Increasing Pilot’s Understanding of Future Automation State – An Evaluation of an Automation State and Trajectory Prediction System Timothy J. Etherington Lynda J. Kramer Kimberlee H. Shish Steven D. Young Technical Fellow Crew Systems and Aviation Intelligent Systems Division Safety-Critical Avionics Systems Collins Aerospace Operations Branch NASA Ames Research Center Branch Hampton, Virginia NASA Langley Research Center Moffett Field, CA NASA Langley Research Center
[email protected] Hampton, Virginia
[email protected] Hampton, Virginia
[email protected] [email protected] Emory T. Evans Taumi S. Daniels Flight Software Systems Branch Electronic Instrument Systems NASA Langley Research Center Branch Hampton, Virginia NASA Langley Research Center
[email protected] Hampton, Virginia
[email protected] Abstract— A pilot in the loop flight simulation study was I. INTRODUCTION conducted at NASA Langley Research Center to evaluate a trajectory prediction system. The trajectory prediction system Automation complexity and non-transparency continue to computes a five-minute prediction of the lateral and vertical path create situations where pilots are surprised during routine of the aircraft given the current and intent state of the automation. operations [1]. Navigation and flight management systems in The prediction is shown as a graphical representation so the pilots particular create optimized routing but only the planned route can form an accurate mental model of the future state. Otherwise, (i.e., flight plan) is shown to the pilot. If conditions are many automation changes and triggers are hidden from the flight encountered outside the plan or if automation modes do not crew or need to be consolidated to understand if a change will allow the execution of the plan, pilots are sometimes surprised occur and the exact timing of the change.