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The International Journal of Robotics Research
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Driver Inattention Detection based on Eye Gaze—Road Event Correlation

Luke Fletcher

Department of Information Engineering, RSISE, Australian National University Canberra, Australia, luke.fletcher{at}anu.edu.au

Alexander Zelinsky

CSIRO ICT Centre, Canberra, Australia, alex.zelinsky{at}csiro.au

Current road safety initiatives are approaching the limit of their effectiveness in developed countries. A paradigm shift is needed to address the preventable deaths of thousands on our roads. Previous systems have focused on one or two aspects of driving: environmental sensing, vehicle dynamics or driver monitoring. Our approach is to consider the driver and the vehicle as part of a combined system, operating within the road environment. A driver assistance system is implemented that is not only responsive to the road environment and the driver's actions but also designed to correlate the driver's eye gaze with road events to determine the driver's observations. Driver observation monitoring enables an immediate in-vehicle system able to detect and act on driver inattentiveness, providing the precious seconds for an inattentive human driver to react. We present a prototype system capable of estimating the driver's observations and detecting driver inattentiveness. Due to the "look but not see" case it is not possible to prove that a road event has been observed by the driver. We show, however, that it is possible to detect missed road events and warn the driver appropriately.

The International Journal of Robotics Research, Vol. 28, No. 6, 774-801 (2009)
DOI: 10.1177/0278364908099459
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