Drivers' Ability to Engage in a Non-Driving Related Task While in Automated Driving Mode in Real Traffic
Journal article, 2020

Engaging in non-driving related tasks (NDRTs) while driving can be considered distracting and safety detrimental. However, with the introduction of highly automated driving systems that relieve drivers from driving, more NDRTs will be feasible. In fact, many car manufacturers emphasize that one of the main advantages with automated cars is that it "frees up time" for other activities while on the move. This paper investigates how well drivers are able to engage in an NDRT while in automated driving mode (i.e., SAE Level 4) in real traffic, via a Wizard of Oz platform. The NDRT was designed to be visually and cognitively demanding and require manual interaction. The results show that the drivers' attention to a great extent shifted from the road ahead towards the NDRT. Participants could perform the NDRT equally well as when in an office (e.g. correct answers, time to completion), showing that the performance did not deteriorate when in the automated vehicle. Yet, many participants indicated that they noted and reacted to environmental changes and sudden changes in vehicle motion. Participants were also surprised by their own ability to, with ease, disconnect from driving. The presented study extends previous research by identifying that drivers to a high extent are able to engage in a NDRT while in automated mode in real traffic. This is promising for future of automated cars ability to "free up time" and enable drivers to engage in non-driving related activities.



driver behavior

non-driving related task


Automated driving



driver experience

secondary task


Task analysis


Maria Klingegard

Folksam försäkringar

RISE Research Institutes of Sweden

Jonas Andersson

RISE Research Institutes of Sweden

Azra Habibovic

RISE Research Institutes of Sweden

Emma Nilsson

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Annie Rydstrom

Volvo Cars

IEEE Access

2169-3536 (ISSN)

Vol. 8 221654-221668

Subject Categories

Infrastructure Engineering

Applied Psychology

Vehicle Engineering



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