Development of simplified traffic loading for secondary road pavement design

Abstract

How to recognise traffic loading clusters and estimate load spectra using historical weigh-in-motion (WIM) data is critical to pavement mechanistic-empirical (ME) design. Various clustering approaches have been proposed in recent years mainly for high-volume roads. These methods require site-specific information to determine the design location cluster. In most cases for secondary road pavements, such data are missing due to resource constraints. In this paper, a simplified approach is developed to generate traffic loading for secondary road pavement design. With WIM data in Arkansas, the K-means cluster algorithm is applied and simplified Truck Traffic Classification clusters are developed. This method only requires prior knowledge of the dominant truck distributions on the design location and will alleviate the work related to traffic load data preparation. A case study is provided to illustrate the applicability of using the simplified clusters to generate Level 2 traffic inputs for DARWin-ME.