Verification, Refinement, and Applicability of LTPP Classification Scheme

Pavement analyses depend upon accurate and consistent load data derived from traffic data. To meet this need, the Long-Term Pavement Performance (LTPP) program requested that all the states submit data according to the Federal Highway Administration (FHWA) 13-category vehicle classification scheme. The practical reality, however, is that the FHWA 13-category vehicle classification scheme is a visual description and the algorithms used to satisfy these criteria vary considerably from state-to-state and vendor-to-vendor. The Transportation Research Board (TRB) Expert Traffic Group (ETG) on LTPP Traffic Data Collection and Analysis (or Traffic ETG) identified the inconsistencies in the classification data as problematic. Therefore, under the LTPP Specific Pavement Study (SPS) Traffic Data Collection Pooled-Fund Study, TPF-5(004), the Traffic ETG developed a prototype classification scheme to be used in an effort to bring uniformity to the SPS traffic data collection. It was developed based on three states' experience. Work is needed to verify the applicability of the LTPP Classification Scheme to the wide variety of traffic data collection locations and diversity of vehicles encountered across the Nation. The appropriateness of the application of the LTPP Classification Scheme needs to be done while the SPS data collection is still underway. This is very important research because binned class data cannot be re-processed into different results. Implementing this National class scheme forms a basis for better data sharing among states. A better understanding of the classification scheme variability will allow pavement designers to account for this in their use of the data. Improved vehicle classification will result in better roadway designs as many states are using classification data in lieu of weight data at many locations. The Mechanistic-Empirical Pavement Design Guide depends upon accurate vehicle classification data. Studies that use traffic data will be impacted by these findings.