Self-Interruptions of Non-Driving Related Tasks in Automated Vehicles: Mobile vs Head-Up Display
Author(s) -
Michael A. Gerber,
Ronald Schroeter,
Xiaomeng Li,
Mohammed Elhenawy
Publication year - 2020
Publication title -
qut eprints (queensland university of technology)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-6708-0
DOI - 10.1145/3313831.3376751
Subject(s) - interrupt , computer science , task (project management) , head up display , human–computer interaction , interleaving , driving simulator , eye tracking , task analysis , driving simulation , mobile device , simulation , artificial intelligence , embedded system , engineering , world wide web , operating system , systems engineering , microcontroller
Automated driving raises new human factors challenges. There is a paradox that allows drivers to perform non-driving related tasks (NDRTs), while benefiting from a driver who regularly attends to the driving task. Systems that aim to better manage a driver's attention, encouraging task switching and interleaving, may help address this paradox. However, a better understanding of how drivers self-interrupt while engaging in NDRTs is required to inform such systems. This paper presents a counterbalanced within-subject simulator study with N=42 participants experiencing automated driving in a familiar driving environment. Participants chose a TV show to watch on a HUD and mobile display during two 15min drives on the same route. Eye and head tracking data revealed more self-interruptions in the HUD condition, suggesting a higher likelihood of a higher situation awareness. Our results may benefit the design of future attention management systems by informing the visual and temporal integration of the driving and non-driving related task.
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