Pavement Rutting Prediction Model based on the Long Term Pavement Performance Data

doi:10.3850/978-981-08-7920-4_S4-P04-cd

Pavement Rutting Prediction Model based on the Long Term Pavement Performance Data

Asmaiel Kodan Naiel and Mumtaz A. Usmen

Department of Civil and Environmental Engineering, Wayne State University, Detroit, Michigan, USA.

ABSTRACT

Various types of pavement deterioration can affect pavement performance, including rutting, which causes safety and service quality problems on the highways. Rutting, often referred to as permanent deformation of a pavement surface, causes longitudinal depressions creating channels in wheel paths. There are many in-service pavement performance databases, but the Long Term Pavement Performance database (LTTP) is the largest of its kind in the world. It encompasses data from four different climate zones in North America. Data on flexible pavements fromonly the dry freeze zone was included in the scope of the study reported herein. Regression analysis was performed to develop a rutting model. The proposed model indicates that the voids in the mineral aggregate (VMA) of hot mixed asphalt is the most important factor and the positive values of the regression coefficient of VMA implies that rut depth increases whenVMAincreases. The other important factors in thismodel areMarshall stiffness and freeze index. The negative values of the regression coefficients of Marshall stiffness and freeze index indicates that the rut depth will decrease when the Marshall stiffness and freeze index increase.

Keywords: Flexible pavement, Pavement deterioration, Pavement performance, Pavement rutting, Empirical model, The Long Term Pavement Performance (LTTP) database.

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