A proactive approach to human error detection and identification in aviation and air traffic control

Abstract

In recent years, there has been a realization that total elimination of human error may be difficult to achieve. A further reduction of accidents will require a better understanding of how practitioners manage their errors in ways that consequences are contained or mitigated. With this goal in mind, the present study has set out to propose a framework of cognitive strategies in error detection that would make human performance resilient to changes in work demands. The literature regarded error detection as a spontaneous process that occurs either while an action is executed (action-based detection) or after action feedback (outcome-based detection). To help practitioners maintain a state of mindfulness and introspection, this study proposes several cognitive strategies such as, rehearsing tasks for future execution, bringing into conscious attention routine tasks, seeing how trajectories change over time, and cross-checking data for reliability. Two further detection mechanisms are proposed at the situation assessment and planning stages of performance. Awareness-based detection may include revising a model of the situation, finding hidden assumptions, and testing the plausibility of assumptions. Planning-based detection addresses issues such as, identifying uncertainties in a plan, thinking out possible errors, and deciding when and how often to review task progress. Finally, several attitudinal factors and team factors are presented that affect the processes of error detection and identification. The cognitive strategies in error detection together with the attitudinal and team factors constitute a framework for designing the content of error management training.