The aerospace algorithms making our skies cleaner
The smooth operation of a large airport is a complex business. With thousands of flights arriving and departing every day, a key concern for operators is limiting delays for aircraft and ensuring a good experience for hundreds of thousands of passengers.
Managing runways is key to this. Yet many UK airports have one or two runways to handle this capacity. We have all seen queues around motorway slip-roads. At airports, all arriving and departing aircraft also converge at the same place, the runway(s), and the key is to ensure that they are not all there at the same time.
Now imagine it matters what order the vehicles are queued in; if you can get the order right then the traffic can flow faster, queues go down or never appear. For example, maybe traffic travels faster if it is all cars or all lorries in a queue than alternating lorries and cars, so you want to group the lorries together, despite the overtaking needed to achieve that. Airport runways need to group the bigger aircraft together if they want to get a good throughput, while enabling overtaking. Plus, complex runway rules, such as the equivalent of slowing traffic if a vehicle follows another with a similar colour, or allocating queue places to specific vehicles, greatly increase the challenge.
The solution to this tricky problem is good sequencing aircraft and managing the queue. By smoothing the flow, some aircraft may even set off later, but end up taking off earlier than they would have done. Not only that, but the engines are started later, so they save on fuel costs and emissions.
This sounds like a perfect solution, but it hits a few problems. Firstly, the world isn’t predictable, so you want aircraft to arrive at the queue with a bit of slack time to allow for unexpected delays. Secondly, it’s a hugely complex problem for airports, and not one which humans can solve in their heads when things get busier.
This is where Dr Jason Atkin and his colleagues at the university’s Institute for Aerospace Technology come in. As members of the Computational Optimisation and Learning lab in the School of Computer Science, they have created programmes which are used at Heathrow (from 2013) and Geneva (from 2016) airports, looking at when aircraft plan to set off towards the runway(s), considering what will happen there, and suggesting delays to some of them to reduce congestion at busy times. This prevents thousands of tonnes of CO2 emissions each year and dramatically reduces delays.
"British Airways estimated that this change would save them £2m in fuel costs each year, as well as cutting CO2 emissions by 16,000 tonnes."
The systems use algorithms to predict Target Take Off Times (TTOT) for aircraft based upon when airlines say aircraft will be ready. They then allocate Target Start-Up Approval Times (TSAT) to these aircraft, telling them when they should actually start (e.g. applying start-up delays to some of them). Removing runway delays makes take-off times more predictable. At Heathrow, Target Take Off Time accuracy has been improved from an average of 8.7 minutes to 30 seconds per flight, in turn enhancing the efficiency of the control of airspace and enabling faster recovery from disruptions.
Aircraft also spend less time in the runway queue, lowering fuel burn and associated emissions. At London Heathrow, British Airways estimated in a trial that single engine taxiing, enabled by knowing the TTOT, would save them £2m in fuel costs each year, as well as cutting CO2 emissions by 16,000 tonnes and SO2 (Sulfur dioxide) by 4,200kg.
Dr Atkin said: “Creating sufficiently detailed and realistic models of airports is vital, including the ways in which aircraft block and delay each other at the stands, as well as solving the runway-sequencing problem itself.”
The Heathrow work received funding from Heathrow Airport and NATS (formerly National Air Traffic Services Ltd) the UK’s leading provider of air traffic control services. The Geneva algorithm was integrated into the system of ADB Safegate Airport Systems. The algorithms contributed towards both airports achieving European aviation A-CDM compliance.
Current work by the team is also being used to help reduce carbon emissions during flights too. In a separate project, Dr Atkin and colleagues are part of a consortium, led by Ampaire - a leader in hybrid-electric aviation - studying the feasibility and advantages of short-haul hybrid-electric passenger flights. The 2ZERO (Towards Zero Emissions in Regional Aircraft Operations) project uses the university’s extensive experience in air transportation system modelling and simulation (M&S) as well as electrification of aviation and systems integration.
Utilising new aircraft types effectively requires an understanding of the effects of operational and sizes differences of aircraft. They are leading the M&S activities, working with airline and airport partners, to assess the impacts on costs and efficiency of different operating modes, rostering choices and resource usage, to ensure that these greener aircraft can be used as effectively as possible, encouraging their earlier adoption.
Other partners involved in the government-backed £5m project include Rolls-Royce Electrical, University of Nottingham, Loganair Ltd, Exeter and Devon Airports Ltd, Cornwall Airport Ltd, Heart of the Southwest Local Enterprise Partnership (HotSWLEP), and UK Power Network Services.
"The project is a major demonstrator to show how we can move towards net zero emissions in regional aviation."
In August the first test flight, using Ampaire’s six-seat Electric EEL aircraft, took place between Exeter and Newquay, a distance of 85 miles. The EEL, a modified six-seat Cessna, features a battery-powered electric motor at the front and conventional combustion engine at the rear, enabling a reduction in emissions and operating costs by as much as 30%. The aircraft flew using a combination of battery and piston power, collecting valuable data to monitor fuel savings, efficiency and noise.
Dr Atkin said: “This project provides an opportunity to utilise our research to evaluate the effects of these revolutionary changes to air travel. The inclusion of airline and airport partners will ensure that the models and evaluations are realistic – guiding decision makers into how to best take advantage of these innovations in future.”
The team’s work looks at the logistics of the support systems needed to enable electric aviation – including the necessary charging and energy storage infrastructure, as well as things like staff-rostering. The objective is to develop an optimised electric aviation ecosystem, including aircraft, airports, power distribution and storage.
He added: “The project is a major demonstrator to show how we can move towards net zero emissions in regional aviation. Our modelling and simulation research in this project utilises airport, airline and aircraft information to produce realistic and integrated models to evaluate how airspace, airports and aircraft could be used.”
Dr Jason Atkin
Dr Jason Atkin is Associate Professor in the Computational Optimisation and Research Lab, School of Computer Science, Faculty of Science