Location

Big Sky, Montana

Date

23-6-2009

Session

Session 1 – Lectures Driver Distraction & Fatigue

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.

Rights

Copyright © 2009 the author(s)

DC Citation

Proceedings of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, June 22-25, 2009, Big Sky, Montana. Iowa City, IA: Public Policy Center, University of Iowa, 2009: 16-23.

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Jun 23rd, 12:00 AM

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

Big Sky, Montana

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.