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다중 차선 인식을 위한 YOLO의 적용 Application of YOLO for Multi-Lanes Recognition

박성찬, 박희문, 박진현
  • 언어KOR
  • URLhttp://db.koreascholar.com/Article/Detail/412123
한국기계기술학회지 (韓國機械技術學會誌)
제23권 제6호 (2021.12)
pp.1137-1145
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

We need data such as the number of lanes for lane change on the road as well as environmental and object recognition of the road for the autonomous vehicle of the future. This study proposed an algorithm that recognizes the left and right lanes and the center lane while driving differently from the black box image taken from a car. In general, deep learning does not recognize lanes individually but recognizes all lanes as only one lane. Therefore, using YOLO's object recognition function, the left and right lanes and the center lane were detected as different lanes, and a heuristic method was applied to recognize multi-lanes as more correct lanes. As a result of the performance evaluation, we confirmed that the proposed method detects the lane more accurately than Fast R-CNN and only YOLOv2.

저자
  • 박성찬(경상국립대학교) | SungchanPark
  • 박희문(경상국립대학교) | Hee-Mun Park
  • 박진현(경상국립대학교) | Park Jin-Hyun Corresponding Author