Effect of Traffic Load Measurement Bias on Pavement Life Prediction

Abstract

The new Mechanistic-Empirical Pavement Design Guide (MEPDG) requires comprehensive traffic inputs to predict pavement performance. Axle load spectra play a critical role in the impact of traffic on pavement performance. Weigh-in-motion (WIM) systems are becoming widely used as an efficient means of collecting traffic load data for mechanistic pavement design. The quality of the WIM-based data, however, remains a concern among pavement engineers. Previous research showed that WIM equipment calibration bias may lead to significant bias in the estimation of equivalent single-axle loads. This study investigated the effect of traffic load measurement bias due to WIM measurement errors on pavement life prediction on the basis of the mechanistic-empirical approach proposed by MEPDG. The results of this study not only support but also advance the existing research in this critical area. The findings of this study can be used to estimate pavement life prediction bias when inaccurate WIM data are used. They can also serve as guidelines for state highway agencies for the selection of WIM equipment and the establishment of criteria for equipment calibration.