Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

RideVR: Reducing Sickness for In-Car Virtual Reality by Mixed-in Presentation of Motion Flow Informationopen access

Authors
Cho, Hyung-JunKim, Gerard J.
Issue Date
2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Visualization; Automobiles; Vehicle dynamics; Dynamics; Virtual reality; Roads; Navigation; Virtual reality; motion sickness; simulation sickness; vection; navigation; distortion
Citation
IEEE ACCESS, v.10, pp.34003 - 34011
Indexed
SCIE
SCOPUS
Journal Title
IEEE ACCESS
Volume
10
Start Page
34003
End Page
34011
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/142145
DOI
10.1109/ACCESS.2022.3162221
ISSN
2169-3536
Abstract
Humans spend a significant portion of their daily life in cars. In this study, we investigate a method to reduce motion sickness and allow people to use virtual reality (VR) while riding in cars. As the sickness arises primarily from the sensory conflict between visual and actual (or vestibular) motions, the proposed approach attempts to resolve the mismatch by mixing in and visualizing the estimated information of the actual motion, which is sensed by the on-board diagnostics and inertial measurement unit modules attached to the vehicle. We conduct a pilot experiment to validate our approach by comparing the sickness levels before and after implementing the approach in three in-car VR usage conditions: (1) Default - using the VR content without modification; (2) transparent wall - using the VR content with its background scene changing depending on the car motion; (3) particle flow - mixing in the VR content with the estimated motion flow of the car visualized as moving particles. Our experimental results show that motion sickness is reduced significantly (but not eliminated to a negligible level) using our approach.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Altmetrics

Total Views & Downloads

BROWSE