Suchergebnisse

The present study examined the effects of task complexity and time on task on the monitoring of a single automation failure during performance of a complex flight simulation task involving tracking, fuel management, and engine-status monitoring. Two groups of participants performed either all three flight simulation tasks simultaneously (multicomplex task) or the monitoring task alone (single-complex task); a third group performed a simple visual vigilance task (simple task). For the multicomplex task, monitoring for a single failure of automation control was poorer than when participants monitored engine malfunctions under manual control. Furthermore, more participants detected the automation failure in the first 10 min of a 30-min session than in the last 10 min of the session, for both the simple and the multicomplex task. Participants in the single-complex condition detected the automation failure equally well in both periods. The results support previous findings of inefficiency in monitoring automation and show that automation-related monitoring inefficiency occurs even when there is a single automation failure. Implications for theories of vigilance and automation design are discussed.

The effects of adaptive task allocation on monitoring for automation failure during multi task flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 3D-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the lO-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.