Road Pothole Detection and Location System Based on YOLOv5 and Beidou GPS
DOI: 10.23977/acss.2025.090407 | Downloads: 3 | Views: 55
Author(s)
Feng Yuanxin 1, Fang Zeping 1, Wang Yitong 1, Du Shuna 1
Affiliation(s)
1 School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
Corresponding Author
Fang ZepingABSTRACT
Road potholes are harmful to safe transportation, which will cause vehicle damage, poor ride comfort and put passengers in danger. Road pothole detection and result application is one of the key measures to solve the above problems. Therefore, this paper designs a road pothole detection and location system. The system mainly consists of edge computing platform (including detection algorithm), road pothole image acquisition module, positioning module, display module and auxiliary module. The computing platform adopts Jetson Nano. The road pothole detection algorithm adopts YOLOv5 algorithm. The positioning module adopts Beidou GPS module. First, the camera collects the image set of road potholes (or adopts an open image set). The image set is divided into two parts: training set and test set, which are used for training and testing respectively. Then, based on YOLOv5 algorithm, the road pothole images in the training set are trained, and the optimal target detection model is obtained. Finally, the model is used to test the road pothole images in the test set. The open road pothole image set is tested, and the road pothole recognition rate is above 90%. Through this system, road potholes can be accurately detected and the location information of potholes can be recorded. The research results in this paper can be provided to traffic management departments and used in unmanned vehicles, which is of great significance to reduce the impact of road potholes on safe driving of vehicles.
KEYWORDS
Road potholes, Detection, YOLOv5, Beidou GPS, Positioning, Edge calculationCITE THIS PAPER
Feng Yuanxin, Fang Zeping, Wang Yitong, Du Shuna, Road Pothole Detection and Location System Based on YOLOv5 and Beidou GPS. Advances in Computer, Signals and Systems (2025) Vol. 9: 52-61. DOI: http://dx.doi.org/10.23977/acss.2025.090407.
REFERENCES
[1] Raja G, Anbalagan S, Senthilkumar S, Dev K, Qureshi NM. SPAS: smart pothole-avoidance strategy for autonomous vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(10): 19827-19836.
[2] Mikhailiuk, A. Dahnoun, N. Design, development and testing of automatic pothole detection and alert system[C]. In 2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016, 123-128. IEEE.
[3] Alpert, M.Onyshchenko. Recognition of potholes with neural network using unmanned ground vehicles[C]. In International Conference on Computer Science, Engineering and Education Applications, 2020, 209-220.
[4] He Huitao. Study on Damage Detection and Maintenance Strategy of Expressway Asphalt Pavement [J]. Traffic Construction and Management, 2024(6): 109-111.
[5] Xuan Yiguo, Yu Chengbo, Jiang Qichao. Road cracks and potholes detection algorithm based on improved YOLOv7 [J]. Science, Technology and Engineering, 2024, 24(17): 7205-7213.
[6] Yuan Chaochun, Wang Junxian, He Youguo. Active obstacle avoidance control of smart cars based on road potholes detection [J]. Journal of Jiangsu University (Natural Science Edition), 2022, 43(05): 504-511+518.
[7] Chang Xiaobo. Research on unmanned vehicle-mounted road potholes visual perception system [D]. Chang'an University, 2023.
[8] Gajankush, A., Dedhia, V., Kaskar, Y., Dandekar, Y.Chhabria. A pothole grievance reporting system using YOLOv5 Algorithm[C]. In 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), 2023, 1-4.
[9] Mpofu, W. T., Ndlovu, B., Dube, S. Mutengeni, J. Pothole detection and reporting system using deep learning[J]. In IEOM Society International, 2022, 232-238.
[10] Jyoti Madake, Hemal Kulkarni. Enhancing Visibility in foggy landmark images: advanced restoration methods [C]. 2025 International Conference on Emerging Smart Computing and Informatics (ESCI), 2025, 1-7.
[11] Rohitaa, R., Shreya, S.Amutha, R. Intelligent deep learning based pothole detection and reporting system[C]. In 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2021, 1-5.
[12] Park S S, Tran V T, Lee D E. Application of various yolo models for computer vision-based real-time pothole detection[J]. Applied Sciences, 2021, 11(23): 11229.
[13] Shaghouri, Anas Al, Rami Alkhatib, and Samir Berjaoui. Real-time pothole detection using deep learning[J]. arxiv preprint arxiv: 2107.06356(2021).
[14] Dhwani Desai, Abhishek Soni, Dhruv Panchal, Sachin Gajjar. Real-time pothole detection on TMS320C6678 DSP[C]. In 2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016, 123-128.
[15] Lekshmipathy, Janani, Sunitha Velayudhan, and Samson Mathew. Effect of combining algorithms in smartphone based pothole detection[J]. International Journal of Pavement Research and Technology, 2021, 14: 63-72.
[16] Desai, Dhwani, et al. Design, development and testing of automatic pothole detection and alert system[C]. 2019 IEEE 16th India council international conference (INDICON). 2019, 12-34.
[17] Hiral Desai Dhruvi Zala. IoT-Based pothole detection system for proactive road safety [C]. International Journal of Pavement Research and Technology. 2023, 19-26.
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