Fewer delays, fewer emissions, lower fuel costs, less noise – remarkably, it’s by targeting times when aircraft are still on the ground that the global aviation industry could make big strides in achieving all of these benefits.
Queen Mary University of London (QMUL) is leading development of a new IT-based system designed to maximise efficiency and minimise bottlenecks when planes are taxiing to runways – reducing hold-ups for passengers, cutting airline running costs and helping to tackle air quality and other environmental issues in and around airports.
With a host of industry partners on board (including two international airports and a world-leading airline), the system could be a game-changer that eases some of the intense pressure on aviation infrastructure as skies grow even busier in the years ahead.
Congestion – A Key Question
It’s no comfort to anyone faced with a delayed or disrupted flight but the smooth, seamless running of a busy airport is a big challenge. Take the headache of getting planes from boarding gate to runway as fast and efficiently as possible. Sounds simple? In fact, taxiing layouts can be complex, confusing and prone to snarl-ups as the curse of congestion strikes.
“With safety still the overriding priority, our system will deliver big advantages over existing tools”Dr Michal Weiszer, QMUL
The problem is set to get worse, with many airports already operating near full capacity and air traffic forecast to grow 150% by 2030. Nor does it just affect passengers. “On short-haul flights, taxiing can account for 6% of fuel consumption,” says Dr Jun Chen of QMUL. “Unnecessary fuel burn is an unwelcome cost for airlines. Then there are the environmental implications – plus the disruption to flight schedules due to inefficient taxiing.”
Dr Chen is Project Director on a 3-year EPSRC-funded initiative that aims to put inefficient taxiing to flight. TRANSIT is developing a unique decision-support system for air traffic controllers that’s fully configurable to the needs of individual airports. Calculating the fastest, most fuel-efficient taxiing route for each plane, plus optimum speeds, spacing and aircraft sequencing, it will integrate a range of data, cutting-edge modelling & simulation tools and new algorithms to generate realistic recommendations suited to every situation.
- Internal aircraft-specific factors such as engine performance, airframe aerodynamics and landing gear behaviour.
- External factors such as current weather conditions and air-traffic volumes.
“With safety still the overriding priority, our system will deliver big advantages over existing tools,” explains Dr Michal Weiszer. “Those tools tend to be based on average taxiing times and unrealistic assumptions that aircraft will maintain a constant speed. In addition, the instructions they generate can be hard for pilots to implement because they don’t take account of specific aircraft types, different airport layouts and constant fluctuations in airport conditions. By gathering data from all kinds of sources, possibly including extensive sensor networks around the airport in the future, our system will be different.”
From Control Tower to Cockpit
As with any technology designed for use in high-pressure environments, success will depend on how straightforward the new system is to interact with. “It’s crucial to ensure that information and advice for air traffic controllers and resulting instructions for pilots are presented in the right way,” says Jun Chen. “Everything must be integrated into existing systems, instrumentation and displays; instructions must be realistic, reliable and easy-to-follow; and everyone needs to feel comfortable and confident using the technology.”Securing aviation industry buy-in is absolutely critical. That’s why the TRANSIT team is broadly based: apart from four UK universities (QMUL, Cranfield, Sheffield and Stirling), partners include Air France KLM, Manchester Airport, Zürich Airport, BAE Systems and Rolls-Royce, plus software firm Simio. “In this industry, the push to cut costs, drive up efficiency and boost passenger satisfaction is relentless,” Michal Weiszer comments. “On the other hand, it’s vital that our system doesn’t appear too radical. Working with the industry means stakeholders can provide direct feedback on the system’s design and content, and can advise on practical issues surrounding its eventual phased introduction at airports.”To provide the necessary level of trust in the system, the team will test the new technology using Cranfield’s aircraft simulator and data from Manchester Airport. It’s hoped that these tests will be conducted using real commercial airline pilots and can be extended to Hong Kong International Airport – one of the world’s busiest. If the system can prove its potential somewhere like Hong Kong, which handles over 70 million passengers a year, it will make a huge contribution to securing the credibility essential to eventual rollout.
A Trip into the Future
It’s estimated that the system could cut taxiing time and associated fuel costs by up to 50% in some cases. More broadly, the project is underlining the key role that technology can play in enabling better use of existing airport infrastructure.
“Everyone needs to feel comfortable and confident using the technology”Dr Jun Chen, QMUL
According to the team, airports could start applying advances and insights secured by TRANSIT within 1 to 5 years, with the full system moving towards implementation over the following decade. “Aviation is a very strictly regulated industry,” Jun Chen observes. “It will inevitably take time to evolve away from taxiing rules now in place and to enable airports, airlines, passengers and local residents to enjoy the benefits of a new way of doing things.”
And there’s yet another dimension to TRANSIT’s potential significance. Thanks to its anticipated incorporation of sophisticated sensor technology in the future to help determine the precise position of taxiing aircraft and ensure they stay on course, the system could represent an important step towards completely automated taxiing where pilot involvement is eliminated. “Airports could see some of the first widespread deployments of autonomous vehicle technology,” Dr Chen confirms. “A confined environment like an airport, where lots of safety features and failsafe systems can be incorporated into the infrastructure, would be a perfect place to demonstrate the potential of vehicle autonomy. For TRANSIT, the sky’s the limit.”
- Multi-objective Fuzzy Rule-Based Prediction and Uncertainty Quantification of Aircraft Taxi Time.
- A Type-2 Fuzzy Modelling Framework for Aircraft Taxi-Time Prediction.
- An Online Speed Profile Generation Approach for Efficient Airport Ground Movement.
- A Rolling Window with Genetic Algorithm Approach to Sorting Aircraft for Automated Taxi Routing.
- Preference-based Evolutionary Algorithm for Airport Surface Operations.
- A Fuzzy Approach to Addressing Uncertainty in Airport Ground Movement Optimisation.
Dr Jun Chen
Dr Michal Weiszer