Enhancing Lane Detection Performance A Comprehensive Analysis of YOLOPv2 under Adverse Conditions

With the growing global interest in autonomous driving from big car companies and the research community, road lane detection has become a hot topic. In this paper, You Only Look Once for Panoptic Driving (YOLOPv2), which is a deep learning network that is designed to perform multitasks including lane detection, is studied and evaluated using three challenging datasets. The authors also collected a DubaiLanes dataset which consists of 70 images under various conditions. The YOLOPv2 model was evaluated using Pixel Accuracy, MSE, IoU, and F1-score. The model was found to perform well with different lighting conditions, multiple lanes, and different curves. However, it was also found that it misdetects tiny speed bumps for lanes and does not create continuous lanes when obstacles are observed.