Latest revision as of 21:18, 1 February 2021

Abstract

In generating advisories, current ground Air Traffic Management (ATM) automation tools such as NASA’s Center-TRACON Automation System (CTAS) and MITRE’s User Request Evaluation Tool (URET) rely upon an aging ground ATM infrastructure to provide current state and to predict future intentions of aircraft. Significant improvement in these advisories could be achieved by tapping into the high-precision state and intent data available onboard today’s air transport aircraft. A recent NASA/FAA data exchange experiment was conducted to assist in quantifying the potential of datalink to improve ground-based ATM automation performance. This paper reports the results of a study into the quantitative characteristics of the improved lateral intent information and its potential impact on automation conflict detection performance. The results suggest that the downlink of flight management system (FMS) state and intent data will significantly improve the performance of current technology ground automation.

Original document

The different versions of the original document can be found in:

• http://www.aviationsystemsdivision.arc.nasa.gov/publications/more/agi/schleicher_10_02.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2002-5845,

http://dx.doi.org/10.2514/6.2002-5845

• https://www.aviationsystemsdivision.arc.nasa.gov/publications/more/agi/schleicher_10_02.pdf,

https://arc.aiaa.org/doi/10.2514/6.2002-5845,

https://www.aviationsystems.arc.nasa.gov/publications/more/agi/schleicher_10_02.pdf,

https://academic.microsoft.com/#/detail/2132919357