Development of Prediction Model for IRI Utilizing Traditional Regression Analysis and Artificial Neural Network

Distresses occur in flexible pavements in various forms. As the age of the flexible pavement increases, the chances for occurrence of distress increase. In general, distresses occur in the pavement due to various factors. Structure, climate, traffic, performance are few of those factors which lead to distresses. In this paper, few factors were selected and related to the performance of International Roughness Index (IRI). Roughness of the roads can cause inconvenience to the people riding or driving a vehicle and it can also delay the journey time. So, study on how to overcome these issues and the main factors causing this distress is important. In this study, six various factors were chosen for the analysis of predicting a model for IRI using regression analysis and Artificial Neural Network.