This Master Thesis was conducted in the Industrial Design Engineering program at theChalmers University of Technology in collaboration with RISE and Volvo Cars. The aimwas to investigate the difference in driving performance between a traditional mirror, CameraMonitoring System (CMS), and CMS with augmented reality information (AR). It wasfurthermore to develop guidelines for applying this knowledge when designing CMS forincreased user performance in cars. Literature studies, expert interviews, workshops, anduser tests were used to discover this knowledge.The user test was conducted in a virtual environment, with four driving scenarios definedfor testing. The scenes and animations for the test were built in Unity, and the test wasconducted in a simulated driving environment with VR-rig. Four categories of data werecollected in the test. Twenty-one participants from Volvo Cars completed the test and providedrelevant feedback on the design of CMS & AR.The user test results revealed that the participants’ driving performance using CMS (withoutaugmented information) did not improve over traditional mirrors. Most participantsindicated that they would only upgrade from a traditional mirror to a CMS car with AR,rather than just a CMS car, as CMS did not provide enough benefit over traditional mirrors.The paper also discussed possible reasons behind this finding.The feedback and suggestions from the participants on the design of CMS & AR obtainedthrough questionnaires and interviews are organized into a guideline on the design ofCMS & AR. In addition, this paper gave recommendations for future study.Finally, this paper also discussed the challenges and experiences encountered in this study.Among them, the limitation of doing tests in a VR environment is highlighted to helpfuture CMS research and testing. / Safe Car Driving with Head Up Displays andCamera Monitor Systems: (SCREENS) (Vinnova Dnr: 2020-05129)
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ri-61469 |
Date | January 2022 |
Creators | Zhang, Miao, Bin, Gao |
Publisher | RISE Research Institutes of Sweden, Chalmers University of Technology, Chalmers University of Technology |
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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