Roughness Progression Model for Asphalt Pavements Using Long-Term Pavement Performance Data

Abstract

A reliable pavement performance prediction model is needed for road infrastructure asset management systems or pavement management systems. In this study, the data on roughness progression of asphalt pavements in the long-term pavement performance (LTPP) database was analyzed in order to develop such a model. The international roughness index (IRI) is a reasonable measure of the ride comfort perceived by occupants of passenger cars and hence used as the basis for the pavement performance prediction model developed in this research. A quantitative relationship between roughness progression and accumulative traffic load, structural number, annual precipitation, and freezing index was developed and validated. Five pavement performance levels were developed to express the extent of asphalt pavement deterioration. This is coupled with a reliability analysis based on the Weibull model to estimate the remaining service life of asphalt pavements. Effective treatments of pavements at the project level for each condition state level were also proposed, which can aid network level optimization of the overall condition and corresponding budget allocations.