Prediction of Pavement Remaining Service Life Using Roughness Data—Case Study in Dubai

This paper presents a methodology for predicting Pavement Remaining Service Life (RSL) using roughness data in terms of the International Roughness Index (IRI). The serviceability, roughness and age data pertaining to more than 400 sections of asphalt-surfaced pavements in Dubai Emirate, U.A.E. were collected and analysed. Models for estimating the Present Serviceability Index (PSI) based on direct roughness measurements were developed and compared with the results of similar international studies. Separate regression models for both heavily trafficked lane (slow lane) and fast traffic lane are presented. The developed roughness—serviceability and roughness—age models were found statistically significant and predictable. A reliable time approach for estimating the RSL for both lanes based on the current age of the pavement has been used. The developed RSL models were found very helpful in facilitating the decision making regarding maintenance, rehabilitation and the efficient use of the allocated maintenance budget.