In the research of autonomous driving,automatic detection of road traffic targets is one of the most critical technolo-gies.However,current detection algorithms have situations such as missed and false detections,which seriously endanger road traffic safety.Therefore,on the basis of deep learning,a false detection module is added and the loss function of the detection algorithm is improved to improve the detection accuracy.The improved method achieved an average accuracy of 97.34％,87.24％,and 80.23％in three difficulty tests,which increased by 2.61％,3.01％,and 3.89％compared to before the improvement,and was superior to the currently more advanced Faster R-CNN,Grid R-CNN,and FreeAnchor algorithms.In actual scenario testing,the improved al-gorithm effectively reduces the occurrence of false positives on rainy days and nights.The experimental results validate the effective-ness of this study and provide valuable reference for automated detection of road traffic targets.
关键词
自动驾驶/道路交通/误检模块/损失函数
Key words
autonomous driving/road traffic/misinspection module/loss function
维普
万方数据