Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
3D Rutting Features Extraction Through Continuous Pavement Laser Point Cloud
https://orcid.org/http://orcid.org/0000-0002-9842-8747
High-precision continuous laser point cloud data of road surface includes not only pavement, but also rutting and other pavement diseases. It is urgent to develop an automatic method to extract the information of 3D features of rutting which is the initial pavement disease. It is difficult for the rutting extraction method based on cross-section to express the information which is not in section position. Therefore, this paper proposes a fine 3D feature extraction method for continuous rutting based on feature images. First, road surface elevation feature image, slope feature image and aspect feature image are generated by road point cloud data. Second, the rutting features of each feature image are comprehensively analyzed. And the 3D contour lines of rutting side edge and rutting bottom center are extracted by image processing method according to rutting features. Finally, the moving weighted mean filtering method is used, considering wheel equidistance to repair rutting track contour information. And the fine 3D features of rutting are expressed by the 3D contour lines of repaired rutting. The 3D characteristic contour of rutting is extracted from 3D data of actualpavement by the above method. The experimental results show that the method in this paper is robust for capturing rutting diseases, with the measurement error of rutting depth of no more 0.3 mm and the deviation of rutting position of less than 0.5 cm.
3D Rutting Features Extraction Through Continuous Pavement Laser Point Cloud
https://orcid.org/http://orcid.org/0000-0002-9842-8747
High-precision continuous laser point cloud data of road surface includes not only pavement, but also rutting and other pavement diseases. It is urgent to develop an automatic method to extract the information of 3D features of rutting which is the initial pavement disease. It is difficult for the rutting extraction method based on cross-section to express the information which is not in section position. Therefore, this paper proposes a fine 3D feature extraction method for continuous rutting based on feature images. First, road surface elevation feature image, slope feature image and aspect feature image are generated by road point cloud data. Second, the rutting features of each feature image are comprehensively analyzed. And the 3D contour lines of rutting side edge and rutting bottom center are extracted by image processing method according to rutting features. Finally, the moving weighted mean filtering method is used, considering wheel equidistance to repair rutting track contour information. And the fine 3D features of rutting are expressed by the 3D contour lines of repaired rutting. The 3D characteristic contour of rutting is extracted from 3D data of actualpavement by the above method. The experimental results show that the method in this paper is robust for capturing rutting diseases, with the measurement error of rutting depth of no more 0.3 mm and the deviation of rutting position of less than 0.5 cm.
3D Rutting Features Extraction Through Continuous Pavement Laser Point Cloud
https://orcid.org/http://orcid.org/0000-0002-9842-8747
High-precision continuous laser point cloud data of road surface includes not only pavement, but also rutting and other pavement diseases. It is urgent to develop an automatic method to extract the information of 3D features of rutting which is the initial pavement disease. It is difficult for the rutting extraction method based on cross-section to express the information which is not in section position. Therefore, this paper proposes a fine 3D feature extraction method for continuous rutting based on feature images. First, road surface elevation feature image, slope feature image and aspect feature image are generated by road point cloud data. Second, the rutting features of each feature image are comprehensively analyzed. And the 3D contour lines of rutting side edge and rutting bottom center are extracted by image processing method according to rutting features. Finally, the moving weighted mean filtering method is used, considering wheel equidistance to repair rutting track contour information. And the fine 3D features of rutting are expressed by the 3D contour lines of repaired rutting. The 3D characteristic contour of rutting is extracted from 3D data of actualpavement by the above method. The experimental results show that the method in this paper is robust for capturing rutting diseases, with the measurement error of rutting depth of no more 0.3 mm and the deviation of rutting position of less than 0.5 cm.
3D Rutting Features Extraction Through Continuous Pavement Laser Point Cloud
Int. J. Pavement Res. Technol.
Liu, Rufei (Autor:in) / Ren, Hongwei (Autor:in) / Chai, Yongning (Autor:in) / Yang, Jiben (Autor:in)
International Journal of Pavement Research and Technology ; 16 ; 1241-1254
01.09.2023
14 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Rutting extraction from vehicle-borne laser point clouds
| Elsevier | 2024
Asphalt Pavement Rutting - Western States
| NTIS | 1984
Rutting of Airport Pavement Granular Layers
| ASCE | 2004
Boeing's Full-Scale Pavement Rutting Tests
| British Library Conference Proceedings | 1997
Asphalt Pavement Rutting Experience in Canada
| British Library Conference Proceedings | 1990