Looking at Drivers and Passengers to Inform Automated Driver State Monitoring of In and Out of the Loop

  • Christopher D. D. Cabrall
  • Veronika Petrovych
  • Riender Happee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 597)

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.

Keywords

Human-systems integration Driver state monitoring Eye-tracking Passenger Driver Drivenger Automated driving 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Christopher D. D. Cabrall
    • 1
  • Veronika Petrovych
    • 2
  • Riender Happee
    • 1
  1. 1.Intelligent Vehicles, Department of Cognitive RoboticsDelft University of TechnologyDelftThe Netherlands
  2. 2.Driver and Vehicle, Department of Computer and Information Science (IDA), Swedish National Road and Transport Research Institute (VTI)Linkoping UniversityLinkopingSweden

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