Virtual reality (VR) is a simulation tool that is being used extensively to study the effects of training and perception. However, several studies have shown that some aspects of perception within VR are not always accurate. The present study investigates the perception of time within a VR environment by asking for retrospective time judgments of the length of VR experiences. These environments varied in both the level of interaction with the VR environment, and also the spatial properties of the environment itself. The judged length of time did not significantly differ between conditions based on the level of activity in the environment. However, the spatial properties of the VR environment did produce significantly different time estimations. This finding suggests that careful attention should be paid to what and how users are trained or evaluated in VR.
Classic research in perception has suggested that visual context can impact how individuals perceive object characteristics like physical size. The current set of studies extends this work to an applied setting by examining whether smartphone display size can impact the perception of objects presented on smartphones. Participants viewed several target items, on two different sized virtual device displays based on actual consumer devices and were asked to make simple judgments of the size of presented objects. Results from both experiments confirm that display size impacts perceived size, such that larger displays cause users to significantly underestimate the size of objects moreso than smaller displays. This is the first study to confirm such an effect, and suggests that beyond aesthetics or cost, one’s personal choice of device might have additional performance consequences.
The characteristics that a supervisor of multiple autonomous and semi-autonomous systems should possess remain unclear. Determination of these qualities would support job performance as well as recruiting and training. To evaluate the human characteristics currently being considered by human-in-the-loop experiments, a review of the multiple remote vehicle supervision literature was conducted. The human characteristics addressed included: gender, domain relevant experience, working memory, supervisory relevant skills and abilities (e.g., visual skills, spatial ability, attentional control, vigilance), and traits related to multi-tasking (e.g., stress, resilience). The discussion identifies gaps in the current state of the art with respect to the consideration of human characteristics for multi-autonomous and semi-autonomous systems supervision where at least one vehicle is an aircraft.
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