Prediction of surface texture for better performance of friction courses

Pavement texture influences safety, human health, agency, user, and environmental costs. Based on the literature, the relationship between mix composition and surface texture is uncertain. This implies that the design of the main surface characteristics of friction courses (e.g., noise-related properties, permeability, friction in wet conditions, and texture) may lack sound bases. This calls for further investigation, and consequently, the main goals of the study presented in this paper were confined into the following: (i) To study how gradation and texture interact for known mixtures; (ii) To express texture as a function of mixture composition. Results show that aggregate gradation is a reliable basis to derive predictions about surface texture levels. In more detail, the concept of nominal maximum aggregate size confirms to be relevant and to influence texture levels, especially when introducing slight adjustments to its definition. The one-peak and log-symmetric model appears to provide a simple and effective interpretation. Results can benefit researchers and practitioners involved in pavement surface design, e.g., for the sake of ISO implementation.