Facilitating Analysts’ Use of Traffic Data from the Long-Term Pavement Performance (LTPP) Program

This study was designed to improve the experience of users of Long-Term Pavement Performance (LTPP) data by enhancing the traffic data included in the LTPP database and making it easier for researchers to find and select the traffic data they need for their specific analyses.

A key outcome of the Federal Highway Administration’s LTPP program is the delivery of a comprehensive, easily used database that supports a wide range of pavement performance research and analyses. Using LTPP data, researchers can develop knowledge, relationships, and models to improve pavement design and complete more reliable performance predictions. However, in the past, when researchers wanted to obtain and use these traffic data in their analyses, they were intimidated by the size of the dataset, the variety of data sources and data collection methods, and the different parameters used to characterize traffic data at LTPP sites.

This study was designed to help LTPP database users better navigate and understand LTPP traffic data and then select the traffic parameters that best fit their project needs. This was accomplished by developing analysis-ready traffic parameters that can support the pavement analysis objectives listed in the Strategic Plan for LTPP Data Analysis, including analyses using the AASHTOWare Pavement ME Design software.

The researchers developed a methodology for computing the required analysis-ready traffic parameters that FHWA selected for this study. They also developed and applied a methodology for assessing the reasonableness and reliability of axle loading estimates that states have supplied to cover time periods that pre-date the routine collection of truck volume and weight information on roadway sections in the LTPP study. LTPP researchers must rely on these state-supplied historical estimates when insufficient traffic data have been collected at those sites.

To help database users select the best LTPP test locations and traffic data for their analyses, the researchers also developed special indicators that explain the nature and applicability of the computed traffic parameters. These indicators are available for each LTPP site and computed traffic parameter. The indicators were developed on the basis of the quality of data used to compute the parameter, and they reflect how well these data represent traffic conditions at LTPP sites.

The forthcoming User Guide for Selecting and Using Long-Term Pavement Performance Traffic Data, which aims to help LTPP database users better navigate and understand LTPP traffic data and parameters, is a product of this study. The Guide walks pavement researchers through the selection of the most appropriate traffic statistics for their pavement analyses, as well as the extraction of data from LTPP computed parameter tables using InfoPave™.

Report FHWA-HRT-22-074

Olga I. Selezneva, Applied Research Associates
Mark E. Hallenbeck, Washington State Transportation Center-UW

Sponsor: FHWA