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Measuring Driver Perception: Combining Eye-Tracking and Automated Road Scene Perception
Jork Stapel1, Mounir El Hassnaoui1, Riender Happee1
1541087 Delft University of Technology, Netherlands.
Objective:
To investigate how well gaze behavior can indicate driver awareness of individual road users when related to the vehicle's road scene perception.
Background:
An appropriate method is required to identify how driver gaze reveals awareness of other road users.
Method:
We developed a recognition-based method for labeling of driver situation awareness (SA) in a vehicle with road-scene perception and eye tracking. Thirteen drivers performed 91 left turns on complex urban intersections and identified images of encountered road users among distractor images.
Results:
Drivers fixated within 2° for 72.8% of relevant and 27.8% of irrelevant road users and were able to recognize 36.1% of the relevant and 19.4% of irrelevant road users one min after leaving the intersection. Gaze behavior could predict road user relevance but not the outcome of the recognition task. Unexpectedly, 18% of road users observed beyond 10° were recognized.
Conclusions:
Despite suboptimal psychometric properties leading to low recognition rates, our recognition task could identify awareness of individual road users during left turn maneuvers. Perception occurred at gaze angles well beyond 2°, which means that fixation locations are insufficient for awareness monitoring.
Application:
Findings can be used in driver attention and awareness modelling, and design of gaze-based driver support systems.
