Using Human–Machine Interfaces to Convey Feedback in Automated Driving

The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active,...

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Bibliographic Details
Published in:	Journal of cognitive engineering and decision making Vol. 16; no. 1; pp. 29 - 42
Main Authors:	Shull, Emily M., Gaspar, John G., McGehee, Daniel V., Schmitt, Rose
Format:	Journal Article
Language:	English
Published:	Los Angeles, CA SAGE Publications 01-03-2022
Online Access:	Get full text
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Summary:	The next decade will see a rapid increase in the prevalence of partial vehicle automation, specifically conditional automation (i.e., SAE level 3; SAE, 2018). In conditional automation, the expectation is that the user is still receptive to takeover and can disengage while the automation is active, but as the automation approaches its operational limits, or the end of its operational design domain, it issues a request to intervene and the user is expected to retake control. A human–machine interface (HMI) that can safely and effectively transition control is therefore very important. This simulator study investigated how features of the HMI design, specifically feedback about the confidence (i.e., current capability) of the automation influenced transition of control. Participants were assigned to one of three conditions, which received varying amounts of visual and auditory feedback regarding the automation’s confidence. Findings suggest 3-stage auditory-visual feedback about the automation’s confidence may improve subsequent takeover performance compared to 3-stage visual and a control group without feedback. This research demonstrates the potential value of providing more insight into automated feature performance in conditional automation.
ISSN:	1555-3434 2169-5032
DOI:	10.1177/15553434221076827