Highlighting Dynamically Loaded Pavement Sections with Profile Indices

Abstract

The interaction between road surface roughness and heavy vehicles results in dynamic wheel loading (DWL), which increases pavement damage. The magnitude of DWL is dependent on the level of surface roughness and its characteristics and the properties and speeds of heavy vehicles. The measurement of DWL under normal operating conditions is costly, and the estimation of the resultant pavement damage is difficult because of the great variation in heavy vehicle fleet characteristics operating on the network. Additional damage caused by DWL is reflected in increased pavement deterioration over time. Deterioration is apparent in changes in the surface profile characteristics, which have a determining influence on dynamic loading and the degree of its spatial repeatability. The suitability of a number of profile indices as indicators of dynamically loaded pavement sections was assessed. Several regression models were developed with different profile indices used as predictors of different measures of pavement damage caused by DWL. The international roughness index and heavy articulated truck index were among the indices tested. The magnitudes of the simulated DWL were represented by such measures as dynamic load coefficient and dynamic aggregate force coefficient. This approach could help road authorities identify sections that are subject to high DWL and to take appropriate measures to reduce the impact. The heavy articulated truck index, measured with the dynamic aggregate force coefficient, proved to be the best predictor of pavement damage caused by DWL.