Binocular stereo vision-based analysis of skid resistance in asphalt mixtures: A study of AC-13, SMA-13, and OGFC-13

Abstract

Evaluating the skid resistance of asphalt mixtures is crucial for enhancing road safety. This study investigates the skid resistance and surface texture characteristics of three types of asphalt mixtures-asphalt concrete (AC-13), stone matrix asphalt (SMA-13), and open graded function course (OGFC-13)-under varying wear durations. Using binocular stereo vision, surface texture information was captured to calculate both macro- and micro-texture parameters. Skid resistance was assessed through the sand patch and British Pendulum tests. A regression model was developed to relate texture parameters to skid resistance, revealing a segmented decline in skid resistance through three distinct phases: growth, attenuation, and stability. The results indicate significant correlations between macro-texture parameters (e.g., mean texture depth, arithmetic mean, peak spacing) and texture depth (TD), with correlation coefficients ranging from 0.45 to 0.80. The regression model, based on the logarithmic transformation of the power function, demonstrated superior accuracy in predicting the relationship between macro-texture parameters and TD compared to multiple linear regression. Furthermore, the fractal dimension and British Pendulum number (BPN) were best fitted using a Gaussian nonlinear function. This study highlights the effectiveness of binocular stereo vision in analyzing skid resistance changes over time; however, additional texture parameters are required for a more comprehensive analysis.