Theses and Dissertations Collection

ABSTRACT

The performance prediction models incorporated in the AASHTOWare Pavement ME Design software (PMED) were calibrated using data primarily obtained from the Long-Term Pavement Performance (LTPP) program database. Therefore, the globally-calibrated models should be evaluated to determine whether they accurately predict field performance for Idaho local conditions. Otherwise, some pavements will be overdesigned and others under designed, turning to either excessive costs or premature failure. This study aims to evaluate and improve the accuracy of the PMED asphalt and rigid pavement performance models for Idaho local conditions. A total of 34 flexible pavement and 39 rigid pavement sites were selected for conducting the local calibration effort. These sites represent different climate zones, traffic levels, pavement structures, and materials across Idaho. The required PMED inputs and the historical performance data for the selected sites were extracted from a variety of sources including project construction data, material testing records, Idaho Transportation Department (ITD) Transportation Asset Management System (TAMS). Each of the selected pavement sites were evaluated using PMED v2.5.3, and the predicted performance results were compared to field conditions. The results showed a significant statistical difference between the performance prediction and field observation. Therefore, to improve the accuracy of the software prediction with less bias and error, the PMED models were recalibrated and local calibration coefficients were determined for both flexible and rigid performance models.