Using Synchronized Trajectory Data to Improve Airspace Demand Predictions

Abstract

The National Airspace System (NAS) and its users employ various decision support systems to model future aircraft trajectories. These trajectories support functions like strategic conflict detection, time-based metering, fuel estimation, arrival time estimation, and strategic traffic flow management. Each system uses its own trajectory prediction algorithm, resulting in discrepancies in aircraft time and position predictions between systems.Air/Ground Trajectory Synchronization (AGTS) reconciles differences in trajectory prediction data elements across NAS systems to increase common situational awareness and enable more efficient and consistent decision making. The AGTS project developed a prototype AGTS Service, with the Traffic Flow Management System (TFMS) as the initial target recipient of synchronized trajectory data. The prototype implements business rules associated with using Time Based Flow Management (TBFM) trajectory data to improve TFMS trajectory prediction outputs.This paper describes analyses of trajectory prediction and scheduling data from TBFM and TFMS that drove selection of the TBFM data to provide to TFMS and associated development of the AGTS business rules. We compared the accuracy of data published by each system relative to actual meter fix crossing times to determine which TBFM Scheduled Times of Arrival (STAs) should be incorporated into TFMS trajectory predictions as an initial step toward trajectory synchronization. This paper summarizes these business rules.