Evaluation of skid resistance of asphalt pavement covered with aeolian sand in desert areas

Abstract

Particulate contaminants adhering to a desert road can significantly affect the contact characteristics of tires and pavements. The effects of sand quantity, temperature and wearing on the skid resistance were analyzed through the laboratory tests. Image analysis and generalized regression neural networks (GRNN) were used to obtain the macrostructure, followed by reconstructing a three-dimensional model and predicting the texture depth of asphalt pavements. Finally, decay prediction models of skid resistance were established. The results show that the 3D model reconstructed by digital images can clearly show the sand distribution on the road. Furthermore, the GRNN model was found to be reliable, with an average relative error of only 3.4%. Aeolian sand amount, temperature and wearing cycles all affect the skid resistance, while the sand has the greatest influence. The skid resistance model can predict the friction capacity well and it provides a reference for determining the maintenance time for asphalt pavements in desert areas.