Comparison of Two Eye-Gaze Based Real-Time Driver Distraction Detection Algorithms in a Small-Scale Field Operational Test

Abstract

Driver distraction is a field which has received increasing attention in the last years, especially after it became evident that distraction is a major factor contributing to road casualties. Monitoring, detecting and limiting driver distraction could contribute significantly to improve road traffic safety. With the introduction of novel unobtrusive gaze-tracking systems real-time algorithms based on the driver’s gaze direction can be developed for driver distraction warning systems. The study describes and compares two different algorithms for gaze-based driver distraction detection based on the eye tracking data obtained in a field study. One algorithm relies on the metric “percent road centre” of gaze direction, the other on gaze zones in the vehicle. Results show that both algorithms have potential for detecting driver distraction, but that no effect of the distraction warnings on attention as defined by the algorithms could be observed.

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