Virtual Reality consumer hardware is now available for the masses through the HTC Vive, Oculus Rift and PlayStation VR. Locomotion or virtual travel inside immersive experiences is an area which is yet to be fully solved due to space constraints, problems with retaining immersion and potential sickness. This thesis had the goal of evaluating user preferences for four locomotion methods in Virtual Reality with a first generation HTC Vive through the gaming platform Steam. The theoretical framework provides an elementary understanding of the field of Virtual Reality and how humans interact and get affected by locomotion in that context. To contextualize the experience of evaluating the locomotion systems the Hedonic-Motivation System Adoption Model is used as it covers intrinsic motivation which is common in video games, social networking and virtual worlds. An extensive process for games selection has been performed which has resulted in four locomotion methods with four games per method. Sixteen participants got to test one locomotion method each where their gameplay got recorded for later observation. After each game session answers were provided by the participants based on surveys and after completion of all games a questionnaire gauged their sickness level. The conclusion proved inconclusive. While the results without interpretation showed the locomotion method Artificial as the overall winner a range of potential problems were found with the study in general. Some problems included observations which did not provide the expected results, introducing doubt into either how the study was conducted or the reliability of certain users. A larger sampler size along with a better study procedure could possibly have provided a more conclusive answer.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hv-11651 |
| Date | January 2017 |
| Creators | Karlsson, Rasmus, Sveninge, Alvar |
| Publisher | Högskolan Väst, Avd för informatik, Högskolan Väst, Avd för informatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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