the study results it is found that the performance of most of the sections is good from structural consideration, but poor from functional point of view. Comparison has been made between the ANN model and regression model. It is found that ANN models give better prediction than of regression models.