Through machine learning, mathematical modelling and optimisation techniques, the team hopes to reduce passenger delays, unlock shorter routes, lower emissions and alleviate the workloads of air traffic controllers by making the dynamic airspace configuration process automated and more flexible.
The €2m SMARTS project, funded by Horizon Europe, is led by Centro de Referencia de Investigación, Desarrollo e Innovación ATM, A.I.E. (CRIDA) with support from researchers from Lancaster University Management School, NATS, the German Aerospace Center, Eurocontrol, Enaire, and Ecole Nationale de l’Aviation Civile (ENAC).
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In a statement, Professor Guglielmo Lulli from Lancaster University Management School said: “There are around 8,000 aircraft carrying 600,000 people across UK skies every day – but with no marked lanes above our heads, it’s hard to envisage how complicated the air travel system is, and how complex a challenge it can be for teams to manage on the ground.
“Airspace is divided into sections that are managed by individual air traffic controllers, responsible for their own particular regions. Dividing up these airspace sectors is quite a manual task, and options for how they are divided is limited by a small number of possible configurations. However, getting the sectors right is crucial as the decision impacts passenger delays, air traffic controllers’ workload, and emission savings.
“By redesigning how air space sectors are configured will not only ensure a system that is more flexible to unlock the right amount of capacity at the right moment, with maximum efficiency – but will also ensure air traffic controllers can handle the associated workload comfortably.
“While automation has been explored in this area before, this project is the first to attack the airspace design and configuration problem at its very core – by redesigning the elementary airspace components which make up our airspace sectors.”
Enabling additional airspace capacity is a key priority for the industry to address the capacity challenges air travel currently faces and to cope with International Air Transport Association’s projected three per cent annual growth in air traffic, estimated to rise to almost eight billion passenger journeys per year by 2040.
By first conducting research to get a thorough understanding of the air traffic system, the SMARTS project team will create accurate predictive models for air traffic demand and capacity provision. Using machine learning and designing bespoke algorithms, they then will look to develop sector configuration plans that are resilient and dynamic to design, flex and adapt when needed.
Eva Puntero, Research and Development Engineer at CRIDA and SMARTS project coordinator, said: “We aim to devise a solution that is robust and will explicitly consider demand uncertainty. By taking full advantage of airspace potential, our system will require less air traffic controller resources per flight, will increase the productivity of the system and ultimately produce more cost-effective capacity management processes.”
The project began at the end of 2023 and will run until 2026.
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