LAUSR

ABSTRACT India’s road network carries over 90% of passenger traffic and over 65% of its freight movement. Therefore, effective maintenance of road networks is to be accorded the highest importance. Assigning priorities to the roads that require immediate repair or maintenance is another vital task. The present study aims to develop a novel method to prioritise the pavement maintenance sections by deploying the functional characteristics of the pavement alone. In order to do this, the relationship between functional and structural characteristics of the pavements is explored with the aid of the computing system, -Artificial Neural Network (ANN). This technique enables pavement maintainers and managers to considerably reduce the frequency of expensive, time-consuming and traffic disruptive tests for obtaining the structural characteristics of pavements. A vast database, comprising of the properties of fourteen rural roads from seven districts of Tamil Nadu, with different traffic characteristics, subgrade soil characteristics, and climatic conditions, is systematically analyzed to achieve the research objective. The numerical outcomes are a testament to evidence the correlation between the structural and functional characteristics of the pavements. The formulated Maintenance Priority Index (MPI) will be beneficial in ranking the Maintenance and Rehabilitation actions based on the urgency level.