Improved traffic light detection algorithm for YOLOv8

Tong Guan; Tengfei Chai; Xiangfeng Shen; Nianfeng Li

doi:10.1117/12.3045363

9 October 2024 Improved traffic light detection algorithm for YOLOv8

Tong Guan, Tengfei Chai, Xiangfeng Shen, Nianfeng Li

Author Affiliations +

Proceedings Volume 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024); 132880E (2024) https://doi.org/10.1117/12.3045363
Event: Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 2024, Chengdu, China

Abstract

The implementation of traffic light detection algorithms is a crucial aspect for the mobility of blind individuals. However, the existing algorithms present limitations in terms of detection efficiency, cost, and applicability to mobile devices. In response to these challenges, a novel lightweight traffic light detection algorithm has been proposed, which enhances the YOLOv8 algorithm. Firstly, a two-layer routing attention mechanism is introduced into the end of the backbone network and the neck network to strengthen the feature extraction capability and suppress the interference of irrelevant features. Secondly, the C2fGhost module is used in the neck network of YOLOv8 in order to reduce the amount of floating-point computation in the fusion process of the feature channels and lower the number of model parameters, while improving the feature expression performance. The experimental results demonstrate that the enhanced algorithm yields an mAP50 improvement of 9.3% on the S2TLD dataset. It also reduces the number of model parameters by 6.7% to 2.7 million. The algorithm achieves a detection speed of 102 FPS, enabling real-time detection of traffic signal targets.

This method has been demonstrated to be effective and superior to other mainstream target detection algorithms through a comparison of their respective results.

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

Citation Download Citation

Tong Guan, Tengfei Chai, Xiangfeng Shen, and Nianfeng Li "Improved traffic light detection algorithm for YOLOv8", Proc. SPIE 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 132880E (9 October 2024); https://doi.org/10.1117/12.3045363

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KEYWORDS

Detection and tracking algorithms

Feature extraction

Convolution

Neck

Evolutionary algorithms

Signal detection

Deep learning

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