Research on the lane line detection method based on YOLOv5

Xiang Gu; Wenjie Shu

doi:10.1117/12.3009519

16 October 2023 Research on the lane line detection method based on YOLOv5

Xiang Gu, Wenjie Shu

Author Affiliations +

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 1280317 (2023) https://doi.org/10.1117/12.3009519
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

Lane-line detection is one of the key technologies in the field of intelligent driving. This paper changes the anchor box regression loss function of the YOLOv5s to the EIoU function to construct a kind of lane-line detection model. The experimental results show that the improved detection model is more accurate in lane-line detection. The improved model improved mAP by about 11.1% compared to the conventional YOLOv5 model. At the same time, it can solve the problems of traditional models such as low real-time performance and underfitting to curved lane lines.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiang Gu and Wenjie Shu "Research on the lane line detection method based on YOLOv5", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 1280317 (16 October 2023); https://doi.org/10.1117/12.3009519

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KEYWORDS

Education and training

Object detection

Data modeling

Detection and tracking algorithms

Image processing

Deep learning

Performance modeling

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