Reducing Human/Pilot Errors in Aviation Using Augmented Cognition and Automation Systems in Aircraft Cockpit

Abstract

Human errors cause the majority of aviation accidents. Augmented cognition and automation systems enhance pilot performance by evaluating system limitations and flight precision and performance. This study examines the human-machine interface in cockpit design using the tenets of augmented cognition and automation systems theory in terms of task allocation, attentional resources, and situational awareness. The study compares how these principles apply to and interact with each other and with a human/pilot in a closed-loop system. We present a method for integrating augmented cognition systems into airplane flight management systems. We demonstrate systems enhancement with an experiment in which test pilots flew two simulated flights, once without and once with an augmented cognition system. We measured pilot and airplane performance, pilots’ situational awareness, workload management, pilots’ use of cockpit checklists, and flight precision along four axes: (1) altitude, (2) course, (3) radial/bearing and heading, and (4) airspeed.