The Efficient Descent Advisor (EDA) is being developed to provide a decision support tool for controllers to help them issue continuous descent trajectories for arrival traffic. This paper investigates methods for improving the accuracy of the trajectory synthesizer, which is the trajectory engine that supports EDA. The study was motivated by the need to harmonize the trajectories generated by the trajectory synthesizer with those generated by on board Flight Management Systems (FMS's), which are used by pilots to execute continuous descents. An analysis of error sources between predicted and actual continuous descent trajectories shows that thrust and descent speed profiles are the most important parameters affecting the accurate prediction of top of descent location and arrival fix cross ing times. While the thrust correction applies to all descents, the descent speed applies to uncontrolled (non-metered) descents. In order to establish the best value for thrust correction for use in the trajectory synthesizer, a limited set of continuous descent trajec tories flown by aircraft during regular revenue flights into the Dallas-Fort Worth Airport were recorded and analyzed. In addition to recorded trajectories, controllers also obtained FMS-calculated top-of-descent ranges, crossing times and speed profiles from pilots when ever possible. In post flight analysis the predicted trajectories generated by the Trajectory Synthesizer were compared to the flight test data. It was generally found that the actual (FMS guided) trajectories were flown at shallower descent angles than the predicted tra jectories and that actual descent speeds often differed significantly from those programmed into the trajectory synthesizer. A descent thrust correction parameter, normalized to air craft weight and dependent on aircraft type and airline/operator is introduced to improve trajectory prediction accuracy. It is shown that this parameter, together with updated speeds obtained from pilots prior to descent, increase the accuracy of trajectory prediction significantly.
展开▼