Vehicle wheel load positioning method based on multiple projective planes.
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| Title: | Vehicle wheel load positioning method based on multiple projective planes. |
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| Authors: | Sun, Kai1 (AUTHOR), Jiang, Xu1 (AUTHOR), Qiang, Xuhong2 (AUTHOR) qiangxuhong@tongji.edu.cn |
| Source: | Computer-Aided Civil & Infrastructure Engineering. 6/3/2025, Vol. 40 Issue 14, p1993-2009. 17p. |
| Subjects: | Projective planes, Material fatigue, Multiple target tracking, Computer vision, Automobile license plates, Spatiotemporal processes |
| Abstract: | Computer vision‐based vehicle load monitoring methods could obtain spatiotemporal data of vehicle loads, which is important for bridge monitoring and operation. However, during the process of vehicle detection and tracking, current research usually focuses on the vehicle as a whole, and there is a lack of research on the accurate positioning of vehicle wheel loads. For the fatigue analysis of orthotropic steel deck, stress at the structural details belongs to the typical third‐class system, and related research requires accurate wheel load position. Based on the principle of camera imaging, this study proposes an innovative vehicle wheel load location method based on vehicle license plate detection and multiple projective planes, and the accurate positioning of the vehicle center is achieved by the projective relationship matrix of different planes. Then, accurate measurement of the lateral wheelbase is achieved through secondary detection and projective transformation. Further, accurate wheel load tracking for fatigue research is achieved by the multi‐objective tracking algorithm. Based on theoretical analysis and practical application results, the effectiveness and accuracy of this method have been verified. Different from traditional positioning methods based on vehicle detection boxes and 3D reconstruction boxes, the proposed method has higher accuracy and will play a fundamental role in the use of vehicle load spatiotemporal data for more accurate analysis such as fatigue research. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer-Aided Civil & Infrastructure Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Abstract: | Computer vision‐based vehicle load monitoring methods could obtain spatiotemporal data of vehicle loads, which is important for bridge monitoring and operation. However, during the process of vehicle detection and tracking, current research usually focuses on the vehicle as a whole, and there is a lack of research on the accurate positioning of vehicle wheel loads. For the fatigue analysis of orthotropic steel deck, stress at the structural details belongs to the typical third‐class system, and related research requires accurate wheel load position. Based on the principle of camera imaging, this study proposes an innovative vehicle wheel load location method based on vehicle license plate detection and multiple projective planes, and the accurate positioning of the vehicle center is achieved by the projective relationship matrix of different planes. Then, accurate measurement of the lateral wheelbase is achieved through secondary detection and projective transformation. Further, accurate wheel load tracking for fatigue research is achieved by the multi‐objective tracking algorithm. Based on theoretical analysis and practical application results, the effectiveness and accuracy of this method have been verified. Different from traditional positioning methods based on vehicle detection boxes and 3D reconstruction boxes, the proposed method has higher accuracy and will play a fundamental role in the use of vehicle load spatiotemporal data for more accurate analysis such as fatigue research. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10939687 |
| DOI: | 10.1111/mice.13432 |
