Pilot performance and preference for short cycles of automation in adaptive function allocation.
The present experiment examined pilot response to the rapid cycling of automation. The experiment was conducted using a multi-task simulation environment consisting of tracking, fuel management, and system monitoring sub-tasks. Monitoring and fuel management sub-tasks were performed manually in all conditions. The tracking sub-task cycled between manual and automated control at fixed intervals of either 15, 30 or 60 sec. These cycle times were completely crossed with three levels of tracking difficulty giving nine within-subject conditions which lasted 5 min each. Performance was measured on each of the sub-tasks, as was pilot fatigue level and subjective workload for the respective conditions. Results indicated that both difficulty and cycle duration significantly affected tracking performance which was degraded with task difficulty and longer cycle times. Fuel management and system monitoring performance were unaffected by tracking difficulty and automation duration. However, a subsequent analysis was conducted using the 15 sec period immediately following each automation episode as a 'window' of performance. A different pattern of results was observed. Tracking performance was similarly affected by difficulty, but was no longer affected by cycle duration. Furthermore, fuel management error indicated a trend toward better performance in low difficulty conditions. Results illustrate micro trade-offs within sub-tasks and macro trade-offs between sub-tasks. Overall, the results support the contention that excessively short cycles of automation prove disruptive to performance in multi-task conditions.
Scallen
S F
SF
Human Factors Research Laboratory, University of Minnesota, 1901 Fourth St S.E., Minneapolis, MN 55455, USA.
Hancock
P A
PA
Duley
J A
JA