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. |
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Key Words |
Autonomous Vehicle, EEG, PPG, Color Temperature, Interior Lighting, 자율주행자동차, 뇌파, 맥파, 색온도, 실내조명 |
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