Research on collaborative positioning of intelligent vehicle aided navigation based on computer vision technology

Shun Zhang

doi:10.1117/12.3014415

9 January 2024 Research on collaborative positioning of intelligent vehicle aided navigation based on computer vision technology

Shun Zhang

Author Affiliations +

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129692P (2024) https://doi.org/10.1117/12.3014415
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

Due to the low accuracy of collecting vehicle position information, the error in the positioning stage is relatively large. Therefore, the collaborative positioning of intelligent vehicle aided navigation based on computer vision technology is proposed. Taking the computer vision equipment-smart cameras VOF/VOF-S as a specific data acquisition device, and combining with the specific running state of the vehicle, the specific parameters in the data acquisition stage are set differently, so as to realize the accurate acquisition of vehicle position information. In the positioning stage, the plane where the wheel is located is taken as the road plane, and the coordinate parameters of data information collected by several road ground points in VOF/VOF-S computer vision technology device are integrated to realize the transformation of vehicle position information in real space. In the test results, the positioning error of vehicle position under different driving conditions is always stable within 1.50m, which has high accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shun Zhang "Research on collaborative positioning of intelligent vehicle aided navigation based on computer vision technology", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129692P (9 January 2024); https://doi.org/10.1117/12.3014415

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