DocumentCode
1144474
Title
Applications of simulation and artificial intelligence technology for ATC training
Author
Fabry, John M. ; Lupinetti, Albert A.
Author_Institution
Federal Aviation Adm. Office of Res. & Technol. Applications, Atlantic City Airport, NJ, USA
Volume
77
Issue
11
fYear
1989
fDate
11/1/1989 12:00:00 AM
Firstpage
1762
Lastpage
1765
Abstract
The authors describe how the application of artificial intelligence technologies to ATC can improve the training of individuals who plan strategic actions, as well as making it possible to interface and cooperate with geographically distributed individuals who plan tactical actions. They also show how such training can affect concerns as diverse as safety, capacity, resource limitations, and traffic system efficiency simultaneously in a real-time environment. By focusing on the learning aspect of artificial intelligence, new dimensions are added to ATC simulation for training. The authors propose the construction of a simulation-based training device, called an intelligent adaptive trainer. This device would be used to teach controllers to reconcile conflicts and simultaneously to build operational confidence within a cooperative decision-making environment. An approach for training controllers to deal with the data discontinuities that frequently occur between levels of planning and operations is discussed
Keywords
aerospace simulation; air-traffic control; computer aided instruction; digital simulation; knowledge based systems; training; ATC training; artificial intelligence technology; capacity; conflict reconciliation; cooperative decision-making environment; data discontinuities; digital simulation; intelligent adaptive trainer; resource limitations; safety; strategic action planning; tactical actions; traffic system efficiency; Air traffic control; Application software; Artificial intelligence; Automation; FAA; Force control; Humans; Railway safety; Real time systems; Traffic control;
fLanguage
English
Journal_Title
Proceedings of the IEEE
Publisher
ieee
ISSN
0018-9219
Type
jour
DOI
10.1109/5.47738
Filename
47738
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