Development and Initial Evaluation of a Reinforced Cue Detection Model to Assess Situation Awareness in Commercial Aircraft Cockpits

Commercial transport aircraft of today vary greatly from early aircraft with regards to how the aircraft are controlled and the feedback provided from the machine to the human operator. Over time, as avionics systems became more automated, pilots had less direct control over their aircraft. Much research exists in the literature about automation issues, and several major accidents over the last twenty years spurred interest about how to maintain the benefits of automation while improving the overall human-machine interaction as the pilot is considered the last line of defense. An important reason for maintaining or even improving overall pilot situation awareness is that the resulting improved situation awareness can assist the human pilot in rapidly solving unanticipated, novel problems for which no computer logic has been written. It is essential for the pilots to obtain cues to make appropriate decisions under time pressure. However, to date, no studies have directly examined the approach of reinforcing the relevant flight and automation status cues during flight to increase the pilot’s situation awareness when a failure unexpectedly occurs. Attitudes toward, and issues with automated systems from the pilots’ perspectives were studied using a survey completed by commercial air transport pilots. The survey results were used as the framework for designing a simulation analysis, using a small group of commercial airline pilots, to assess the benefits of a reinforced cue detection model. A phenomenological assessment of open ended questions asked at the conclusion of each simulation showed, subject to the limits of the relatively small sample size, that the “Reinforced Cue Detection Model” implemented in the form of asking the pilots situational awareness questions during the flight, can help to reduce pilot’s complacency, increase situation awareness, and make automation a better team member. Pilots also found reinforced cues to be helpful in the event of unexpected system failure. The current research supports literature regarding pilots’ opinions towards automated systems and indicates that there are benefits to be gained from improving the pilot automation integration. The Reinforced Cue Detection Model, albeit tested on a small sample size, supported improvement of the pilots’ situation awareness