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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
REPORT |
This report is an archived publication and may contain dated technical, contact, and link information |
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Publication Number: FHWA-HRT-13-090 Date: April 2016 |
Publication Number: FHWA-HRT-13-090 Date: April 2016 |
The Mechanistic-Empirical Pavement Design Guide (MEPDG) methodology was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A, and the MEPDG Manual of Practice was balloted affirmatively through the American Association of State Highway and Transportation Officials (AASHTO) in 2008 at the Joint Technical Committee on Pavements annual meeting.(3,1) Currently, many State highway agencies are evaluating and implementing the new pavement design procedures.
This report focuses on traffic inputs that support the MEPDG method. As a result, the abbreviation "MEPDG" is used extensively throughout this report. This abbreviation does not refer to a specific publication; rather, it is used to define parameters, models, and computational procedures that support the MEPDG method.
The MEPDG requires actual traffic inputs, rather than the number of 18-kip equivalent single-axle loads (ESALs) determined through the use of the AASHTO equivalency factors.(4) The MEPDG traffic inputs are normalized axle load spectra (NALS) for each truck class and axle group type, number of axles of each type per vehicle class, percentile truck class volume distribution, truck volume, and truck growth.
NALS are percentile distributions of axle counts by load level. Individual NALS are computed for each axle group type and truck class. The axle group types included in the MEPDG design procedure are single, tandem, tridem, and quad.(4) Truck classes are vehicle classes 4 through 13 based on the Federal Highway Administration (FHWA) vehicle classification scheme F-13. For the design, NALS representative of axle load distribution for a typical day of the month are used. For roads that do not show significant seasonal variations, the same NALS are used for all calendar months.
Out of all MEPDG traffic inputs, NALS are the most challenging to collect due to the high data collection costs, the time needed to collect an adequate quantity of data, and weigh-in-motion (WIM) equipment calibration and maintenance requirements. Therefore, the majority of pavement designs in accordance with the MEPDG rely on regional, agency-wide, or national NALS traffic loading defaults. It is important that default NALS values are as representative of the actual truck loading along the project site as possible.
The default traffic datasets included in the MEPDG were developed during NCHRP Project 1-37A and based on Long-Term Pavement Performance (LTPP) traffic data collected by State highway agencies prior to 1999.(3) At that time, these data represented the best available and most comprehensive national set of WIM and automatic vehicle classification (AVC) data. However, some concerns existed regarding the lack of documented quality of the data that were used to determine the truck traffic default values-specifically, the NALS values for each axle group type within a truck class. More importantly, many agency personnel have also questioned the quality of their own truck traffic data.
Since 1999, the LTPP Specific Pavement Study (SPS) Traffic Data Collection transportation pooled fund (TPF) study, TPF-5(004) (SPS TPF study) has generated high-quality traffic loading information for 26 LTPP SPS TPF WIM sites.(2) These data were collected using uniform protocols for data quality assurance (QA) and in accordance with the LTPP vehicle classification scheme. These new data provide an opportunity to evaluate the applicability of the MEPDG NALS defaults and to provide alternate NALS.
The primary purpose of this project was to revise axle loading defaults based on data from SPS TPF WIM sites, compare new defaults with the existing MEPDG global NALS defaults, and provide recommendations for use of the new axle loading defaults. This research project addresses the following specific objectives:
The following are the outcomes and deliverables of this study:
This report consists of two parts. Part I (chapters 1 through 7) focuses on a review of the MEPDG traffic loading data requirements, data assessment, and development of data selection criteria. Part II (chapters 8 through 11) focuses on the development of alternate MEPDG traffic loading defaults and recommendations for use of those alternate defaults.