4.7 Article

A Lack of Restraint: Comparing Virtual Reality Interaction Techniques for Constrained Transport Seating

Journal

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2023.3247084

Keywords

Virtual Reality; Interaction; Constrained Spaces; Transport

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Standalone VR headsets can be used in transportation, but the limited physical space and movement constraints pose challenges for users. This study investigates three at-a-distance interaction techniques to improve the interaction capabilities of VR users in confined spaces. The linear gain technique was found to be the most effective, providing similar performance and user experience to unconstrained conditions, despite some boundary violations and arm movements. AlphaCursor, on the other hand, kept users within limits but had poorer performance and experience. Eight guidelines for using and researching at-a-distance techniques in constrained spaces are provided based on the findings.
Standalone Virtual Reality (VR) headsets can be used when travelling in cars, trains and planes. However, the constrained spaces around transport seating can leave users with little physical space in which to interact using their hands or controllers, and can increase the risk of invading other passengers' personal space or hitting nearby objects and surfaces. This hinders transport VR users from using most commercial VR applications, which are designed for unobstructed 1-2m 360 degrees home spaces. In this paper, we investigated whether three at-a-distance interaction techniques from the literature could be adapted to support common commercial VR movement inputs and so equalise the interaction capabilities of at-home and on-transport users: Linear Gain, Gaze-Supported Remote Hand, and AlphaCursor. First, we analysed commercial VR experiences to identify the most common movement inputs so that we could create gamified tasks based on them. We then investigated how well each technique could support these inputs from a constrained 50x50cm space (representative of an economy plane seat) through a user study (N=16), where participants played all three games with each technique. We measured task performance, unsafe movements (play boundary violations, total arm movement) and subjective experience and compared results to a control 'at-home' condition (with unconstrained movement) to determine how similar performance and experience were. Results showed that Linear Gain was the best technique, with similar performance and user experience to the 'at-home' condition, albeit at the expense of a high number of boundary violations and large arm movements. In contrast, AlphaCursor kept users within bounds and minimised arm movement, but suffered from poorer performance and experience. Based on the results, we provide eight guidelines for the use of, and research into, at-a-distance techniques and constrained spaces.

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