Abstract

In view of the ever-increasing air traffic, much attention in air-traffic-management research has been given to improving arrival and departure efficiency. As air traffic begins and ends at the airport, the issues of taxi delays and ground-operation incursions become more pressing. This paper considers the surface-traffic problem at major airports and envisions a collaborative traffic and aircraft control environment where a surface traffic automation system will help coordinate surface traffic movements. A previous study has established the performance potential of advanced guidance and control of a transport aircraft to deliver high-precision taxi capability. Such an aircraft capability will provide the surface traffic automation system with the flexibility to issue taxi clearances with tight time margins, in an effort to reduce taxi delays. An example is the ability to clear taxiing aircraft to cross active runways within a precise time window, without the need for the aircraft to hold short of the runways and unnecessarily increase taxi delay while waiting for the opportunity to cross. This paper describes the development of a surface traffic automation system, known as Ground-Operation Situation Awareness and Flow Efficiency (GO-SAFE). The GO-SAFE system is designed to work with advanced surveillance and communications technologies, and anticipated air traffic automation systems under development. It includes tools to help the ground controller with predicted traffic information, functionality to manipulate taxi routes, and advanced capabilities to schedule runway usage to accommodate landing, takeoff, and crossing traffic. Some of the GO-SAFE functionality will be useful for current-day operations, and its advanced tools will provide maximum benefit when integrated with advanced aircraft taxi control capabilities.


Original document

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

http://dx.doi.org/10.2514/6.2002-4856
https://core.ac.uk/display/101154706,
http://human-factors.arc.nasa.gov/ihi/hcsl/publications/AIAAGNC02_ChengFoyle.pdf,
https://human-factors.arc.nasa.gov/publications/20051025111048_AIAAGNC02_ChengFoyle.pdf,
https://hsi.arc.nasa.gov/publications/20051025111048_AIAAGNC02_ChengFoyle.pdf,
https://humanfactors.arc.nasa.gov/publications/20051025111048_AIAAGNC02_ChengFoyle.pdf,
http://hsi.arc.nasa.gov/groups/HCSL/publications/AIAAGNC02_ChengFoyle.pdf,
http://humansystems.arc.nasa.gov/groups/hcsl/publications/AIAAGNC02_ChengFoyle.pdf,
http://humanfactors.arc.nasa.gov/ihi/hcsl/publications/AIAAGNC02_ChengFoyle.pdf,
http://www.optisyn.com/research/publications/2002/GNC2002.pdf,
https://academic.microsoft.com/#/detail/2021183712
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Published on 01/01/2002

Volume 2002, 2002
DOI: 10.2514/6.2002-4856
Licence: CC BY-NC-SA license

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