Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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Study on the Variation of Driver's Biosignals According to the Color Temperature of Vehicle Interior Mood Lighting

자동차 실내 무드조명의 색온도에 따른 운전자의 생체신호 변화

  • 김규범 (한밭대학교 산업경영공학과) ;
  • 조형석 (한밭대학교 산업경영공학과) ;
  • 김영중 (한밭대학교 산업경영공학과) ;
  • 민병찬 (한밭대학교 산업경영공학과)
  • Received : 2019.12.30
  • Accepted : 2020.03.16
  • Published : 2020.06.30
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Abstract

The purpose of this work is to suggest the optimal color temperature, which induces a sense of comfort for autonomous vehicle users through the analysis of biosignal using electroencephalography (EEG) and photoplethysmography (PPG). To achieve this purpose, we applied lighting with a color temperature of 3000 K, 4000 K, 5000 K, and 6000 K to the autonomous driving environment. We experimented in a laboratory equipped with a graphic driving simulator. The experimental procedure is as follows: 1) stabilization (5 min). 2) Uchida-Kraepelin test (3 min). 3) Automatic driving + lighting (3 min). This procedure was repeated four times under different color temperatures. We performed frequency analysis on a collected time-series data and calculated the power value for each frequency band through power spectrum analysis. In the case of EEG, we analyzed α- and β-waves, which are indicators of stability and arousal, respectively. In the case of PPG, we analyzed the sympathetic nervous system activity. To reduce deviations between the subjects, we normalized the data before analysis. The result of the first analysis revealed that α-wave increased only at 5000 K, while the β-wave increased at almost all color temperatures. In addition, in the case of PPG, sympathetic nervous system activity (SNSA) increased under driving conditions. The result of the second analysis revealed that the difference between β-wave and SNSA is insignificant. In conclusion, the increase in α-waves showed that EEG was most stable at 5000 K. The results of this study can be applied to the upcoming autonomous driving era to induce high driver satisfaction. Furthermore, this approach could eventually lead to the acceptance of autonomous vehicles by suggesting a positive effect of autonomous driving.

본 연구에서는 뇌파와 맥파를 이용한 생체신호 분석을 통해 자율주행차량 사용자에게 안정감을 유발하는 최적의 색온도를 제안하고자 하였다. 이를 위해 3000 K, 4000 K, 5000 K, 6000 K의 색온도를 갖는 조명을 자율주행 환경에 적용하여 제시하였다. 실험은 자동차 그래픽 시뮬레이터가 구비된 실험실에서 진행되었으며, 실험절차는 다음과 같다. 1) 안정기(5분), 2) U-K테스트(3분), 3) 자율주행+조명(3분). 이 과정은 색온도를 변경해가며 총 4회 반복되었다. 수집된 시계열데이터에 대해 주파수 분석을 실시하였고 파워 스펙트럼 분석을 통해 주파수 대역별 power값을 산출하였다. 뇌파는 안정의 지표인 α파와 각성의 지표인 β에 대해 분석을 실시하였으며, 맥파의 경우 교감신경계 활성도에 대해 분석을 실시하였다. 산출된 데이터는 연구대상자 개인 간 편차를 줄이기 위해 정규화하여 통계분석을 실시하였다. 1차 분석 결과, 뇌파의 경우 5000 K의 조명을 제시하였을 때 α파가 가장 높았고, 대부분의 조명 제시 상황에서 β파가 증가하였다. 맥파의 경우 주행 상황에서 SNSA가 증가하였다. β파와 SNSA에 대한 2차 분석 결과, 유의수준 5%에서 색온도 간 유의한 차이가 인정되지 않았다. 결론적으로, α파가 가장 높은 5000 K의 색온도가 안정감을 유발한다고 볼 수 있다. 이러한 결과를 자율주행차량에 적용한다면, 탑승자의 높은 만족도를 유발할 수 있을 것으로 보인다. 나아가, 이와 같은 긍정적인 효과가 자율주행차량의 수용으로 이어질 수 있다.

