Evaluating driving fatigue detection algorithms using eye tracking glasses

Abstract

Fatigue is a status of human brain activities, and driving fatigue detection is a topic of great interest all over the world. In this paper, we propose a measure of fatigue produced by eye tracking glasses, and use it as the ground truth to evaluate driving fatigue detection algorithms. Particularly, PERCLOS, which is the percentage of eye closure over the pupil over time, was calculated from eyelid movement data provided by eye tracking glasses. Experiments of a vigilance task were carried out in which both EOG signals and eyelid movement were recorded. The evaluation results of an effective EOG-based fatigue detection algorithm convinced us that our proposed measure is an appropriate candidate for evaluating driving fatigue detection algorithms.