Error Types and Related Error Detection Mechanisms in the Aviation Domain: An Analysis of Aviation Safety Reporting System Incident Reports

Abstract

Human error is considered a contributing factor in 70% to 80% of all aviation accidents. Because errors can never be eliminated completely, a further reduction of the already low accident rate in this domain will require investments in better support for error management. In particular, a better understanding of the nature and effectiveness of error detection mechanisms is needed. With this goal in mind, NASA Aviation Safety Reporting System incident reports were analyzed in terms of the formal characteristics of underlying errors, the cognitive stage, and the performance level at which these errors occurred, and with respect to the processes that led to their detection and, thus, prevented these incidents from turning into accidents. The majority of incidents involved lapses (i.e., failures to perform a required action) or mistakes, such as errors in intention formation and strategy choice. These errors were most often detected based on routine checks and the observed outcome of an action, respectively. Most slips appear to have been discovered by the crew before they could lead to a problem worth reporting. Our findings suggest a need for more effective feedback in support of data-driven monitoring, especially in the case of errors of omission and for shared knowledge of intent between airborne and ground-based operators to promote the more timely and reliable detection of mistakes.