Assessment of Situation Awareness and Automation in Performance-Based Navigation Procedures

Abstract

PBN (Performance-Based Navigation) implies an increase in the automation of air operations, in the context of the current evolution of flight trajectories that are based on a flexible definition of route waypoints, to enable the implementation of TBO (Trajectory-Based Operations) and trajectory negotiation, all under the umbrella of SWIM (System-Wide Information Management). From a general perspective, automation has a positive impact on flight safety, contributing to the reduction of flight crew workload. However, in the particular case of PBN turns, there are cases where pilots are not aware of the type of turns that their aircraft perform. There is a risk of an automation bias leading to situations where the crew perceive that it is not their responsibility to start a turn or to monitor the conditions that drive the autopilot behaviour. In the context of a research line that aims to apply Bayesian networks to SA (Situation Awareness) measurement, we have designed an experiment to assess automation in a simulated PBN departure procedure, intending to collect data that are relevant to analyze the automation bias problem and rate SA using logistic regression.