Implementation of AASHTOWare Pavement ME Design Software for pavement rehabilitation

Abstract

The 1993 version of the American Association of State Highway Transportation Officials (AASHTO) design guide has been the primary pavement design tool for state highway agencies in the United States. Recently, a mechanistic-empirical pavement design guide (MEPDG) has been developed for new and rehabilitated pavement design. MEPDG approaches have been incorporated into a proprietary design software (commonly known as AASHTOWare Pavement ME Design (PMED)) for new and rehabilitated pavement designs. The main objective of this study was to facilitate implementation of this AASHTOWare PMED software for rehabilitated pavement design in Kansas. As part of this implementation, transfer functions for translating mechanistic pavement responses into visible distresses embedded in the AASHTOWare PMED software were locally calibrated to eliminate bias and reduce standard error for rehabilitated pavements in Kansas. Rehabilitated pavement sections included asphalt concrete (AC) over AC and jointed plain concrete pavement (JPCP) sections. The PMED software requires periodic recalibration of the prediction models to account for improvements in the PMED models, changes in agency design and construction strategies, and updates in performance data. Thus, another objective of this study was to develop an automated technique for calibrating the AASHTOWare PMED software performance models. The automated methodology developed in this study incorporated robust sampling techniques to verify calibrated PMED models. In addition, a statistical equivalence testing approach was incorporated to ensure PMED-predicted performance results tend to agree with the in-situ data.