Research on Data Fusion Algorithms for Non-stop Overload Detection on Highways

With the rapid development of highway network, overloading of freight vehicles has caused serious impact on road safety and infrastructure. In order to improve the data fusion accuracy of the overload control system, combining dynamic weighing, image capture recognition and laser scanning technologi...

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Vydáno v:2024 IEEE 5th International Conference on Pattern Recognition and Machine Learning (PRML) s. 291 - 295
Hlavní autoři: Tang, Lian, Liu, Qing, Lin, Hang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 19.07.2024
Témata:
Accuracy
Data fusion
Data integration
Dynamic weighing
Heuristic algorithms
Laser scanning
Non-stop detection
Road transportation
Systems architecture
Technological innovation
Transportation
Transportation industry
Vehicle dynamics
Weight measurement
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Shrnutí:With the rapid development of highway network, overloading of freight vehicles has caused serious impact on road safety and infrastructure. In order to improve the data fusion accuracy of the overload control system, combining dynamic weighing, image capture recognition and laser scanning technologies, a complete set of non-stop detection system architecture is researched and designed, a multi-feature volume data fusion model is constructed, and the data matching and fusion process is optimized. Through the application test of comprehensive super-control platform, the results show that the proposed data fusion algorithm of non-stop detection for highway super-control can effectively control the error of total weight within ± 2.5%, and the errors of vehicle length and height within ± 150mm and ± 50mm, respectively, which verifies its application value in highway super-control.
DOI:10.1109/PRML62565.2024.10779619