Implementation of the AASHTO Mechanistic-Empirical Pavement Design Guide and Software (2014)

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26 INTRODUCTION As noted in chapter three, the majority of highway agencies currently design their highway pavements in accordance with the AASHTO 1993 Guide, which is primarily based on empiri- cal relationships derived from the AASHO Road Test. As such, the performance prediction relationships are representative of the design present at the Road Test. However, since that time (1958 to 1960), significant changes have occurred in pavement cross sections, advances in material characterization, changes in vehicle truck type, and increased volume and weight distri- bution of traffic making the empirical-based design process limiting. At the same time, highway agencies are familiar with the AASHTO 1993 Guide and, for the most part, it has served the pavement design community well. The development of the MEPDG raises issues and chal- lenges related to implementation. These include, but are not limited to, material and traffic characterization, incorporation of climatic effects, verification of predicted performance, evaluation and acceptance of a new method, justification of benefits over the current process, staffing requirements, budget needs, and training. COMMON ELEMENTS Based on the survey of agencies, approximately 43 agencies indicated that they are in the process of evaluating the MEPDG. However, 15 agencies have progressed further into the imple- mentation process, such that implementation is anticipated to occur within the next 2 years. Additional review of the agency implementation practices may provide valuable insight into the features (or elements) of the MEPDG implementation process. The literature review indicated that a number of agencies have developed implementation plans, materials and traffic libraries, agency-specific user input guides, and train- ing programs. Determining which elements to include in the implementation plan is based on the approach that best meets the individual agency needs. The following summarizes the literature review of common elements of agency implemen- tation plans. Pavement Types This implementation element identifies the pavement types that will be analyzed or designed using the MEPDG (Coree et al. 2005). Pavement types may include new, reconstructed, and rehabilitated asphalt and concrete pavements. In addition, agencies may also define pavement types according to func- tional classes (e.g., interstate pavements only). An agency’s decision may be based on agency policy, practice, or criticality of the roadway (e.g., interstate versus farm-to-market). Initially, applying the implementation effort for new construction is an approach used by several agencies (Mallela et al. 2009; Timm et al. 2010). Then, as familiarity, knowledge, and data become available, extending implementation to other pave- ment types is commonly conducted. Data Needs and Required Information There are a large number of inputs needed to conduct an MEPDG analysis. Evaluation of input needs not only outlines and identifies the various sources of available data, but also is used to identify where additional testing may be required to obtain missing data. The following provides a summary of needed data and related information. • Hierarchical level—Data availability, practices and procedures, time required to collect needed data, bud- get constraints, required resources, and agency policy (Coree et al. 2005; Hoerner et al. 2007). • Climate data—Stations with preferably 20 years of con- tinuous data; consider identifying a generic station for use in the calibration process and add additional sites as needed (Coree et al. 2005). • Material and traffic input values—Typical values based on MEPDG default values, existing conditions, labora- tory and field testing, construction specifications, and testing equipment needs (Coree et al. 2005; Hoerner et al. 2007; Schwartz 2007). • To ease the implementation effort, the development of an input library (database) that can be accessed within the AASHTOWare Pavement ME Design™ software will not only reduce the amount of required data entry but will also reduce the potential of data error and/or utilization of incorrect parameters (Coree et al. 2005; Schwartz 2007; Mallela et al. 2009; Timm et al. 2010). The agency-specific materials and traffic input libraries allow for collecting, organizing, and arranging data utilized in the AASHTOWare Pavement ME Design™ software (AASHTO 2013). • Testing program—Type of tests and the number of test samples needed to obtain missing or needed data (Hoerner et al. 2007; Schwartz 2007). chapter four COMMON ELEMENTS OF AGENCY IMPLEMENTATION PLANS

