Development of Truck Loading Groups for the Mechanistic-Empirical Pavement Design Guide.

A key to the use of weigh-in-motion (WIM) traffic data for the Mechanistic-Empirical Pavement Design Guide (MEPDG) is to be able to successfully recognize the differences in loading patterns and to estimate the full axle-load spectrum data occurring under different conditions. However, how to identify these patterns on the basis of the large amount of WIM data remains a challenge. In this paper, WIM data collected in the state of Arkansas are analyzed by using cluster analysis methodologies to identify groups of WIM sites with similar traffic characteristics on the basis of the MEPDG-required traffic attributes. Case studies are presented and the cluster results are discussed. Combining the loading clusters, four long-term transportation planning factors currently adopted in Arkansas, including the modified Arkansas primary highway network (APHN) classification, demography, geography, and region attribute (rural or urban) of a highway under design, are adopted as the influencing criteria to develop the truck loading groups. The most significant influencing criteria are identified by using Fisher's exact test. Consequently, truck loading groups and their categorical logit models are developed in the paper. The developed method for determining truck loading groups will simplify the understanding and applicability of the traffic patterns and ultimately ease the preparation of the traffic load spectra inputs on the basis of WIM data for the MEPDG procedure. [ABSTRACT FROM AUTHOR]