Abstract
The “drivenger” aim of the current study was to investigate attentional differentiation of drivers (who are in control) from passengers (who have no control) to inform future driver-in-the-loop monitoring/detection systems and facilitate multiple levels of manual/automated driving. Eye-tracking glasses were worn simultaneously by the driver and front seat passenger on 32 on road trips. Halfway en-route, the passenger was tasked with pretending with their eyes to be driving. Converging with a recent and independent drivenger study, our results found differences of higher probabilities of small saccades and significantly shorter blinks from our drivers and pseudo-drivers. Additionally, a new measure of eye eccentricity differentiated between driver/passenger roles. While naturalistic attentional manipulations may not be appropriately safe/available with actual automated vehicles, future studies might aim to further use the eye behavior of passengers to refine robust measures of driver (in)attention with increasing reductions in measurement intrusiveness and data filtering/processing overhead requirements.
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Acknowledgments
The authors are supported by and performed the current work under the Marie Curie ITN: HF Auto, Human Factors of Automated Driving (PITN-GA-2013605817), www.hf-auto.eu. We would like to thank Dr. Magnus Hjalmdahl for inspiration towards simultaneous eye tracking of driver vs. passenger while driving across Sweden between VTI office while playing with one of the eye tracking glasses used in the present study. Additionally, we are also indebted to Peter van Leeuwen for his insights into the potential value of driver visual eccentricity behavior, specifically regarding both time and distances away from center taken jointly together.
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Cabrall, C.D.D., Petrovych, V., Happee, R. (2018). Looking at Drivers and Passengers to Inform Automated Driver State Monitoring of In and Out of the Loop. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2017. Advances in Intelligent Systems and Computing, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-60441-1_67
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