Cluster Analysis of LTPP Data to Estimate MEPDG Traffic Input for NM State and Perform a Sensitivity Analysis

Abstract

Mechanistic-empirical pavement design guide (MEPDG) uses vehicle type, load spectra and number of axle to characterize traffic inputs for the pavement designs, as an alternate of the previously used equivalent single axle load (ESAL). Long term pavement performance (LTPP) study has 8 sites in New Mexico (NM) which collects the weigh-in-motion (WIM) data all over the year. In this study, the LTPP traffic data were extracted and then clustering technique was used to find out the similarities between different sites. Then, the traffic data from different cluster was compared to the default values in the MEPDG software. The effect of these differences on the pavement performance for New Mexico conditions was established through a sensitivity analysis. It was found that the alligator cracking and rutting are sensitive to axle load distribution. However, IRI was not significantly affected.