A Novel Approach to Road Safety: Detecting Illegal Overtaking Using Smartphone Cameras and Deep Learning for Vehicle Auditing

• DOI: 10.3390/jsan14010010
• Publication Date: 2025-01-27T08:54:27Z
• Authors: Karem Daiane Marc...; Vitória de Carval...; Gregori da Cruz B...; Vitor Tosetto; Luiz Carlos Duarte; Antonio Roberto D...
• Keywords: Overtaking; Vehicle safety

Overtaking relies heavily on the driver’s attention and cognitive state, illegal overtaking can lead to accidents, severe injuries, or fatalities. To enhance highway safety, we propose a method for accurately detecting continuous road lanes. We used dashboard-mounted smartphone cameras geolocation data filter analysis areas. state-of-the-art deep learning model You Only Look Once version 8 (YOLOv8) detect yellow When these lanes suggest potential overtaking, apply YOLO Panoptic driving Perception 2 (YOLOPv2) model, followed by post-processing. confirm events checking overlaps between detections from both models. store confirmed instances evaluate information temporally rather than just individual frames. then analyze entire video identify violations extract moments of occurrence. tested algorithm real-world traffic under various weather lighting conditions. Our demonstrates reliability consistency in identifying overtaking. achieved 16 TP only 1 FP over 56 videos totaling 41 h, 9 min, 24 s, with precision, recall, F1-score values 1.000, 0.941, 0.970, respectively. Consequently, our innovative practical solution, utilizing simple advanced computer vision models, significantly safety support vehicle auditing systems.