The effect of prolonged conditionally automated driving on fatigue, physiological activity, and takeover performance: a driving simulator experiment

<i>Objective</i>. This driving simulator experiment was conducted to examine the effect of prolonged automation on fatigue during conditionally automated driving (CAD). Driver fatigue, which can be distinguished from drowsiness and already accounts for as many as 20% of all road traffic accidents, is likely to remain a pervasive problem during CAD, as reductions in attention and vigilance due to fatigue could imperil safe transitions of control between automated system and user. While considerable research exists concerning drivers' responses under states of drowsiness or distraction, fewer studies have investigated the effect of automation on fatigue.<i>Approach</i>. Drivers' self-reported fatigue and workload, physiological responses, and takeover performance were examined across three driving conditions: a baseline period of manual driving, an automated driving condition in which drivers interacted with the<i>N</i>-back task, and a 50 min automated drive with no secondary task.<i>Main results</i>. Findings show that fatigue was significantly higher following 50 min of automated driving than at baseline, or while participants performed a non-driving-related task. Strikingly, 80% of participants experienced signs of sleepiness, and almost half had to exercise effort to stay awake. Fatigue also resulted in decreases in heart rate (HR) and relative beta power derived from electroencephalography, and an increase in blink rate and HR variability.<i>Significance</i>. Overall, the findings advance knowledge in this area by supporting the idea of fatigue as failure to adequately self-regulate during automation. Several physiological measures have also been identified as possible markers of fatigue to inform emerging monitoring technology.