Title
Rolling out the red (and green) carpet: Supporting driver decision making in automation-to-manual transitions
Author
Eriksson, Alexander (University of Southampton)
Petermeijer, S.M. (Technische Universität München)
Zimmermann, Markus (Technische Universität München)
de Winter, J.C.F. (TU Delft Human-Robot Interaction)
Bengler, Klaus J. (Technische Universität München)
Stanton, Neville A. (University of Southampton)
Date
2019
Abstract
This paper assessed four types of human–machine interfaces (HMIs), classified according to the stages of automation proposed by Parasuraman et al. [“A model for types and levels of human interaction with automation,” IEEE Trans. Syst. Man, Cybern. A, Syst. Humans, vol. 30, no. 3, pp. 286–297, May 2000]. We hypothesized that drivers would implement decisions (lane changing or braking) faster and more correctly when receiving support at a higher automation stage during transitions from conditionally automated driving to manual driving. In total, 25 participants with a mean age of 25.7 years (range 19–36 years) drove four trials in a driving simulator, experiencing four HMIs having the following different stages of automation: baseline (information acquisition—low), sphere (information acquisition—high), carpet (information analysis), and arrow (decision selection), presented as visual overlays on the surroundings. The HMIs provided information during two scenarios, namely a lane change and a braking scenario. Results showed that the HMIs did not significantly affect the drivers’ initial reaction to the take-over request. Improvements were found, however, in the decision-making process: When drivers experienced the carpet or arrow interface, an improvement in correct decisions (i.e., to brake or change lane) occurred. It is concluded that visual HMIs can assist drivers in making a correct braking or lane change maneuver in a take-over scenario. Future research could be directed toward misuse, disuse, errors of omission, and errors of commission.
Subject
Augmented reality
automated driving
driver support systems
human factors
human performance
transitions of control
To reference this document use:
http://resolver.tudelft.nl/uuid:65abe2ad-68af-4ebf-865c-e31feff909b2
DOI
https://doi.org/10.1109/THMS.2018.2883862
Embargo date
2019-06-28
ISSN
2168-2291
Source
IEEE Transactions on Human-Machine Systems, 49 (1), 20-31
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2019 Alexander Eriksson, S.M. Petermeijer, Markus Zimmermann, J.C.F. de Winter, Klaus J. Bengler, Neville A. Stanton