Unprecedented global initiatives have begun to redesign the aviation systems that provide for the efficient and safe transport of civilian aircraft. Success of these initiatives is only possible through global collaborations that allow broader analyses and data to be shared. The paper reports on just such a study that examines the lateral deviations from the automation's known horizontal route of flight to the actual aircraft position. These errors are due to the typical navigation and surveillance errors, as well as the larger atypical errors that are mainly caused by purposeful changes in the route of flight that are not updated. Large data analyses within the ground automation systems of the United States and Europe indicated errors from 20 to 30 nautical miles are common, while airborne Australian and more samples in the United States had errors from 100 to 800 times smaller. Further analysis illustrated the direct impact these errors have on safety critical separation management functions. It was concluded that airborne derived data via Automatic Dependent Surveillance Contract reports offer a major opportunity to improve the groundbased automation functions.

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This paper aims to demonstrate how current technology can ass ist to improve ground-based trajectory prediction. The lack of accurate ground-based trajectory prediction is often associated with the inefficiencies resulting from current Air Traffic Control (ATC) practices. To this purpose, results from different ground-based Trajectory Predictors (TPs)-both standard and enhanced with Future Air Navigation Systems (FANS) data-link-are compared using operations into Los Angeles (LAX). At first sight, direct use of trajectory information down-linked through FANS from the aircraft's Flight Management System (FMS) seems logical, but numerous arguments exist against that approach. Instead, this research inferred parameters as speed schedule and aircraft mass from the FMS down-linked trajectory. Contrary to the trajectory data itself, these parameters can be used as input to many legacy TPs and are often unknown such that nominal values must be assume d. This paper indicates that with use of this inferred information significant improvements in ground-based trajectory prediction can be achieved. The 95% spread in the estimate time of arrival and top of descent error were reduced by a maximum 79% and 86%, respectively. The predicted

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