Assisting the Improvement of a Military Safety System: An Application of Rapid Assessment Procedures to the Automatic Ground Collision Avoidance System

Abstract

This article describes an iterative application of Rapid Assessment Procedures (RAP) to study human-machine interaction issues with a recently implemented, highly automatic system on the F-16 fighter aircraft known as the Automatic Ground Collision Avoidance System (Auto-GCAS). Auto-GCAS is a sophisticated technology that has the ability to detect an imminent ground collision threat and automatically execute a last-moment maneuver to avoid a crash. We employed RAP methods at multiple United States Air Force and Air National Guard sites in the United States and abroad. Over a three-year period, we conducted semi-structured interviews with 402 F-16 pilots experienced with the system. The method we employed, termed here iterative RAP, is reviewed in detail and evaluated in the framework of Utarini, Winkvist, and Pelto's (2001) eleven criteria for quality RAP studies. Results from this study include assisting in correcting system misunderstandings and anomalies, improving information flow about Auto-GCAS, and contributing towards the perception of military safety systems as valuable. This article concludes by (1) discussing positive effects that iterative RAP can contribute to the defense community and (2) arguing our method's utility towards the study of complex bureaucracies and multi-sited research, particularly following the introduction of new technology or policy.