Browse > Article
http://dx.doi.org/10.12815/kits.2022.21.5.57

Development of Mask-RCNN Based Axle Control Violation Detection Method for Enforcement on Overload Trucks  

Park, Hyun suk (Dept. of Highway & Transportation Research., Korea Institute of Civil Engineering and Building Technology)
Cho, Yong sung (ITS Performance Evaluation Center, Korea Institute of Civil Engineering and Building Technology)
Kim, Young Nam (Computer Vision and Artificial Intelligence laboratory, Advanced Institute of Convergence Technology)
Kim, Jin pyung (Computer Vision and Artificial Intelligence laboratory, Advanced Institute of Convergence Technology)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.21, no.5, 2022 , pp. 57-66 More about this Journal
Abstract
The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.
Keywords
Overloaded Truck Axle Control; Mask RCNN; Axle Control Violation Detection Method;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Redmon, J., Divvala, S., Girshick, R. and Farhadi, A.(2016), "You only look once: Unified, real-time object detection", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.779-788.
2 Han, J. H. and Hong, S. S.(2020), "Semiconductor Process Inspection Using Mask R-CNN", Journal of the Semiconductor & Display Technology, vol. 19, no. 3, pp.12-18.
3 SBS News, https://news.sbs.co.kr/news/endPage.do?news_id=N1005159046&oaid=N1005159979&plink=TEXT&cooper=SBSNEWSEND, 2022.06.01.
4 Enforcement Decree of the Road Act, Enforcement Decree of the Road Act(2022), Article 80, Interference with Measuring Loads, Korean Law Information Center.
5 Girshick, R., Donahue, J., Darrell, T. and Malik, J.(2014), "Rich feature hierarchies for accurate object detection and semantic segmentation", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.580-587.
6 He, K., Gkioxari, G., Dollar, P. and Girshick, R.(2017), "Mask r-cnn", Proceedings of the IEEE International Conference on Computer Vision, pp.2961-2969.
7 He, K., Zhang, X., Ren, S. and Sun, J.(2016), "Deep residual learning for image recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.770-778.
8 Road Act Enforcement Decree(2022), Article 79 Vehicle Operation Restriction, etc., National Law Information Center.
9 Oh, M. S., Kwon, S. M. and Oh, C.(2018), "Analyzing the Impact of Weigh-in-Motion (WIM)-based Overloading Enforcement Systems on Freeway Traffic Stream", International Journal of Highway Engineering, vol. 20, no. 5, pp.129-140.   DOI
10 Zhao, X. X., Shi, M., Ren, P., He, R., Wei, X. and Yang, H.(2022), "Crack Detection and Comparison Study Based on Faster R-CNN and Mask R-CNN", Sensors, vol. 22, no. 3, p.1215.   DOI