Automation of Air Traffic Management Using Fuzzy Logic Algorithm to Integrate Unmanned Aerial Systems into the National Airspace

Unmaned Aircraft Systems (UAS) have been increasing in popularity in personal, commercial, and military applications. The increase of the use of UAS poses a significant risk to general air travel, and will burden an already overburdened Air Traffic Control (ATC) network if the Air Traffic Management (ATM) system does not undergo a revolutionary change. Already there have been many near misses reported in the news with personal hobbyist UAS flying in controlled airspace near airports almost colliding with manned aircraft. The expected increase in the use of UAS over the upcoming years will exacerbate this problem, leading to a catastrophic incident involving substantial damage to property or loss of life. ATC professionals are already overwhelmed with the air traffic that exists today with only manned aircraft. With UAS expected to perform many tasks in the near future, the number of UAS will greatly outnumber the manned aircraft and overwhelm the ATC network in short order to the point where the current system will be rendered extremely dangerous, if not useless. This paper seeks to explore the possibility of using the artificial intelligence concept of fuzzy logic to automate the ATC system in order to handle the increased traffic due to UAS safely and efficiently. Automation would involve an algorithm to perform arbitration between aircraft based on signal input to ATC ground stations from aircraft, as well as signal output from the ATC ground stations to the aircraft. Fuzzy logic would be used to assign weights to the many different variables involved in ATM to find the best solution, which keeps aircraft on schedule while avoiding other aircraft, whether they are manned or unmanned. The fuzzy logic approach would find the weighted values for the available variables by running a simulation of air traffic patterns assigning different weights per simulation run, over many different runs of the simulation, until the best values are found that keep aircraft on schedule and maintain the required separation of aircraft

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Machine Learning and Cognitive Ergonomics in Air Traffic Management: Recent Developments and Considerations for Certification

Aerospace ◽

10.3390/aerospace5040103 ◽

2018 ◽

Vol 5 (4) ◽

pp. 103 ◽

Cited By ~ 12

Author(s):

Trevor Kistan ◽

Alessandro Gardi ◽

Roberto Sabatini

Keyword(s):

Machine Learning ◽

Traffic Management ◽

Air Traffic Management ◽

Air Traffic ◽

Unmanned Aerial Systems ◽

Research Attention ◽

Cognitive Ergonomics ◽

Traffic Flow Management ◽

Recent Developments ◽

Aerial Systems

Resurgent interest in artificial intelligence (AI) techniques focused research attention on their application in aviation systems including air traffic management (ATM), air traffic flow management (ATFM), and unmanned aerial systems traffic management (UTM). By considering a novel cognitive human–machine interface (HMI), configured via machine learning, we examined the requirements for such techniques to be deployed operationally in an ATM system, exploring aspects of vendor verification, regulatory certification, and end-user acceptance. We conclude that research into related fields such as explainable AI (XAI) and computer-aided verification needs to keep pace with applied AI research in order to close the research gaps that could hinder operational deployment. Furthermore, we postulate that the increasing levels of automation and autonomy introduced by AI techniques will eventually subject ATM systems to certification requirements, and we propose a means by which ground-based ATM systems can be accommodated into the existing certification framework for aviation systems.

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New and Envisioned Communication Technologies: How Well can They Support Future Air Traffic Management Operations?

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/107118139704100154 ◽

1997 ◽

Vol 41 (1) ◽

pp. 238-242

Author(s):

Nadine B. Sarter ◽

David D. Woods

Keyword(s):

Traffic Control ◽

Traffic Management ◽

Communication Systems ◽

Current System ◽

Effective Means ◽

Communication Technologies ◽

Air Traffic Management ◽

Air Traffic ◽

Prior Approval ◽

The Future

In the future air traffic management (ATM) system, flight crews will most likely have the option to dynamically adjust their flight path without prior approval from the ground. As a result, knowledge of intent may no longer be shared by pilots and controllers, and the potential for unforeseen conflicts as well as the need for immediate yet coordinated interventions can be expected to increase. To support such a short-term reactive approach to traffic management and separation, highly effective means of communication will be required that allow for a rapid creation and update of shared frames of reference. It is not clear that recently developed and envisioned communication media and technologies are designed with these goals in mind. A recent line of research explored the ability of two communication systems - DataLink and the Voice Control and Switching System (VSCS)—to handle communication not only in the current air traffic control system but to also support the highly flexible operations and new coordination and knowledge demands that are likely going to be part of the future ATM system. System reviews, conceptual simulations, and a pilot survey served to gather information on current and potential future experiences with these systems. The results of our research suggest that neither system is tailored to future ATM operations, and that they create new challenges even in the context of the current system.

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Safety Culture and Safety-Relevant Behavior in Air Traffic Management

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000068 ◽

2015 ◽

Vol 5 (1) ◽

pp. 3-17 ◽

Cited By ~ 5

Author(s):

Michaela Schwarz ◽

K. Wolfgang Kallus

Keyword(s):

Safety Culture ◽

Traffic Management ◽

Service Providers ◽

Five Factor Model ◽

Principal Component ◽

Air Traffic Management ◽

Air Traffic ◽

Psychometric Validation ◽

Safety Attitudes ◽

Culture Development

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

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