Prediction of tire–pavement friction based on asphalt mixture surface texture level and its distributions

Tire–pavement friction plays a key role in traffic safety. With the development of auto vehicle industry, most of the new vehicles are equipped with Anti Braking System (ABS). Therefore, a prediction model representing the braking process of vehicles equipped with ABS is deemed necessary. In this paper, the tire–pavement friction is measured by Dynamic Friction Tester (DFT) and Hand Friction Tester. The surface texture of asphalt pavement is acquired using a recently developed programme named as 2-Dimensional Image Texture Analysis Method (2D-ITAM). Tire–pavement friction at optimum design slip speed corresponding to the maximum tire–pavement friction is calculated with a widely used model. Then a prediction model correlating the tire–pavement friction at optimum design slip speed with the macro-texture and micro-texture of pavement is established using multivariate non-linear regression analysis. This prediction model is validated through laboratory test indicating its effectiveness of predicting the tire–pavement friction. The model is anticipated to be an improved tool which can be considered by practitioners in an optimised asphalt mixture design including the evaluation of skid resistance of pavement.