计算机科学与探索2026，Vol.20Issue(6)：1545-1561,17.DOI:10.3778/j.issn.1673-9418.2508016
深度学习在车道线检测中的应用综述
Review of Deep Learning Based Lane Line Detection Methods
摘要
Abstract
With the rapid development of autonomous driving technology,lane detection,as the core task of environmental perception systems,faces key challenges such as occlusion,sudden changes in lighting,and geometric diversity in complex scenes.A systematic study is conducted on lane detection methods based on deep learning to address this issue,with a focus on analyzing the algorithm frameworks,implementation processes,and performance optimization strategies of 2D and 3D detection technologies.In terms of 2D detection,the limitations of traditional image processing methods are explored,and the applications of convolutional neural networks,fully convolutional networks,and Transformer architectures in feature extraction,instance segmentation,and lightweight design are elaborated in detail.In the aspect of 3D detection,the technical route based on LiDAR point cloud,stereo vision and multi-sensor fusion is described,and the advantages and disadvantages of different sensor combinations in geometric reconstruction and dynamic tracking are analyzed.By combining commonly used datasets and evaluation metrics,a standardized reference basis is provided for the standardized testing of algorithm performance.Analysis shows that multimodal data fusion and lightweight network design can effectively improve the stability of lane detection systems in complex scenarios such as occlusion and sudden changes in lighting,while 3D detection technology further enhances positioning accuracy by introducing spatial geometric information.Future research should focus on the construction of a universal modeling framework,innovation in multimodal complementary fusion mechanisms,enhancement of temporal reasoning capabilities in dynamic scenarios,and efficient and lightweight deployment of embedded platforms to promote the practical application of autonomous driving technology.关键词
车道线检测/环境感知/深度学习/多模态融合/自动驾驶系统Key words
lane line detection/environmental perception/deep learning/multimodal fusion/autonomous driving system分类
信息技术与安全科学引用本文复制引用
黄德启,郭亚楠,倪自聪..深度学习在车道线检测中的应用综述[J].计算机科学与探索,2026,20(6):1545-1561,17.基金项目
国家自然科学基金(51468062) （51468062）
新疆维吾尔自治区自然科学基金(2022D01C430). This work was supported by the National Natural Science Foundation of China(51468062),and the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01C430). （2022D01C430）
