Using Neural Networks for Pavement Rolling Resistance

Abstract

All pavements contribute to the rolling resistance of vehicles. For passenger cars, the pavement influence is limited to the surface properties, but heavy trucks are influenced by the deformation, the internal damping, and non-elastic behavior of the pavement materials involved. Previous studies have been addressing the pavement type, the material type and various stages of compaction. Recently, even the effects of curling slabs on rolling resistance was assessed. As sustainable pavements are now becoming a requirement from road authorities, it is important to have access to calculable parameters of energy losses during use, and not only from construction. The present paper addresses some of the input parameters needed to assess rolling resistance losses for pavements in general and rigid pavements in particular, by using neural network techniques. The results can be used for the decision-making in either bidding processes or strategic planning.