Abstract

Pavement surface texture features are one of key factors affecting the skid resistance of pavement. In this study, a set of stable and reliable texture measurement equipment was firstly assembled by using the linear laser ranging sensor, control system and data acquisition system. Secondly, the equipment was calibrated, and the superposition error of sensor and control system was tested by making a standard gauge block. Thirdly, four different kinds of asphalt mixture were designed, and their surface texture features were obtained by leveraging a three-dimensional laser scanner. Therefore, the surface texture features were characterized as one-dimensional profile features and three-dimensional surface features. At the end of this study, a multi-scale texture feature characterization method was proposed. Results demonstrate that the measurement accuracy of the laser scanning system in the x-axis direction can be controlled ranging from −0.01 mm to 0.01 mm, the resolution in the XY plane is 0.05 mm, and the reconstructed surface model of surface texture features can achieve a good visualization effect. They also show that the root mean square deviation of surface profiles of different asphalt pavements fluctuates greatly, which is mainly affected by the nominal particle size of asphalt mixture and the proportion of coarse aggregate, and the non-uniformity of pavement texture distribution makes it difficult to characterize the roughness of asphalt pavement effectively by a single pavement surface profile. This study proposed a texture section method to describe the 3D distribution of road surface texture at different depths. The macrotexture of the road surface gradually changes from sparse to dense starting from the shallow layer. The actual asphalt pavement texture can be characterized by a simplified combination model of “cone + sphere + column”. By calculating the surface area distribution of macro and microtextures of different asphalt pavements, it was concluded that the surface area of asphalt pavement under micro scale is about 1.8–2.2 times of the cutting area, and the surface area of macrotexture is about 1.4 times of the cutting area. Moreover, this study proposed texture distribution density to characterize the roughness of asphalt pavement texture at different scales. The SMA index can represent the macroscopic structure level of different asphalt pavements to a certain extent, and the SMI index can well represent the friction level of different asphalt pavements.

Highlights

  • The skid resistance of pavement is an important factor affecting road traffic safety [1]

  • This paper proposes a texture section method to evaluate the spatial distribution of the three-dimensional texture of asphalt pavement surfaces, which can directly measure and evaluate the roughness of the pavement texture

  • The effective measurement range is ±23 mm, and the maximum resolution is 0.05 mm. It can fully meet the needs of surface profile measurement for the general asphalt mixture surface layer and even for the large void asphalt pavement, such as OGFC

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Summary

Introduction

The skid resistance of pavement is an important factor affecting road traffic safety [1]. Based on the above background, this paper furtherly upgrades the original laser equipment developed in our previous research [25] and designs a 3D laser scanner which can accurately collect 3D point cloud data and reconstruct the 3D model of asphalt pavement. Limited by the width of the line laser beam, the display system can only display one scan of point cloud data at a time, and later it needs to be stitched into a complete specimen image with the help of MATLAB (Ver 9.1,2016, MathWorks company; MA, USA) software.

Design Requirement
Correlation between Pavement Texture Density and Skid Resistance Performance
Summary
Prospects
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