Analysis Of Virginia Specific Traffic Data Inputs For Use With The Mechanistic Empirical Pavement Design Guide

This study developed traffic inputs for use with the Guide for the Mechanistic-Empirical Design of New & Rehabilitated Pavement Structures (MEPDG) in Virginia and sought to determine if the predicted distresses showed differences between site-specific and default traffic inputs for flexible and rigid pavements. The axle-load spectra, monthly adjustment factors, vehicle class distribution factors, and number of axles per truck inputs were considered. The predicted distresses based on site-specific traffic inputs from eight interstate and seven primary route weigh-in-motion sites in Virginia were compared to predicted distresses using MEPDG default traffic inputs. These comparisons were performed by use of a normalized difference statistic for each site-specific traffic input and the coefficient of variation for each pavement distress model. In addition, the practical significance for flexible pavements was considered from the difference in the predicted time to failure between site-specific and default traffic inputs. The analysis showed that the effect of the site-specific traffic inputs was generally not statistically significant when the uncertainty of the distress models was considered. However, the site-specific axle-load spectra and vehicle class distribution inputs showed a statistically significant effect on certain predicted distresses for flexible and rigid pavements, respectively. The study recommends that site-specific axle-load spectra data be considered for analysis of flexible pavements. Alternatively, summary (statewide average) axle-load spectra data for analysis of interstate and primary flexible pavements should be considered preferentially over default axle-load spectra. Site-specific vehicle class distribution factors should be considered for analysis of rigid pavements on the interstate system. Alternatively, summary (statewide average) vehicle class distribution factors for analysis of interstate rigid pavements should be considered preferentially over default vehicle class distribution data. Default traffic data are recommended for analysis of primary rigid pavements. This study also recommends that a local calibration process be completed to determine if the predictive models accurately predict the conditions found on Virginia's roadways. If the predictive models are modified, the results may impact the recommendations resulting from this study. The implementation of the recommendations of this study and the use of the MEPDG in general will provide the Virginia Department of Transportation with a more advanced means of designing and analyzing pavements. This should result in optimal designs that are more efficient in terms of initial construction and future maintenance costs.