A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations
AIAA/IEEE Digital Avionics Systems Conference - Proceedings
In this paper we describe and evaluate a flight replanning tool, called the trial planner, for terminal area air transport applications. The trial planner employs predefined airspace structures to generate rerouting options between vertiports. In a simplified definition, vertiports are facilities that provide services for managing the take-off and landing of autonomous or manned electric vertical take-off or landing (eVTOL) aircraft. The airspace structures involved in our test cases are arrival routes that consisting of predefined entry points to which a transitional path is computed dynamically from the current position of the aircraft. Rerouting options include both the transitional path and approach segment along the arrival route. These rerouting options are not vetted for potential conflicts with other operations until a human operator commits to a choice and forwards the flight plan modification for approval from an automated airspace management service. A selected rerouting option is executed by loading a flight plan file to the aircraft ground control station. We conducted a qualitative evaluation of the trial planner using ratings provided by flight crews and air transportation human factors experts with relevant experience from air traffic control. The trial-planner was evaluated against operator rated trust in the route recommendations and rated adequacy of the explanations for the route options. In this paper, we detail the logic and implementation of the trial planner, as well as report the results of the evaluation of the implementation herein.
air taxi, automated decision-making support, autonomous aircraft, eVTOL, operation modification, terminal area operations, trial planning, Urban Air Mobility
Anne S. Suzuki and Quang V. Dao. "A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations" AIAA/IEEE Digital Avionics Systems Conference - Proceedings (2022). https://doi.org/10.1109/DASC55683.2022.9925838