Characterization of Truck Traffic in California for Mechanistic–Empirical Design

Abstract

Truck traffic information is one of the key inputs in the design and analysis of pavement structures. Until relatively recently, truck traffic data typically were aggregated into equivalent repetitions of a standard axle load for pavement design. The mechanistic pavement design procedures being developed for the California Department of Transportation by the University of California Pavement Research Center will make use of axle-load spectra and other more detailed truck traffic information when incremental design and incremental–recursive design approaches are used. It is necessary to develop traffic inputs in different regions in the state to support the new pavement design procedures. With the weigh-in-motion data collected in California, the truck traffic characteristics were studied for developing default traffic inputs. Traffic composition, temporal and spatial distribution of truck volume, traffic growth rate, vehicle speed, and axle-load spectra were analyzed by intensive and unbiased sampling. Cluster analysis was applied to multivariate responses (e.g., axle-load spectrum) to extract the structure of highway sections in terms of traffic characteristics, which ensured the preservation of useful information during analysis.