Abstract
The skid resistance of asphalt pavement is affected by the surface macrotexture depth, especially when there is water on the pavement. Pavements with appropriate macrotexture can effectively ensure the traffic safety. However, previous research on characterisation methods still cannot properly reflect the three-dimensional (3D) information of pavement macrotexture, such as 3D features or distribution density of texture. In this study, a 3D laser scanner is used to collect the data of asphalt pavement texture, which will be used to reconstruct the 3D pavement model in the next step. Thereafter, the model is evenly meshed by a large number of micro elements. Based on the volume of elements, a method is proposed to characterise the 3D features of pavement macrotexture; the 3D characteristics of macrotexture can also be analysed quantitatively. Compared with four types of gradation of asphalt pavement, the results show that the proposed method can accurately represent the 3D macrostructure of asphalt pavement surface.
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