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NATS Will Test AI at Heathrow to Reduce Weather-Related Flight Delays

Artificial intelligence could help reclaim lost landing capacity at Heathrow caused by low cloud cover and poor visibility.

(Image source: NATS)

NATS Holdings  (NATS), formerly National Air Traffic Services and the United Kingdom’s (UK’s) main air navigation service provider, is exploring the impact of artificial intelligence (AI) on air traffic at London’s Heathrow Airport. By processing ultra-high-definition (UHD), 4K resolution camera images with state-of-the-art AI and machine learning systems at a new £2.5 million ($3.3 million) “digital tower laboratory,” NATS is investigating whether these technologies can improve Heathrow’s landing capacity during low-visibility periods and reduce flight delays.

(Image source: NATS)

The digital tower laboratory – located inside Heathrow’s 87 meter (285 foot) tall control tower – was established to understand how emerging technologies can support both present and future air traffic operations. Twenty UHD cameras across the airport feed images into an advanced neural network framework developed by Ottawa-based Searidge Technologies, Inc.  called “ Aimee  ” that tracks aircraft movement and informs controllers when an aircraft has cleared the runway.

Learn more about AI
(Image source: NATS)

According to Searidge, Aimee, can overcome environmental challenges common to AI applications at airports, such as camera vibration and sensor shaking in mast installations. The neural network provides excellent probability of detection in all environmental and weather conditions, aircraft occlusion resolution, classification of detected objects, including easily distinguishing between stationary aircraft and vehicles, and detection of aircraft that are only partially visible in the video sensor field of view.

The impetus for the trial is an issue stemming from the control towers’ height and regional weather issues. Heathrow’s control tower is the highest in the UK and provides commanding views of the airport and surrounding landscape, but its height can also mean it disappears into low cloud, even when the runways below are clear.

Read more: The UK’s first digital air traffic control tower
(Image source: NATS)
(Image source: NATS)

In those conditions, controllers must rely on radar to know if an arriving aircraft has left the runway and add extra time between each landing to ensure safety, resulting in a 20% loss of landing capacity, delays for passengers, and knock-on disruption for the rest of the operation. “Safety is always our top priority and Artificial Intelligence is about supporting air traffic controllers. While they remain the decision makers at the heart of the operation, we can use it to provide new tools that help them make the best possible decisions and improve efficiency and safety,” says NATS Chief Solution Officer, Andy Taylor. “Right now we’re focusing on when the control tower is in low cloud, where I’m confident we can make a very positive difference, but I am convinced that this technology can totally revolutionize how air traffic is managed at airports around the world.”

SAE International event: AI & Machine Learning

From now until March, Aimee will study the behavior and patterns of more than 50,000 aircraft landing at Heathrow to ensure system accuracy. The findings from these nonoperational trials will be presented to the UK’s aviation regulator, the Civil Aviation Authority  .

NATS believes the system will help the airport reclaim all the lost capacity and is hoping to roll out the operational version of the system by the end of this year.

“We’re delighted to be working with NATS to bring this pioneering technology to the UK’s only hub airport. Our capacity challenges are unique to our operation and we’re always exploring new and innovative techniques to help us overcome these constraints and improve the passenger experience in a safe and resilient manner,” says Kathryn Leahy, director of operations at Heathrow Airport. “We’ll be keeping a close eye on this trial, as the technology could have a major role as we prepare for the expanded airport. We will watch how AI and digital towers could be used to monitor all three of the expanded airport’s runways in future.”

In addition to the work at Heathrow, NATS and Searidge are currently developing the world’s first “smart tower” prototype at Changi Airport in Singapore. Operational trials are planned to start there in late January.

William Kucinski  is content editor at SAE International, Aerospace Products Group in Warrendale, Pa. Previously, he worked as a writer at the NASA Safety Center in Cleveland, Ohio and was responsible for writing the agency’s System Failure Case Studies. His interests include literally anything that has to do with space, past and present military aircraft, and propulsion technology.

Contact him regarding any article or collaboration ideas by e-mail at This email address is being protected from spambots. You need JavaScript enabled to view it..

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    Transcript

    00:00:00 we're in the digital tower lab at Heathrow Airport in the control tower and we are currently sitting in front of the world's first 4k digital tower facility so while others are using digital technology to simply recreate a physical control tower we're using that technology along with serious software platform artificial intelligence to provide performance improvement so

    00:00:32 airports that are constrained by weather by physical infrastructure all of those can have a digital solution the control tower at Heathrow is 87 meters high it means it gives the controller's a great view of the airfield in normal conditions unfortunately it also means that those same controllers find themselves disappearing into cloud as soon as we experience low cloud days and

    00:01:01 that can mean that they can't see some or all of the view outside of the window and they are reliant then on radar systems that results in a reduced arrival flow of traffic while we space the inbound aircraft further apart the solution that we are testing for operational deployment here in the lab will use AI to determine that the aircraft has fully vacated the runway

    00:01:27 strip and will indicate to ATC that that is the case this means that we can reduce the final approach basing back to a normal operation and that means reduce delays for the airport airlines and the flying public the tool itself is there as a support tool to enhance the performance a sister controller reduce their workload and make the operation safer

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