Statistical Distributions of Pavement Damage Associated with Overweight Vehicles: Methodology and Case Study

Abstract

The trucking industry is the primary mode of transporting for goods and commodities in the United States. Currently, there is an increasing trend in the use of overweight (OW) vehicles on the highway network. State highway agencies (SHAs) are challenged to address this increase, particularly relative to associated pavement damage. In this study, a probabilistic method was developed to evaluate rutting and fatigue cracking damage caused by OW vehicles under different road and environmental conditions. The influential input parameters in this analysis included gross vehicle weight (GVW), axle configuration, axle weight, pavement temperature, and vehicle-miles traveled (VMT). Necessary information was obtained by analyzing more than 170,000 entries of a Nevada Department of Transportation (NDOT) OW permit database. The developed model was based on mechanistic-empirical (ME) approach and considered asphalt concrete (AC) viscoelastic characterization. The results of this study were distributions of AC critical responses, load equivalency factors (LEFs), and relative damage factors (RDFs). The analysis showed that load equivalent factor (LEF) distributions could be incorporated in pavement design methods to account for OW vehicles. Furthermore, the damage induced by specific OW vehicles could be assessed using the relative damage factor (RDF) concept and may be efficiently used by SHAs during the permit application process. A case study was presented illustrating the impact of an OW axle configuration on pavement damage. Finally, a method was suggested for developing RDF tables with damage ranges corresponding to different axle configurations and the GVW that could be a tool for SHAs to evaluate and understand pavement damage induced by OW vehicles.