Development of a Pavement Rutting Model from Long-Term Pavement Performance Data

Rutting is one of the most important types of load-associated distresses that develop on flexible pavements. Extensive research has been conducted on the development of empirical models to predict pavement rutting progression using different data sources. However, the rutting data in the Long-Term Pavement Performance (LTPP) database has rarely been used to develop empirical rutting models. This paper uses the rutting data collected on LTPP sections in the State of Texas to statistically estimate the relationship of rut depth and explanatory variables representing pavement structure, materials, traffic loading and climate. All data used in this paper are extracted from different modules of the LTPP database. The proposed model demonstrates a concave trend of the rut depth with respect to the load repetition that is a common finding in most empirical rutting models. All climate parameters in this model show significant effects on the rutting progression. The structural number is statistically significant and has a negative estimated parameter, which indicates that a stronger pavement has smaller rutting depth.