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Asphalt Pavement Texture Level and Distribution Uniformity Evaluation Using Three-Dimensional Method
To supplement the research on the evaluation method of asphalt pavement texture, novel three-dimensional (3D) methods are proposed. First, pavement textures were measured in laboratory from asphalt mixture specimens using laser texture scanner (LTS), and the macro-texture and micro-texture were extracted based on spectrum analysis techniques. Then, macro-texture level evaluation indices f8mac and f9mac together with micro-texture level evaluation indices f8mic and f9mic were proposed based on the gray level co-occurrence matrix (GLCM) method, and the hyperparameters existing in GLCM were discussed. Through the correlation analysis with mean texture depth (MTD) measured by sand patch method (SPM) and friction coefficient µ measured by walking friction tester (WFT), the optimum pavement texture level evaluation indices were determined. Additionally, the evaluation index σ of distribution uniformity of pavement texture (DUPT) was proposed based on the uniformity of deviations between sub-surfaces and the average surface of pavement texture. Finally, the correlations of σ with texture profiles were studied. The results show that f8mac and f8mic are the optimum indices for pavement texture level. MTD has significant correlation with f8mac, and the correlation coefficient R is 0.9348; friction coefficient µ has significant correlation with f8mic, and the R is 0.8030. The hyperparameters of GLCM selected in this study were proved effective. Moreover, the effectiveness of σ is also validated by calibrating with standard grooved surface. It can be concluded that the proposed indices in this study are suitable to the evaluation of pavement texture level and pavement texture distribution.
Asphalt Pavement Texture Level and Distribution Uniformity Evaluation Using Three-Dimensional Method
To supplement the research on the evaluation method of asphalt pavement texture, novel three-dimensional (3D) methods are proposed. First, pavement textures were measured in laboratory from asphalt mixture specimens using laser texture scanner (LTS), and the macro-texture and micro-texture were extracted based on spectrum analysis techniques. Then, macro-texture level evaluation indices f8mac and f9mac together with micro-texture level evaluation indices f8mic and f9mic were proposed based on the gray level co-occurrence matrix (GLCM) method, and the hyperparameters existing in GLCM were discussed. Through the correlation analysis with mean texture depth (MTD) measured by sand patch method (SPM) and friction coefficient µ measured by walking friction tester (WFT), the optimum pavement texture level evaluation indices were determined. Additionally, the evaluation index σ of distribution uniformity of pavement texture (DUPT) was proposed based on the uniformity of deviations between sub-surfaces and the average surface of pavement texture. Finally, the correlations of σ with texture profiles were studied. The results show that f8mac and f8mic are the optimum indices for pavement texture level. MTD has significant correlation with f8mac, and the correlation coefficient R is 0.9348; friction coefficient µ has significant correlation with f8mic, and the R is 0.8030. The hyperparameters of GLCM selected in this study were proved effective. Moreover, the effectiveness of σ is also validated by calibrating with standard grooved surface. It can be concluded that the proposed indices in this study are suitable to the evaluation of pavement texture level and pavement texture distribution.
Asphalt Pavement Texture Level and Distribution Uniformity Evaluation Using Three-Dimensional Method
Lecture Notes in Civil Engineering
Pasindu, H. R. (editor) / Bandara, Saman (editor) / Mampearachchi, W. K. (editor) / Fwa, T. F. (editor) / Dong, Shihao (author) / Han, Sen (author)
2022-01-30
19 pages
Article/Chapter (Book)
Electronic Resource
English
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