Practical Task-Driven Drivers' Gaze Prediction Using Map and Route Information

Accurate prediction of drivers' gaze is crucial for vision-based driver monitoring and assistive systems, especially during safety-critical episodes such as performing maneuvers or crossing intersections. The proposed SCOUT+ model leverages map and route information inferred from commonly available GPS data to effectively model task and context influences on drivers' attention.