Developing International Roughness Index (IRI) Model from visible pavement distresses

Abstract

The pavement maintenance, rehabilitation, and design methodologies need an appropriate evaluation of the pavement functional condition. The roughness is generally recognized as a measure of the pavement functional capacity. The roughness of pavement is measured using IRI, which depends on the quantity of distresses existing on the pavement surface. This study focuses on developing a model to predict the roughness (IRI) from the flexible pavement distresses. Accordingly, 83 flexible pavement sections were selected in AL-Diwaniyah city roadways, Iraq. The length of the section is equal to 250 meters. Distress data were collected manually, in terms of amount and severity. The IRI data were collected from all sections using the Dynatest Road Surface Profiler (RSP) test system. Using SPSS software, a stepwise multiple linear regression has been used to develop the model between the IRI and visible pavement distresses depending on the data collected. The resulting equation was found among the IRI and percentages of polished aggregate, high and medium severity potholes, medium severity alligator cracking, medium severity patching, high severity raveling, and high severity corrugation. The results indicate that this model is strong enough for the prediction of the International Roughness Index.