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Takeover Requests in Highly Automated Truck Driving: How Do the Amount and Type of Additional Information Influence the Driver–Automation Interaction?

1
Chair of Automotive Technology, Technical University of Munich, Garching b., 85748 München, Gremany
2
MAN Truck & Bus AG, 80995 München, Germany
*
Author to whom correspondence should be addressed.
Multimodal Technol. Interact. 2018, 2(4), 68; https://doi.org/10.3390/mti2040068
Received: 1 August 2018 / Revised: 10 September 2018 / Accepted: 28 September 2018 / Published: 4 October 2018
(This article belongs to the Special Issue Automotive User Interfaces)
Vehicle automation is linked to various benefits, such as increase in fuel and transport efficiency as well as increase in driving comfort. However, automation also comes with a variety of possible downsides, e.g., loss of situational awareness, loss of skills, and inappropriate trust levels regarding system functionality. Drawbacks differ at different automation levels. As highly automated driving (HAD, level 3) requires the driver to take over the driving task in critical situations within a limited period of time, the need for an appropriate human–machine interface (HMI) arises. To foster adequate and efficient human–machine interaction, this contribution presents a user-centered, iterative approach for HMI evaluation of highly automated truck driving. For HMI evaluation, a driving simulator study [n = 32] using a dynamic truck driving simulator was conducted to let users experience the HMI in a semi-real driving context. Participants rated three HMI concepts, differing in their informational content for HAD regarding acceptance, workload, user experience, and controllability. Results showed that all three HMI concepts achieved good to very good results in these measures. Overall, HMI concepts offering more information to the driver about the HAD system showed significantly higher ratings, depicting the positive effect of additional information on the driver–automation interaction. View Full-Text
Keywords: human–machine interface; highly automated truck driving; driving simulator study; acceptance; user experience; controllability; takeover human–machine interface; highly automated truck driving; driving simulator study; acceptance; user experience; controllability; takeover
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Richardson, N.T.; Flohr, L.; Michel, B. Takeover Requests in Highly Automated Truck Driving: How Do the Amount and Type of Additional Information Influence the Driver–Automation Interaction? Multimodal Technol. Interact. 2018, 2, 68.

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