Optimizing pavement skid resistance measurement with texture resolution sensitivity indices

Accurate measurement of pavement skid resistance (SR) is essential for road safety but remains challenging. Surface texture plays a crucial role in SR, yet varying texture resolutions for the same surface can introduce inconsistencies in texture descriptors and friction coefficients. This study introduces Texture Resolution Sensitivity Indices (TRSI) to quantify the impact of texture resolution on SR and the resulting errors. TRSI combines texture characterization (geometric, spectral, and fractal descriptors) with friction coefficient predictions, using the highest resolution or measured coefficients as benchmarks. Multi-resolution datasets were created via downsampling and Dynamic Time Warping for sensitivity analysis. Results show that for geometric descriptors, 0.25 mm marks a critical threshold between macrotexture and microtexture, with sensitivity rising sharply below this value. Spectral analysis indicates that lower resolutions miss high-frequency microtexture details, while macrotexture remains largely unaffected. Although fractal dimensions are scale-independent in theory, lower resolutions increase calculation variability. Persson's rubber-road contact model identified 0.02 mm as the optimal resolution for friction prediction, balancing overestimation at finer scales and underestimation at coarser ones. The proposed TRSI offers a practical tool for selecting texture resolutions, enabling efficient and accurate SR assessments.