The measurement and prediction of pavement performance is a critical element of any pavement management system (pms). Pavement condition rating (pcr), a composite statistic derived from functional andstructural conditions, is used as a measure of serviceability. After a review of the various types of prediction models, the authors concluded that an empirical-mechanistic model is best suited, with a systematic database that includes the structural information, trafficvolume, and condition data for each "homogeneous" section of the road. Pavements with an asphalt concrete surface are grouped into three categories (pavements with no overlay, pavements with overlay, andcomposite pavements), and prediction equations are developed for each of them. The equations are validated by comparing them with several existing models, both empirically and mechanistically based. In all three prediction models, age is by far the most significant predictor of serviceability. The traffic volume and weight expressed in terms of equivalent single-axle loads (esals) and the structural makeup of the pavement described by the composite structural number playonly a secondary role in forecasting performance of pavements. Thispaper appears in transportation research record no. 1215, Pavement management and rehabilitation.
Abstract