摘要
车道线检测是推动辅助驾驶和无人驾驶技术实现的重要因素。介绍车道线检测技术的应用和发展,列举部分车道线检测算法,对其研究现状进行综述;评述传统方法和深度学习方法的优缺点,系统地阐述深度学习对车道线检测领域的贡献;最后分析车道线检测方法目前存在的难点,对其未来的研究方向进行展望,为今后车道线检测技术的学习和发展提供参考。
Lane detection is an important factor to promote the realization of assisted driving and unmanned driving technology.This paper first introduces the application and development of lane detection technology,then lists some lane detection algorithms,and summarizes its research status.The advantages and disadvantages of traditional methods and deep learning methods are reviewed,and the contribution of deep learning to lane detection is systematically described.Finally,the difficulties of lane detection methods are analyzed,and the future research direction is prospected,which provides references for the study and development of lane detection technology in the future.
作者
杨荣锦
张秀峰
龚莉娜
牛选兵
王伟
马天翼
YANG Rong-jin;ZHANG Xiu-feng;GONG Li-na;NIU Xuan-bing;WANG Wei;MA Tian-yi(Schoo1 of E1ectromechanica1 Engineering, Da1ian Minzu University, Da1ian Liaoning 116605, China)
出处
《大连民族大学学报》
2021年第1期40-44,共5页
Journal of Dalian Minzu University
关键词
车道线检测
深度学习
语义分割
计算机视觉
lane detection
deep learning
semantic segmentation
computer vision
