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Objective: To examine operator strategies for diagnosing and recovering from errors and disturbances as well as the impact of automation design and time pressure on these processes., Background: Considerable efforts have been directed at error prevention through training and design. However, because errors cannot be eliminated completely, their detection, diagnosis, and recovery must also be supported. Research has focused almost exclusively on error detection. Little is known about error diagnosis and recovery, especially in the context of event-driven tasks and domains., Method: With a confederate pilot, 12 airline pilots flew a 1-hr simulator scenario that involved three challenging automation-related tasks and events that were likely to produce erroneous actions or assessments. Behavioral data were compared with a canonical path to examine pilots' error and disturbance management strategies. Debriefings were conducted to probe pilots' system knowledge., Results: Pilots seldom followed the canonical path to cope with the scenario events. Detection of a disturbance was often delayed. Diagnostic episodes were rare because of pilots' knowledge gaps and time criticality. In many cases, generic inefficient recovery strategies were observed, and pilots relied on high levels of automation to manage the consequences of an error., Conclusion: Our findings describe and explain the nature and shortcomings of pilots' error management activities. They highlight the need for improved automation training and design to achieve more timely detection, accurate explanation, and effective recovery from errors and disturbances., Application: Our findings can inform the design of tools and techniques that support disturbance management in various complex, event-driven environments.

Operators in complex event-driven domains must coordinate competing attentional demands in the form of multiple tasks and interactions. This study examined the extent to which this requirement can be supported more effectively through informative interruption cueing (in this case, partial information about the nature of pending tasks). The 48 participants performed a visually demanding air traffic control (ATC) task. They were randomly assigned to 1 of 3 experimental groups that differed in the availability of information (not available, available upon request, available automatically) about the urgency and modality of pending interruption tasks. Within-subject variables included ATC-related workload and the modality, frequency, and priority of interruption tasks. The results show that advance knowledge about the nature of pending tasks led participants to delay visual interruption tasks the longest, which allowed them to avoid intramodal interference and scanning costs associated with performing these tasks concurrently with ATC tasks. The 3 experimental groups did not differ significantly in terms of their interruption task performance; however, the group that automatically received task-related information showed better ATC performance, thus experiencing a net performance gain. Actual or potential applications of this research include the design of interfaces in support of attention and interruption management in a wide range of event-driven environments.