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EPSRC Reference: EP/N029496/1
Title: TRANSIT: Towards a Robust Airport Decision Support System for Intelligent Taxiing
Principal Investigator: Chen, Dr J
Other Investigators:
Lone, Dr MM
Researcher Co-Investigators:
Dr M Weiszer
Project Partners:
Air France KLM BAE Systems Beihang University
Manchester Airport Plc Queen Mary University of London Rolls-Royce Plc
Simio LLC University of Bristol Zurich Airport
Department: Lincoln School of Engineering
Organisation: University of Lincoln
Scheme: Standard Research
Starts: 01 July 2016 Ends: 31 May 2017 Value (£): 316,421
EPSRC Research Topic Classifications:
Artificial Intelligence Software Engineering
Transport Ops & Management
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
There is an imminent need to make better use of existing aviation infrastructure as air traffic is predicted to increase 1.5 times by 2035. Many airports operate at near maximum capacity, and the European Commission recognises the necessity to increase capacity to satisfy demand. In addition, inefficient operations lead to delays, congestion, and increased fuel costs and noise levels inconveniencing all stakeholders, including airports, airlines, passengers and local residents.

A critical issue is routing and scheduling the ground movements of aircraft. Although ground movement is only a small fraction of the overall flight, the inefficient operation of aircraft engines at taxiing speed can account for a significant fuel burn. This applies particularly at larger airports, where ground manoeuvres are more complex, but also for short-haul operations, where taxiing represents a larger fraction of an overall flight. It is estimated that fuel burnt during taxiing alone represents up to 6% of fuel consumption for short-haul flights resulting in 5m tonnes of fuel burnt per year globally. This project aims to investigate a decision support system which considers multiple factors to provide more robust taxiing routes.

Current decision support systems for routing and scheduling taxiing aircraft suffer from several limitations:

1) The only objective they consider is minimising taxi time, ignoring other important factors. These other factors include taking into account engine performance which is linked to fuel consumption, environmental impact and cost. Routes and schedules, which are efficient in terms of fuel and cost, are therefore compromised as a result of considering a one dimensional objective.

2) Airframe dynamics are not taken into account during planning of routes and schedules. Consequently, the taxing instructions issued may be hard to follow, making compliance with the allocated routes unrealistic.

3) Taxi time is typically based on average speeds of aircraft. This is an over-simplification meaning that any taxiing manoeuvre which falls outside the expected duration can affect the taxiing of other aircraft. Furthermore, if the approach of including overly conservative time buffers to absorb uncertainty is adopted, the resulting overall airport operating efficiency will be degraded.

4) It is difficult to specify taxiing speeds and heuristic rules for routing and scheduling systems as: they depend on airport layout and operational requirements, which can vary throughout the day according to the volume of air traffic. Consequently, routing and scheduling systems have to be reconfigured for specific airports and operational constraints.

5) Due to variability in taxi speed and over-simplistic models of aircraft, there is lack of understanding as to how much benefit can be achieved by automated routing and scheduling in real-world settings.

TRANSIT will directly address these limitations of current systems, to make better use of existing airport infrastructure and lessen the impact of the growing aviation sector on the environment. Multi-objective optimisation algorithms will be integrated with models of aircraft to balance the reduction of taxi time, cost and emissions. We aim to make the routing and scheduling system easily reconfigurable to any airport. The uncertainty will be directly incorporated in planning, resulting in robust taxiing, verified by pilot-in-the-loop trials.

TRANSIT aims to investigate such a system and its associated benefits in collaboration across a broad range of disciplines and fields (Engineering, Operational Research, and Computer Science) needed to tackle such challenging problem. Cooperation with leading industrial stakeholders, and consultation with established academics, ensure that the work is cutting edge while reflecting needs of the industrial partners.

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Organisation Website: http://www.lincoln.ac.uk