Prediction of Friction Coefficient Based on 3D Texture Characteristics of Road Surfaces

Accurate assessment of road pavement friction is crucial for maintaining road safety. This study explores the prediction of the friction coefficient (µ) using 3D texture parameters of pavement surfaces. Measurements were conducted on 17 different rural road sections using the Traction Watcher One (TWO) for friction coefficients and a newly developed Static Road Scanner (SRS) for surface texture. Multiple linear regression models were created, incorporating texture parameters such as the valley material portion (Smr2,MIC), arithmetic mean peak curvature (Spc,MAC), and dale void volume (Vvv,PS). The results demonstrate a strong correlation between texture characteristics and friction, with R2 values up to 0.80 and an RMSE as low as 0.076, validating the model’s accuracy. This approach highlights the potential of using non-contact texture measurements for reliable prediction of friction, offering a significant advancement in pavement management and safety.