Alec Brookens and Bijay Panta, “Navigating Precision: A Comparative Analysis of Guided Walking Techniques in Virtual Reality”
Mentor: Jerald Thomas, Computer Science
Poster #34
The consistency of walking speed among participants in Virtual Reality (VR) studies is often challenging to maintain, introducing unwanted variability that can impact study outcomes. Some studies use “guided walking” techniques to control users’ walking speeds, which use visual or auditory stimuli to prompt the user to walk at the desired speed, or in a desired direction. Studies use different techniques to do this, but none of these techniques have been verified to work effectively, nor has one been proven to work better than another. This study aims to evaluate the effectiveness of various guided walking techniques, and compare their results. By testing different guided walking techniques, this study seeks to identify the strategy that can either eliminate or predictably control these extraneous variables, thereby enhancing the reliability of further VR research findings. Utilizing a Finite State Machine developed in C#, this study employs a controlled experimental design within a Unity environment to systematically assess four guided walking techniques: static sphere, dynamic sphere, static metronome, and dynamic metronome. Participants will navigate through three distinct walking path shapes—square, circle, and figure-eight—across three trials for each of the four techniques, allowing for a comprehensive comparison. It is expected the dynamic methods will yield better results, but at the cost of increased cognitive load on the user. Therefore, the anticipated outcome is that the static sphere or static metronome will be the best methods of guided walking, due to their simplicity. This study not only addresses a significant gap in VR research methodology but also sets the stage for future studies by establishing a more controlled and predictable experimental environment.