Investigation on driver stress utilizing ECG signals with on-board navigation systems in use

Abstract

People today rely more and more on global positioning system (GPS) for navigation when driving in unfamiliar environments. While GPS navigation is indispensable in an intelligent vehicle and provides convenience for road direction, concerns are also raised if the use of GPS may distract drivers to increase unnecessary stress. In this paper, we explore the effects of using GPS navigation on driver stress utilizing electrocardiogram (ECG) signals. In particular, the effects of higher or lower density of GPS instructions are studied. To analyze the driver stress, eight heart rate variability (HRV) features, which were commonly utilized in human stress related studies, were computed from ECG signals. Statistical significance tests were then performed to each HRV feature, so that those effective features for detecting driver stress may be localized. Our studies, based on road driving experiments with ten healthy subjects, showed that MeanRR, SDNN and HRVTri are the top three effective features to detect driver stress, while frequency domain features in general are not sensitive to driver stress. Based on the effective features, our analysis further showed that basically, driving with higher density of GPS instructions has no significant driver stress difference from driving with lower density of GPS instructions.