The rapid growth of air carrier, general aviation, and military traffic has strained the nation's Air Traffic Control (ATC) system. The symptoms of this strain appear as controller fatigue, low controller moral, and the occasional creation of a hazardous situation caused by human error. The current method employed to improve the ATC system has been in the form of increasing its air traffic handling capacity by adding more machinery and manpower. Thus, machines with greater processing power and more humans are coupled into a man machine system which is destined to continually grow. Little has been done in finding new forms of technology to increase the joint efficiency of man and machine. Two relatively new technologies which could create a path towards greater system efficiency are the technologies of voice recognition and artificial intelligence. With greater system efficiency, less controller fatigue and better air safety are expected. Where to apply these technologies, in what form, and how deep these technologies can be integrated into the ATC system are questions which deserve inquiry. The research details a method to answer these questions, develops prototype equipment from which to experiment, and establishes a basis from which other research efforts may be launched. A review of literature indicates that current efforts at applying voice recognition in flight operations are centered around pilot task improvement and special projects such as the space shuttle. While these efforts are certainly important, the controller environment can be just as demanding, stressful, and important. It is within this light that this study is launched.
Voice Recognition and Artificial Intelligence in an Air Traffic Control Environment
1988
117 pages
Report
No indication
English
Verbal , Air Transportation , Human Factors Engineering , Air traffic control systems , Artificial intelligence , Speech recognition , Air traffic , Aviation safety , Capacity(Quantity) , Efficiency , Environments , Errors , Fatigue(Physiology) , Hazards , Man machine systems , Human factors engineering , Manpower , Performance(Human) , Pilots , Prototypes , Job analysis
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