Keywords

References

  1. Chang, J. H. (2008). A study on appropriate corrected color temperature and colors of LEDs for specific spaces and users. (Master's thesis). Sejong University, Seoul, Republic of Korea. Retrieved from http://www.riss.kr/
  2. Chang, J. H., Lee, S. J., Park, B. C., & Choi, A. S. (2007). A study on appropriate correlated color temperature (CCT) for each space by subjective evaluation. In Proceeding of 2007 Conference of Architectural Institute of Korea, 985-988.
  3. DongA. (2019). http://www.donga.com/news/article/all/20190924/97571279/1
  4. Hur, M. R., & Lee, A. R. (2016). Study on the relationship between EEG of brain laterality and personality traits. Science of Emotion & Sensibility, 19(1), 83-94. DOI: 10.14695/KJSOS.2016.19.1.83
  5. Im, I. J., Lee, C. K., & Hwang, K. Y. (2016). Legal issues related with autonomous vehicle operation. Journal of Korea Transport Institute, 23(3), 75-91. DOI: 10.34143/jtr.2016.23.3.75
  6. Jee, S. D., & Kim, C. B. (2014). Electroencephalogram analysis on learning factors during relaxed or concentrated attention according to the color temperatures of LED illuminance. Journal of Korean Institute of Educational Facilities, 21(6), 33-42. DOI: 10.7859/kief.2014.21.6.033
  7. Kim, B. S. (2010). Effects of training to improve visual and spatial working memory skills on driving behaviors of elderly drivers: Integrative research of driving performance, eye movements, and physiological changes. (Doctoral dissertation). Chungnam National University, Daejeon, Republic of Korea. Retrieved from http://www.riss.kr/
  8. Kim, H. C., Jeong, W. S., Lee, K. H., & Nam, K. C. (2015). Development of a photoplethysmographic method using a CMOS image sensor for smartphone. Journal of the Korea Academia-Industrial cooperation Society, 16(6), 4021-4030. DOI: 10.5762/KAIS.2015.16.6.4021
  9. Kim, H. J. (2019). Exploration of the solution of cyber sickness symptoms through listening to music: Focused on using vr head set devices. (Master's thesis). Hanbat National University, Daejeon, Republic of Korea. Retrieved from http://www.riss.kr/
  10. Kim, J. M., & Kim, M. S. (2009). Change of sensitivity perception subsequent to the difference in color temperature of light in the image. Journal of Korea Design Knowledge, 10, 102-111. DOI: 10.17246/jkdk.2009.10.010010
  11. Kim, K. B., Jo, H. S., & Min, B. C. (2019). The effect of indoor mood lighting in autonomous vehicle environments. In Proceeding of 2019 Spring Conference of Korean Society for Emotion & Sensibility, 37-38.
  12. Kim, S. H., Kim, J. P., & Lim, J. H. (2011). Effects of color (light) environment of art therapy space on nurie coloring and emotional change for university students. Journal of Korean Art Therapy Association, 18(6), 1259-1278. DOI: 10.35594/kata.2011.18.6.005
  13. Kim, Y. J., Ji, D. H., Ryu, Y. J., Kim, S. H., Seo, S. H., Kwak, S. H., Kang, J. K., & Min, B. C. (2017). Effect of color and color temperature on the attention in the residential space by the analysis of EEG and ECG. Journal of the Society of Korea Industrial and Systems Engineering, 40(1), 124-130.
  14. KPMG. (2019). 2019 Autonomous vehicles readiness index.
  15. Lee, B. Y. (2016). Trend and prospect of autonomous vehicle technology development in domestic & overseas(국내외 자율주행자동차 기술개발 동향과 전망). Journal of The Korean Institute of Communication Sciences, 33(4), 10-16.
  16. Lee, J. H., Chang, H. S., & Park, Y. I. (2018). Influencing factors on social acceptance of autonomous vehicles and policy implications. Journal of Korea Technology Innovation Society, 21(2), 715-737.
  17. Lee, J. H. (2000). Design of heart rate variability signal time-frequency analysis system for the assessment of autonomic nervous system activities. (Doctoral dissertation). Yonsei University, Seoul, Republic of Korea. Retrieved from http://www.riss.kr/
  18. Lee, J. H. (2018). A comparative analysis of factors affecting acceptance by type of autonomous vehicle and policy implications. (Doctoral dissertation). Ewha Womans University, Seoul, Republic of Korea. Retrieved from http://www.riss.kr/
  19. Lee, J. S., & Lee, H. W. (2015). A study on influence of the stress in a color temperature and controllable illuminance environment on human body. Journal of Korea Society of Color Studies, 29(2), 125-134. DOI: 10.17289/jkscs.29.2.201505.125
  20. Park, H. S., & Lee, C. S. (2018). Psychophysiological responses of passengers to the illuminance and color temperature of lighting for different in-vehicle activities. Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 32(1), 9-16. https://doi.org/10.5207/JIEIE.2018.32.1.009
  21. Park, J. S., Kim, K. B., Jo, H. S., Kim, G. R., Kim, H. J., & Min, B. C. (2019). The ability of auditory stimuli to mask siren sounds in a vehicle graphic simulator. Science of Emotion & Sensibility, 22(3), 47-54. DOI: 10.14695/KJSOS.2018.22.3.47
  22. Park, K. J., & Jung, H. J. (2014). Assessing methods of heart rate variability. Korean Journal of Clinical Neurophysiology, 16(2), 49-54. DOI: 10.14253/kjcn.2014.16.2.49
  23. Seoul Finance. (2018). http://www.seoulfn.com/news/articleView.html?idxno=311953
  24. Shin, J. Y., Park, H. S., & Lee, C. S. (2015). Effects of color temperature change of LED lighting in vehicle on passengers' bio-signals. In Proceeding of 2015 KSCS Spring Conference, 79-80.
  25. Shin, J. Y., Chun, S. Y., & Lee, C. S. (2013). Analysis of the effect on attention and relaxation level by correlated color temperature and illuminance of LED lighting using EEG signal. Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 27(5), 9-17. DOI: 10.5207/JIEIE.2013.27.5.009