Date of Award

2023

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Computer Science (PhD)

Administrative Home Department

Department of Computer Science

Advisor 1

Scott Kuhl

Committee Member 1

Robert Pastel

Committee Member 2

Keith Vertanen

Committee Member 3

Ricardo Eiris Pereira

Abstract

While individuals can accurately estimate distances in the real world, this ability is often diminished in virtual reality (VR) simulations, hampering performance across training, entertainment, prototyping, and education domains. To assess distance judgments, the direct blind walking method—having participants walk blindfolded to targets—is frequently used. Typically, direct blind walking measurements are performed after an initial practice phase, where people become comfortable with walking while blindfolded. Surprisingly, little research has explored how such pre-experiment walking impacts subsequent VR distance judgments. Our initial investigation revealed increased pre-experiment blind walking reduced distance underestimations, underscoring the importance of detailing these preparatory procedures in research—details often overlooked. In a follow-up study, we found that eyes-open walking prior to pre-experiment blind walking did not influence results, while extensive pre-experiment blind walking led to overestimation. Additionally, see-through walking had a slightly greater impact and less underestimation compared to one loop of pre-experiment blind walking. Our comprehensive research deepens our understanding of how pre-experiment methodologies influence distance judgments in VR, guides future research protocols, and elucidates the mechanics of distance estimation within virtual reality.

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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