Trajectory predictor performance experiment using Required Time of Arrival during descent

Most commercial aircraft today have advanced navigation computer systems, referred to as the Flight Management System or FMS. In recent years, the FMS has been increasingly utilized to support a type of performance-based navigation that allows an aircraft to fly a specific path between two defined 3-dimensional points in space. However, current deployed FMS architectures can do even more, calculating a Required Time of Arrival (RTA) at a precise 3-dimensional point in space and then automatically controlling the aircraft´s airspeed and rate-of-descent to reach that point within a very small tolerance. This capability could offer increased efficiency for airlines and reduced workload for air traffic control under certain operational concepts such as metering to a transition fix into a terminal area. One challenge is that while RTA clearances are commonly used by en-route controllers when metering, the en-route air traffic automation tools that predict aircraft conflicts do not have the capability to input RTA clearances. The automation depends on flight plan information to generate aircraft trajectories, which are then used to predict conflicts. Adjustments in speed and Top of Descent (TOD) point implemented to meet an RTA would not be known to the automation and therefore not reflected in the trajectories generated. This paper describes an experiment where a real FMS platform was utilized in a simulation environment and simulated flight data was run through the current ground based automation in en route airspace, referred to as En Route Automation Modernization (ERAM). The predicted trajectories were compared under various RTA settings, weather conditions, and flight paths to examine how the current ERAM trajectory predictor performed. The results provide guidance on where additional research is needed and insights into using this FMS capability in current operations.