Air Traffic Control (ATC) is a ground-based air navigation
service that directs airplanes on the ground and in regulated airspace.
Air traffic controllers also give advising services in
uncontrolled airspace on occasion.
By coordinating the movement of commercial and private
planes and guaranteeing a safe separation of traffic in the air and on the
ground, controllers ensure the safe flow of air traffic.
They usually provide pilots with real-time traffic and
weather notifications along with directing guidance.
The major goals of the ATC, according to the Federal
Aviation Administration (FAA), are to manage and expedite air traffic flow, as
well as to prevent aircraft crashes and provide real-time information and other
navigational assistance for pilots.
The ATC is a service that is both risk adverse and safety
crucial.
Air traffic controllers use a variety of technology,
including computer systems, radars, and transmitters, in addition to their eye
observation.
The volume and density of air travel has been increasing
over the world.
The operational boundaries of modern ATC systems are being
pushed as worldwide air traffic density increases.
To keep up with the rising need for accommodating future
expansion in air traffic, air navigation and air traffic management systems
must become increasingly complex.
Artificial intelligence (AI) provides a number of
applications for safer, more efficient, and better management of rising air
traffic.
According to the International Civil Aviation Organization's
(ICAO) Global Air Navigation Plan (GANP), AI-based air traffic management
systems may help address the operational issues posed by the growing volume and
variety of air traffic.
Simulation systems with AI that can monitor and advise the
activities of trainee controllers are already used in the training of human air
traffic controllers.
In terms of operations, the ability of machine
learning-based AI systems to ingest massive amounts of data may be used to
solve the complexity and challenges of traffic management.
Such technologies may be used to assess traffic data for
flight planning and route selection during the planning stages.
By detecting a wide range of flight patterns, AI can also
provide reliable traffic predictions.
AI-based ATC systems may be used for route prediction and
decision-making in en route operations, particularly in difficult scenarios
with little data.
AI can help with taxiing methods and runway layouts.
Additionally, AI-assisted voice recognition technologies may
help pilots and controllers communicate more effectively.
With such a wide range of applications, AI technologies may
help human air traffic controllers improve their overall performance by
providing them with detailed information and quick decision-making procedures.
It's also worth noting that, rather than replacing human air
traffic controllers, AI-based solutions have shown to be useful in ensuring the
safe and efficient flow of air traffic.
~ Jai Krishna Ponnappan
You may also want to read more about Artificial Intelligence here.
See also: Intelligent Transportation.
Further Reading
Federal Aviation Administration. 2013. Aeronautical Information Manual: Official Guide to Basic Flight Information and ATC Procedures. Washington, DC: FAA. https://www.faa.gov/air_traffic/publications/.
International Civil Aviation Organization. 2018. “Potential of Artificial Intelligence (AI) in Air Traffic Management (ATM).” In Thirteenth Air Navigation Conference, 1–3. Montreal, Canada. https://www.icao.int/Meetings/anconf13/Documents/WP/wp_232_en.pdf.
Nolan, Michael S. 1999. Fundamentals of Air Traffic Control. Pacific Grove, CA: Brooks/Cole.
