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Journal of Advanced Transportation
Volume 2017 (2017), Article ID 6105087, 12 pages
Research Article

Improving Usefulness of Automated Driving by Lowering Primary Task Interference through HMI Design

1Center for Traffic Sciences (IZVW), University of Würzburg, Würzburg, Germany
2Würzburg Institute for Traffic Sciences (WIVW), Veitshöchheim, Germany

Correspondence should be addressed to Frederik Naujoks; ed.wviw@skojuan

Received 13 April 2017; Revised 4 June 2017; Accepted 28 June 2017; Published 16 August 2017

Academic Editor: David F. Llorca

Copyright © 2017 Frederik Naujoks et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


During conditionally automated driving (CAD), driving time can be used for non-driving-related tasks (NDRTs). To increase safety and comfort of an automated ride, upcoming automated manoeuvres such as lane changes or speed adaptations may be communicated to the driver. However, as the driver’s primary task consists of performing NDRTs, they might prefer to be informed in a nondistracting way. In this paper, the potential of using speech output to improve human-automation interaction is explored. A sample of 17 participants completed different situations which involved communication between the automation and the driver in a motion-based driving simulator. The Human-Machine Interface (HMI) of the automated driving system consisted of a visual-auditory HMI with either generic auditory feedback (i.e., standard information tones) or additional speech output. The drivers were asked to perform a common NDRT during the drive. Compared to generic auditory output, communicating upcoming automated manoeuvres additionally by speech led to a decrease in self-reported visual workload and decreased monitoring of the visual HMI. However, interruptions of the NDRT were not affected by additional speech output. Participants clearly favoured the HMI with additional speech-based output, demonstrating the potential of speech to enhance usefulness and acceptance of automated vehicles.