Stereoscopic 3D dashboards: an investigation of performance, workload, and gaze behavior during take-overs in semi-autonomous driving

Abstract

When operating a conditionally automated vehicle, humans occasionally have to take over control. If the driver is out of the loop, a certain amount of time is necessary to gain situation awareness. This work evaluates the potential of stereoscopic 3D (S3D) dashboards for presenting smart S3D take-over-requests (TORs) to support situation assessment. In a driving simulator study with a 4 × 2 between-within design, we presented 3 smart TORs showing the current traffic situation and a baseline TOR in 2D and S3D to 52 participants doing the n-back task. We further investigate if non-standard locations affect the results. Take-over performance indicates that participants looked at and processed the TORs' visual information and by that, could perform more safe take-overs. S3D warnings in general, as well as warnings appearing at the participants’ focus of attention and warnings at the instrument cluster, performed best. We conclude that visual warnings, presented on an S3D dashboard, can be a valid option to support take-over while not increasing workload. We further discuss participants’ gaze behavior in the context of visual warnings for automotive user interfaces

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