Air traffic management
Right: The digital control tower at NATS’ Swanwick site is approximately 115km from the runway it monitors at London City Airport.
Below: There are 14 HD display screens in NATS’ Swanwick control room.
airspace above it, overlaid with data that ATCs would ordinarily have to look away to retrieve, is a huge step for aforementioned efficiency and safety. Bringing AI and machine learning into that realm could go even further – continually assessing the environment to identify risks the human eye might miss. “AI can be trained to monitor the full 360º for specific things that we need the controller to be aware of,” Taylor says. “That means controllers don’t have to be looking in that direction as part of their scan – the system can flag that they need to now look somewhere else, that an important or safety-critical decision or monitoring is required.”
The benefit of this data-driven, digitised capability stretch far beyond just seeing aircraft land and take off – it reaches across the entire turnaround process. It may also advance the role of others at the airfield too, even where there is already a collaborative decision-making system (A-CDM). Thanks to digital towers and AI, controllers’ ability to see, in an instant, the ground status thanks to the bank of cameras, and the enhanced visuals that come with them adds significantly to their situational awareness.
Taylor says that even at the better connected sites, A-CDMs don’t always provide a view of how things are really progressing. “Because what you’re relying on is that the ground handling agents, for example, are updating the target off-block times,” he notes. “They could change at the very last minute because they’ve pulled them behind, which becomes a bit of a clunky process as you get an update at the point they update the data.” Instead, cameras and AI are feeding back information by the millisecond, rather than when it’s manually updated. This, he says, provides more granular KPIs and greater awareness, thus facilitating more informed decision making. The fusing together of data, AI and machine learning with human handlers is likely to prove to be one of the biggest developments of ATC in aviation’s almost 120 year history. Taylor believes putting people at the top of a tower surrounded by glass, and asking them to get on with it is becoming consigned to history. “Today’s approach is to give them digital enhancements,” he says.
19.6%
The projected compound annual growth rate of the global remote tower market
between 2022–27. However, it will still be relatively small, in comparison, valued at $600m.
ResearchAndMarkets.com 50
Project Bluebird is an effort to bring all these elements together, safely, by working with controllers to understand how they make decisions so that these behaviours can be taught to AI systems. It wants to address the ethical questions that might raise too, such as “where the responsibility lies if a human-AI system makes a mistake, how to build a system that is trusted by humans, and how to balance the need for both safety and efficiency”, the Alan Turing Institute says.
The evolution of digital capabilities and AI in
ATC is one that could revolutionise the way aviation is conducted. From providing decision-critical information for on-the-ground and in-air operations, to continually monitoring for risks that controllers might miss if a unique set of circumstances arise – the potential is almost limitless. The way ATC is an area continuously in flux, developing and progressing as the new technologies are introduced, and will change further in the years to come. For now, AI is a new frontier, one that will excite and raise questions as we continue on a path towards it. ●
Future Airport /
www.futureairport.com
NATS
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