Development of Regression Models for Predicting Simulator Sickness in Driving Simulation

자동차 모의운전환경에서 Simulator Sickness의 예측 회귀모형 개발

  • 김도회 (한양대학교 부설 산업과학연구소)
  • Published : 1999.09.01

Abstract

This study proposed multiple linear regression models to predict those who can be easily infected simulator sickness(SS) in simulator or virtual reality environment. In this study, SSQ(Simulator Sickness Questionnaire) scores which are recently used for assessing SS, and RSSQ(Revised Simulator Sickness Questionnaire) scores are selected as dependent variables. Also ten dependent variables are used. The results are these models coefficient of determination(max $R^2=0.52$) is improved 18% more than Kolasinski's model($R^2=0.35$), and it became easy to predict with simple data. Accordingly, we can easily predict who will be apt to get into simulator sickness.

Keywords

References

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