Effects of partially automated driving on the development of driver sleepiness

Ahlström, Christer; Zemblys, Raimondas; Jansson, Herman; Forsberg, Christian; Karlsson, Johan; Anund, Anna · 2021 · Crossref

DOI: 10.1016/j.aap.2021.106058

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Summary

This study investigates the impact of Level 2 partially automated driving on the development of driver sleepiness compared to manual driving. Motivated by concerns that the shift from active driving to passive monitoring may induce underload and increased fatigue, the researchers hypothesized that partially automated driving would lead to higher levels of sleepiness. The study aimed to compare subjective and objective sleepiness indicators during daytime (alert) and night-time (sleep-deprived) conditions on a real motorway. The experiment employed a within-subject 2 × 2 design involving 89 drivers who completed 180 km drives on a Swedish motorway. Participants drove in two conditions: manual driving and partially automated driving using Volvo Pilot Assist (adaptive cruise control and lane keeping assistance). The drives were conducted during the day with full sleep and at night after sleep deprivation. Data collection utilized instrumented vehicles equipped with eye-tracking systems, electrocardiograms, and, in one vehicle, 64-channel electroencephalograms (EEG). Sleepiness was measured using the Karolinska Sleepiness Scale (KSS), blink duration, PERCLOS, pupil diameter, heart rate, and EEG alpha and theta power. Psychomotor vigilance tasks (PVT) were administered before and after each drive to assess alertness. Results indicated that night-time driving significantly increased sleepiness across all metrics, including subjective ratings, blink duration, PERCLOS, pupil diameter, and heart rate. Partially automated driving led to slightly higher subjective sleepiness ratings, longer blink durations, decreased pupil diameter, slower heart rates, and increased EEG alpha and theta activity compared to manual driving. However, these negative effects were primarily evident during night-time drives when sleep pressure was high. During daytime drives, when drivers were alert, partially automated driving had little to no detrimental effect on fatigue; in some instances, it showed a slight alerting effect early in the drive. PVT results showed slower reaction times and more lapses after night-time drives, but partial automation did not significantly alter lapse counts. The study concludes that while partially automated driving can increase sleepiness, this effect is contingent on the driver’s baseline alertness. The risk of increased fatigue due to underload is significant mainly during night-time or sleep-deprived conditions. During daytime, the system does not detrimentally affect fatigue. The authors suggest that future research should investigate whether the safety benefits of lateral and longitudinal driving support compensate for the potential increase in sleepiness during high-risk periods.

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Topics

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• drowsiness detection algorithms
• drowsiness
• sleep deprivation
• time on task
• truck driver fatigue
• vigilance

Information type

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• Empirical Findings: physiological data, behavioral performance data
• Methodological Resource: tool software