TRANSIT: Towards a Robust Airport Decision Support System for Intelligent Taxiing

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.

The immediate impact of TRANSIT includes better understanding of causes, behaviour and consequences of uncertainties, and the dynamic nature of ground movement obtained by the analysis of real-world data and simulation. Such knowledge can be used in short term (1-5 years) by airports/airlines in their day-to-day planning. However, the vision of TRANSIT, through the investigation of modelling techniques and optimisation methods, is to develop a basis for future decision support and flight deck automation systems for ground movement. Such a system, developed and implemented in the long term (5-15 years) will be of benefit to industry, environment and society. Pathways to impact are designed to deliver impacts by exchanging knowledge between academics and industry, educating the next generation of researchers, exploring future research directions, delivering public awareness, and in particular fostering economy performance and improving society in the following areas:

Quality of life: Taxi time will be optimised considering uncertainty in times, detailed taxi speeds and other operating conditions producing two benefits: 1) more precise and robust taxi schedules, which will reduce the chances of congestion and therefore subsequent delays; 2) Reducing the time spent on taxiing. Both of these benefits will contribute to the quality of life of passengers as they pass through the airport.

Environment: Optimising airport ground movement with regard to fuel consumption will decrease the amount of fuel burnt during taxiing, resulting in lower emission of greenhouse gases and associated pollutants in the immediate vicinity of airports. This is an important consideration as, while taxiing is only a small portion of the overall journey, jet engines burn very inefficiently at low speed and therefore make a substantial contribution to the total emissions.

Health: Reduced taxi time and optimised aircraft engine performance, means aircraft engines are running for a shorter period of time with lower fuel consumption, decreasing noise and pollutants, benefiting residents in the immediate vicinity of airports.

Policy: The environmental impact of the proposed research directly helps the UK to fulfil its national and international commitments. Decrease in the emission of greenhouse gases aligns with the Climate Change Act 2008, which aims for the net UK carbon account for 2050 to be 80% lower than 1990. Furthermore, the European White paper 'Roadmap to a Single European Transport Area' calls to reduce greenhouse gas emissions to 20% of 2008 levels, and Flightpath 2050 envisions emission-free taxiing by 2050.

Cost reduction for passengers, airlines and airports: Decreasing the number and length of delays and dynamic decision making for different airport operational scenarios will have a direct impact on reducing costs, in terms of wasted time or missed connections for passengers, and in terms of costs of using airport infrastructure, aircraft and crew costs for airlines. Preliminary studies on Active Routing framework indicate a reduction of up to 50% in both taxi time/fuel consumption.

Competitiveness of air transport industry: Minimising transit time, fuel consumption and costs are key factors in an already highly competitive industry. Not only is it important for the aviation industry to remain competitive with alternative modes of transport, but also it should provide a reliable service, as a flight is part of a passenger's overall journey. Therefore, reducing delays at an airport is an important milestone in effectively transporting passengers from door to door, over an ever more interconnected transportation network.

Safety: While conflicts between taxiing aircraft usually do not pose a serious safety hazard, they result in costly damage and interrupted operation. By providing largely conflict-free taxi routes, generated by the proposed optimisation framework based on full-4DTs, this risk can be substantially reduced.