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Maritime piloting operations involve on-call work schedules that may lead to sleep loss and circadian misalignment. Our study documented pilot work scheduling practices (n = 61) over a one-year period. Most pilots worked a week-on/week-off schedule. Work periods averaged 7.6 hours in duration and pilots worked up to four ship assignments during a given work period. Work weeks averaged a total of 35.0 hours with pilots working on average three consecutive days. Night work was common (19.0 hours/week) with 02:00 h the most common starting hour for a work period. On-call work periods occurred at irregular times with a high degree of start time variability between consecutive work periods. While typical individual and weekly work total hours were not high, there were instances with long work periods, minimal rest opportunities, and extended total weekly work hours. Fatigue-model predictions based on work schedules were similar to objective outcomes collected among other groups of maritime pilots and may prove useful in identifying potential fatigue risks within on-call work schedules. Future studies should be conducted using objective measures to provide further insight on how on-call maritime operations influence sleep timing, alertness, and performance.

Exploration of deep space poses many challenges. Mission support personnel will not be immediately available to assist crewmembers performing complex operations on future long-duration exploration operations. Consequently, it is imperative that crewmembers have objective, reliable, and non-invasive metrics available to aid them in determining their fitness for duty prior to engaging in potentially dangerous tasks. The Robotics On-Board Trainer (ROBoT) task is NASA’s platform for training astronauts to perform docking and grappling maneuvers. It is regularly used by crewmembers during spaceflight for refresher training. The operational ROBoT system, however, does not record data. Thus, a research version of ROBoT, called ROBoT-r, was developed so that operationally relevant data could be mined to provide feedback to crewmembers. We investigated whether ROBoT-r metrics would change according to sleep loss and circadian phase in a 28-h laboratory-based sleep deprivation study. Overall, participants showed improvement over time despite sleep loss, indicating continued learning. Performance on the psychomotor vigilance task (PVT) followed an expected profile, with reduced performance across the night. These findings suggest that individuals may be able to temporarily compensate for sleep loss to maintain performance on complex, novel tasks. It is possible that some ROBoT-r metrics may be sensitive to sleep loss after longer bouts of wakefulness or after individuals have habituated to the task. Studies with additional participants and extended pre-training on the ROBoT-r task should be conducted to disentangle how brain activity may change as individuals learn and habituate to complex tasks during sleep loss.