Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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A Research of a Traffic Light Signal Classification Model using YOLOv5 for Autonomous Driving

자율주행을 위한 YOLOv5 기반 신호등의 신호 분류 모델 연구

  • Joongjin Kook (Dept. of Information Security Engineering, Sangmyung University) ;
  • Hakseung Lee (Dept. of Information Security Engineering, Sangmyung University)
  • 국중진 (상명대학교 정보보안공학과) ;
  • 이학승 (상명대학교 정보보안공학과)
  • Received : 2024.02.09
  • Accepted : 2024.03.20
  • Published : 2024.03.31
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Abstract

As research on autonomous driving technology becomes more active, various studies on signal recognition of traffic lights are also being conducted. When recognizing traffic lights with different purposes and shapes, such as pedestrian traffic lights, vehicle-only traffic lights, and right-turn traffic lights, existing classification methods may cause misrecognition problems. Therefore, in this study, we studied a model that allows accurate signal recognition by subdividing the classification of signals according to the purpose and type of traffic lights. A signal recognition model was created by classifying traffic lights according to their shape and purpose into horizontal, vertical, right turn, etc., and by comparing them with the existing signal recognition model based on YOLOv5, it was confirmed that more correct and accurate recognition was possible.

Keywords

Acknowledgement

This research was funded by a 2023 research Grant from Sangmyung University.

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