Research Article Transportation Research Record 1–10 Ó National Academy of Sciences: Transportation Research Board 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0361198119835540 journals.sagepub.com/home/trr Implementation of AASHTOWare Pavement ME Design Software for Asphalt Pavements in Kansas Shuvo Islam 1 , Mustaque Hossain 1 , Christopher A. Jones 1 , Avishek Bose 2 , Ryan Barrett 3 , and Nat Velasquez, Jr. 3 Abstract Many highway agencies are transitioning from the 1993 AASHTO pavement design guide to the AASHTOWare Pavement ME Design (PMED). Pavement performance models embedded in the PMED software need to be calibratedfor new and recon- structed hot-mix asphalt (HMA) pavements. Twenty-seven newly constructed HMA pavements were used to calibrate the prediction models—twenty-one for calibration and six for validation. Local calibration for permanent deformation, top-down fatigue cracking, and the International Roughness Index (IRI) models was done using the traditional split-sample method. Comparison with the results from the 1993 AASHTO design guide for ten new HMA pavement sections with varying traffic levels was done. The results show that the thicknesses obtained from locally calibrated PMED are within 1 inch of the AASHTO 1993 design guide prediction for low to medium-low traffic. For sections with high traffic level, the 1993 AASHTO design guide yielded higher thickness than PMED. The PMED implementation strategies adopted in Kansas and relevant con- cerns are discussed. Finally, an automated calibration technique has been proposed to help highway agencies to perform peri- odic in-house calibration of the performance models. US state highway agencies have predominantly been using the American Association of State Highway Transportation Officials (AASHTO) Guide for Design of Pavement Structures (1993 version) and the associated DARWin software to design highway pavements. Many agencies, including the Kansas Department of Transportation (KDOT), are planning to adopt the recently developed mechanistic-empirical pavement design guide (MEPDG) for new and reconstructed flex- ible pavements. The MEPDG design approach has been incorporated in proprietary pavement design software, commonly known as AASHTOWare Pavement ME Design (PMED). Version 2.5 is the latest version of the AASHTOWare series. After the release of MEPDG several states have attempted implementation of the software for routine pavement design. NCHRP synthesis 457 conducted a sur- vey in 2014 among fifty-seven highway transportation agencies across North America and reported that three agencies had implemented MEPDG approaches and forty-six agencies were evaluating MEPDG models (1). The technical report of the AASHTO Pavement ME national user group in 2017 stated that nine highway agencies (out of twenty-one responding) have successfully implemented PMED software for asphalt pavements (2). The report also listed several challenges faced by the state highway agencies in implementing the PMED software. Local calibration and verification of PMED performance models topped the list. Other challenges include availabil- ity of performance data, characterizing bound and unbound layer material properties, compatibility of per- formance measures and threshold criteria, and so forth. One of the prerequisites of implementing the PMED software for routine design is to calibrate and validate the performance models to local conditions (3). In addi- tion, truck-traffic characterization, developing a material inputs database, and establishing performance criteria and distress-wise reliability levels are also required (4). Nantung et al. proposed a six-step MEPDG imple- mentation plan for the Indiana Department of Transportation (5). These steps include reviewing 1 Department of Civil Engineering, Kansas State University, Manhattan, KS 2 Department of Computer Science, Kansas State University, Manhattan, KS 3 Bureau of Road Design, Kansas Department of Transportation, Topeka, KS Corresponding Author: Address correspondence to Shuvo Islam: sislam@ksu.edu