27 • Pavement performance—Adequacy of pavement man- agement system data and other data (e.g., LTPP) to support local calibration (Schwartz 2007). • Calibration test sites—Number of pavement segments by pavement type, functional class, distress type, traffic volumes, and climatic regions (Coree et al. 2005; Hoerner et al. 2007; Schwartz 2007; Mallela et al. 2009; Bayomy et al. 2010; Bayomy et al. 2012). Performance Prediction Models, Threshold Limits, and Reliability Determine performance criteria and reliability level for each distress indicator and IRI. It is up to the agency to determine what constitutes an acceptable design based on the level of accepted distress (Coree et al. 2005; Hoerner et al. 2007; Schwartz 2007). MEPDG Verification An MEPDG analysis is conducted to verify that the design results meet agency expectations (AASHTO 2010). Verifica- tion is conducted using agency-identified performance cri- teria and reliability levels, material inputs, and traffic inputs for a standard agency pavement design(s) (AASHTO 2010). One or more climate regions and truck traffic volume levels are typically analyzed as part of this effort (AASHTO 2010). The MEPDG predicted conditions are compared with the agency-measured distress. If the predicted condition reason- ably (agency determined) matches the measured distress, then the MEPDG default calibration coefficients can be adopted; if not, local calibration is highly recommended (Coree et al. 2005; Hoerner et al. 2007; AASHTO 2010). Local Calibration Local calibration of the performance prediction models was summarized in chapter two of this synthesis and the reader is referred to the Local Calibration Guide (AASHTO 2010) for specific details. Selection of a statistically significant number of highway sections for each distress type, and use of LTPP sites is encouraged (Coree et al. 2005; Schwartz 2007; Mallela et al. 2009; Timm et al. 2010). Calibration Database As new materials, new design features, modifications to construction specifications, and additional performance data become available the development of a calibration database may be warranted (Hoerner et al. 2007). The calibration data- base can be updated as necessary and utilized in the future calibration efforts. Not only will this provide consistency from one calibration effort to the next, it will also make the calibra- tion process less burdensome (Hoerner et al. 2007). The cali- bration database contains pertinent information related to the calibration process, such as project information (design proper- ties, location) traffic data, climate station information (station location or list of stations used to create a virtual weather sta- tion), material properties, falling weight deflectometer (FWD) data (if applicable), pavement design, and pavement perfor- mance data (Hoerner et al. 2007; Pierce et al. 2011). Local Calibration Validation Once the local calibration coefficients have been determined, validation of the resulting models using different locations and design features is recommended (AASHTO 2010). Concurrent Designs The ability to compare the results of previous design pro- cedures with the MEPDG may facilitate the implementa- tion process. Concurrent designs can help to familiarize and improve the staff confidence in the MEPDG design results (Timm et al. 2010). Documentation Documentation may include an agency-specific pavement design manual and users guide that includes (Coree et al. 2005; Hoerner et al. 2007; Schwartz 2007): • Descriptions of the analysis and input value details, • Identification of the process for accessing material and traffic libraries, • Details on how to modify a pavement structure to meet performance criteria, • Calibration and validation procedures, • A definition of how to incorporate future enhancements, and • A catalog design for use by local agencies. Training A training program may be developed in-house or through universities, consultants, and national programs (e.g., National Highway Institute) in relation to ME procedures, MEPDG- specific analysis, AASHTOWare Pavement ME Design™ functionality and operation, and analysis of results (Coree et al. 2005; Hoerner et al. 2007; Schwartz 2007; and Timm et al. 2010). In addition, agencies have found it beneficial to have an MEPDG champion and an MEPDG oversight committee (Coree et al. 2005; Hoerner et al. 2007; MIDOT 2012). The MEPDG oversight committee can assist with decision making, more efficiently utilize existing personnel and resources, and expand the coordination and data acquisition process across agency divisions and offices. The MEPDG committee may include representatives from roadway design, construction, planning (traffic), materials (asphalt, concrete, aggregates, and

28 soils), roadway maintenance, pavement testing and evalua- tion, pavement design, pavement management, research, and industry. Example tasks of the MEPDG oversight committee may include (MIDOT 2012): • Facilitating change from current pavement design pro- cedure to the MEPDG. • Making decisions on equipment and personnel (e.g., pur- chasing equipment and hiring agency personnel versus contracting with universities and consultants). • Facilitating testing needs. • Establishing acceptable performance criteria and reli- ability levels. • Finalizing the level of input and input values. • Reviewing design results to learn the impacts of different inputs. • Developing and facilitating training, including manuals and documents. • Exploring research needs and developing research ideas and proposals. • Facilitating industry participation and addressing their requests and concerns.