Driver drowsiness in automated and manual driving

Abstract

Driver drowsiness is a major cause of traffic accidents. Automated driving might counteract this problem, but in the lower automation levels, the driver is still responsible as a fallback. The impact of driver drowsiness on automated driving under realistic conditions is, however, currently unknown. This work contributes to risk and hazard assessment with a field study comparing manual to level-2 automated driving. The experiment was conducted on a test track using an instrumented vehicle. Results (N=30) show that in automated driving, driver drowsiness (self-rated with the Karolinska Sleepiness Scale) is significantly higher as compared to manual driving. Age group (20--25, 65--70 years) and driving time have a strong impact on the self-ratings. Additionally, to subjective measures, a correlation was also identified between drowsiness and heart rate data. The gained knowledge can be useful for the development of drowsiness detection systems and dynamic configuration of driver-vehicle interfaces based on user state.