Keeping Eyes on the Road: Understanding Driver Attention and Its Role in Safe Driving

Monitoring the driver’s attention is an important task to maintain the driver’s safety. The estimation of the driver’s gaze direction can help us to evaluate if the drivers are not focusing their attention on the street. For an evaluation of this type, comparing the inside view and outside scenery of the vehicle is essential, therefore we decided to create a specific dataset for this task. In this work, we realize a machine-learning-oriented approach to driver’s attention evaluation using a coupled visual perception system. By analyzing the road and the driver’s gaze simultaneously it is possible to understand if the driver is looking at the traffic signs detected. We evaluate if a determined Region Of Interest (ROI) contains a road sign or not through YOLOv8.