assessment of maintenance strategies and performance prediction for urban roads using iri and hdm-4 models

Globally emerging markets need a well distributed, safe, and efficient transportation system. analyzing, pavement management and maintaining such a dense highway networks and transportation systems comes with its own complications. out of the many available techniques globally i.e. highway development and management (hdm-4) can be adopted to achieve such a daunting task. in hdm-4, pavement distress initiation and progression can be predicted using hdm-4 pavement deterioration models using different parameters like traffic, climate, pavement structure, and composition combinations. however, before implementation, such hdm-4 model should be calibrated and validated. since, in-situ variables greatly influence the rate at which each pavement distress initiates and propagates. the paper focuses on distress factors i.e. rutting, fatigue, pothole, and patching on a highway of two and four-lanes using hdm-4 model. international roughness index (iri) values are computed using merlin instrument. the results are given as input to hdm-4 software for the predicting initiation and progression of discomfort for the present and future traffic. based on the iri values, priority ranking are given for road maintenance, higher the iri value, higher is the priority for road maintenance and vice-versa. findings from this study can be used to improve road networks, traffic safety, and applicability for comparable road conditions.