Lane Line Detection Based on Attention Mechanism and Line Anchor Information Transmission
Lane line detection is a key technology in the field of autonomous driving,and it currently faces many challenges.The sparsity of the lane line supervision signal,as well as factors such as occlusion and shadows in complex scenes,can affect detection accuracy and real-time performance.Based on this,this paper proposes a lane line detection model that integrates the CBAM attention mechanism and a line anchor feature aggregation module.The proposed algorithm achieves an accuracy of 96.19％ and a comprehensive F1 score of 76.24％ on the Tusimple and CULane datasets,respectively.Real vehicle tests show that the algorithm detects a frame rate of 67 fps,allowing for real-time detection in complex traffic scenarios and more effectively addressing the problem of lane line occlusion.
lane line detectionline anchorsattention mechanismsinformation delivery
国家科技期刊平台
NSTL
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