Artificial Intelligence for Automatic Classification of Unintentional Electromagnetic Interference in Air Traffic Control Communications

In this chapter, the authors propose the application of artificial intelligence (namely expert system and neural network) for estimating the mental workload of air traffic controllers while working at different control centers (sectors): terminal control center, approach control center, area control center. At each air traffic control center, air traffic controllers will perform the following procedures: coordination between units, aircraft transit, climbing, and descending. So with the help of the artificial intelligence (AI) and its branches expert system and neural network, it is possible to estimate the mental workload of dispatchers for a different number of aircraft, compare the workload intensity of the air traffic control sectors, and optimize the workload between sectors and control centers. The differentiating factor of an AI system from a standard software system is the characteristic ability to learn, improve, and predict. Real dispatchers, students, graduate students, and teachers of the National Aviation University took part in these researches.

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Distributed artificial intelligence approach to air traffic control

IEE Proceedings D Control Theory and Applications ◽

10.1049/ip-d.1991.0072 ◽

1991 ◽

Vol 138 (6) ◽

pp. 515 ◽

Cited By ~ 10

Author(s):

N.V. Findler ◽

R. Lo

Keyword(s):

Artificial Intelligence ◽

Traffic Control ◽

Air Traffic Control ◽

Air Traffic ◽

Distributed Artificial Intelligence ◽

Intelligence Approach ◽

Artificial Intelligence Approach

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Classification of radar clutter in an air traffic control environment

Proceedings of the IEEE ◽

10.1109/5.90155 ◽

1991 ◽

Vol 79 (6) ◽

pp. 742-772 ◽

Cited By ~ 32

Author(s):

S. Haykin ◽

W. Stehwien ◽

C. Deng ◽

P. Weber ◽

R. Mann

Keyword(s):

Traffic Control ◽

Air Traffic Control ◽

Air Traffic ◽

Control Environment ◽

Radar Clutter

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Workload Perception of Air Traffic Control Officers and Pilots During Continuous Descent Operations Approach Procedures

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000154 ◽

2019 ◽

Vol 9 (1) ◽

pp. 2-11

Author(s):

Marina Efthymiou ◽

Frank Fichert ◽

Olaf Lantzsch

Keyword(s):

Fuel Consumption ◽

Traffic Control ◽

Air Traffic Control ◽

Negative Impact ◽

Air Traffic ◽

Reduce Fuel Consumption ◽

Total Load ◽

Open Path

Abstract. The paper examines the workload perceived by air traffic control officers (ATCOs) and pilots during continuous descent operations (CDOs), applying closed- and open-path procedures. CDOs reduce fuel consumption and noise emissions. Therefore, they are supported by airports as well as airlines. However, their use often depends on pilots asking for CDOs and controllers giving approval and directions. An adapted NASA Total Load Index (TLX) was used to measure the workload perception of ATCOs and pilots when applying CDOs at selected European airports. The main finding is that ATCOs’ workload increased when giving both closed- and open-path CDOs, which may have a negative impact on their willingness to apply CDOs. The main problem reported by pilots was insufficient distance-to-go information provided by ATCOs. The workload change is important when considering the use of CDOs.

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How to Evaluate Remote Tower Metrics in Connection With Weather Observations

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000142 ◽

2018 ◽

Vol 8 (2) ◽

pp. 100-111 ◽

Cited By ~ 1

Author(s):

Maik Friedrich ◽

Christoph Möhlenbrink

Keyword(s):

Traffic Control ◽

Air Traffic Control ◽

Influential Factors ◽

Air Traffic ◽

Weather Event ◽

Evaluation Of Performance ◽

Weather Events ◽

Weather Observations ◽

Validation Experiment ◽

Remote Controller

Abstract. Owing to the different approaches for remote tower operation, a standardized set of indicators is needed to evaluate the technical implementations at a task performance level. One of the most influential factors for air traffic control is weather. This article describes the influence of weather metrics on remote tower operations and how to validate them against each other. Weather metrics are essential to the evaluation of different remote controller working positions. Therefore, weather metrics were identified as part of a validation at the Erfurt-Weimar Airport. Air traffic control officers observed weather events at the tower control working position and the remote control working position. The eight participating air traffic control officers answered time-synchronized questionnaires at both workplaces. The questionnaires addressed operationally relevant weather events in the aerodrome. The validation experiment targeted the air traffic control officer’s ability to categorize and judge the same weather event at different workplaces. The results show the potential of standardized indicators for the evaluation of performance and the importance of weather metrics in relation to other evaluation metrics.

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