Use of Pavement Management Data for Calibration of the Mechanistic-Empirical Pavement Design Guide

Implementation of the Mechanistic-Empirical Pavement Design Guide (MEPDG) is expected to improve the efficiency of pavement designs and enhance the abilities of highway agencies to predict pavement performance, which will thereby improve their ability to assess maintenance and rehabilitation needs over the life of the pavement structure. Before the MEPDG can be fully implemented, verification and if necessary, calibration using actual pavement design input and response data to ensure its validity and accuracy to local conditions is needed. The MEPDG has been nationally calibrated using data contained within the Long-Term Pavement Program (LTPP) database. Although the LTPP database represents a valuable resource, the enormous variability between the states in terms of geography, climatic conditions, construction materials, construction practices, traffic compositions and volumes, and numerous other pavement design variables make it desirable to calibrate the MEPDG at the local level using local field performance data. Collection of data needed to support the local calibration effort is expensive, time consuming, and resource intensive, but significant savings could be realized by highway agencies if existing pavement management system data could be used for MEPDG performance prediction model calibration. This paper will discuss the development of a framework for using existing pavement management data to calibrate the MEPDG performance models. The framework identifies the data collection and storage requirements for using data contained within a highway agencies pavement management system. The feasibility of the framework will be demonstrated using actual data from a highway agencies pavement management system.