Characterization of Asphalt Pavement Surface Texture

Abstract

This paper presents improved analysis methods for characterizing asphalt pavement surface texture and focuses on the use of laser profiling techniques to estimate friction characteristics. Derived from signal processing theories, texture spectral analysis methods show promise for improving characterization of the tire–pavement interface. Texture parameters measured with spectral analysis techniques represent a means for quantifying surface properties. Current methods to analyze frictional properties rely on the mean profile depth (MPD) and mean texture depth (MTD) texture parameters. Although these parameters are used widely, they do not capture the range and distribution of surface asperities on the pavement surface. Knowing the distribution of surface asperities is critical for assessing friction characteristics. Thus, texture spectral analysis methods are anticipated to improve on the MPD and MTD parameters by capturing relevant texture-level distributions. This study investigates the applicability of laser profiling systems for measuring pavement surface texture and subsequent relationships to friction. Models accounting for aggregate and mixture properties are developed and related to texture parameters through analysis of constructed field sections and corresponding laboratory samples. Results indicate that stationary laser profiling systems can capture the microtexture and macrotexture spectrum and suggest that a comprehensive friction characterization of asphalt mixtures can be obtained in a laboratory setting. With this analysis system, it is believed that asphalt mixture designers will have an improved tool by which to estimate pavement surface texture and frictional properties.