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SUMMARY In 2008, AASHTO published the Mechanistic-Empirical Pavement Design Guide: A Manual of Practice (MEPDG) and released the first version of the accompanying software program AASHTOWare Pavement ME Design⢠(formerly DARWin-ME) in 2011. The MEPDG and accompanying software are based on mechanistic-empirical (ME) principles and, as such, are a significant departure from the previous empirically based AASHTO pavement design procedures. Moving from previous empirically based to ME-based design procedures provides a number of advantages, including the evaluation of a broader range of vehicle loadings, material properties, and climatic effects; improved characterization of the existing pavement layers; and improved reliability of pavement performance predictions. However, implementation of the MEPDG may require a significant increase in the required time to conduct a pavement design, in the needed data (e.g., traffic, materials, and calibration and verification to local conditions), and in the knowledge and experience of the personnel conducting the pavement design or analysis. The objective of this synthesis is to document the strategies and lessons learned from highway agencies in the implementation of the MEPDG (and accompanying AASHTOWare Pavement ME Design⢠software), as well as the reasons why some agencies have not or may not proceed with implementation. This synthesis is intended to aid in the facilitation and enhancement of the MEPDG and AASHTOWare Pavement ME Design⢠implementation process through the demonstration of procedures and practices of highway agencies that have successfully implemented this pavement design procedure. This synthesis is based on the results of a literature review of agency MEPDG implementa- tion efforts, a survey of highway transportation agencies (U.S. state highway agencies, Puerto Rico, and the District of Columbia, and Canadian provincial and territorial governments), and follow-up questions with agencies that have implemented the MEPDG. In total, 57 agencies [48 U.S. (92%) and nine Canadian (69%) highway transportation agencies] provided responses to the agency survey. For this synthesis, implementation is defined as the MEPDG and AASHTOWare Pavement ME Design⢠being used to design or evaluate pavement structures, either for a limited number of pavement sections (e.g., interstate only), for a specific pavement type (e.g., asphalt or concrete), or for a specific pavement treatment (i.e., new, reconstructed, and rehabilitated), or for all pave- ment designs on the state highway network. Of the 57 agencies that responded to the survey, three indicated that they have fully implemented the MEPDG, forty-six are in the process of implementing, and eight indicated that they have no plans at this time for implementing the MEPDG. The majority of the agencies indicated that the MEPDG will be used for the design and analysis of new or reconstructed asphalt pavements and jointed plain concrete pavements (JPCP). Most agencies reported that the MEPDG will be used for the design and analysis of asphalt overlays of existing asphalt pavements, existing concrete pavements, and fractured concrete pavements. For concrete overlays, most agencies indicated that the MEPDG will be used for the design and analysis IMpleMentAtIon of the AAShto Mechanistic-eMpirical paveMent Design guiDe And SoftwARe
2 of unbonded JPCP overlays of existing JPCP, JPCP overlays of existing asphalt pavements, and bonded concrete overlays of existing JPCP. In relation to MEPDG input values, agencies responded that, for the most part, the MEPDG default or agency-determined regional values are being used to characterize traffic and materials inputs (excluding truck volume and vehicle class distribution, which is pre- dominately based on site-specific input values). In addition, 12 agencies indicated that the applicable MEPDG performance prediction models have been calibrated to local conditions. A number of implementation aids were common among the agencies that have or will implement the MEPDG within the next 3 years (2013â2015). For example, 27 of the 32 responding agencies indicated having a MEPDG champion and 18 of 32 agencies indi- cated having an established MEPDG oversight committee. When asked about activities that would aid the implementation effort, the majority of agencies indicated the need for assistance in the local calibration of the MEPDG performance prediction models and training in the use of the AASHTOWare Pavement ME Design⢠soft- ware. Additional suggestions included developing a dedicated MEPDG website for sharing technical information, training in the interpretation of MEPDG results, training in methods for obtaining inputs, training in ME principles, and training in how to modify pavement sections to meet design criteria. The results of the literature review indicated that a number of common elements were included in agency implementation plans, including identification of the pavement types to include in the implementation process, determining the data need requirements, defining materials and traffic input libraries, establishing threshold limits and reliability levels for each pavement performance prediction model, verifying the predicted pavement performance, updating agency documents to include analyzing pavement structures with the MEPDG, and providing training to agency staff on ME principles, MEPDG, and AASHTOWare Pavement ME Designâ¢. Three agency case examples were developed covering the implementation efforts of the departments of transportation of Indiana, Missouri, and Oregon. As part of the agency sur- vey, these three agencies reported that the MEPDG had been implemented in their respective states. The agency case examples were developed using information provided by each agency in the agency survey, supplemented with follow-up questions and a review of agency-provided documents.
