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

Lead Research Organisation: University of Lincoln
Department Name: Lincoln School of Engineering


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.

Planned Impact

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.


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Weiszer M (2020) Multi-objective routing and scheduling for airport ground movement in Transportation Research Part C: Emerging Technologies

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Weiszer M (2018) Preference-based evolutionary algorithm for airport surface operations in Transportation Research Part C: Emerging Technologies

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Zhang T (2020) The feasibility of Follow-the-Greens for 4-dimensional trajectory based airport ground movements in Transportation Research Part C: Emerging Technologies

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Zhang T (2018) An online speed profile generation approach for efficient airport ground movement in Transportation Research Part C: Emerging Technologies

Related Projects

Project Reference Relationship Related To Start End Award Value
EP/N029496/1 01/07/2016 31/05/2017 £316,421
EP/N029496/2 Transfer EP/N029496/1 01/09/2017 30/04/2021 £201,364
Description -Preliminary Trials
(1) We developed an aircraft simulator interface for testing ground movement operations. This enabled testing previous approaches which confirmed deviations in following the instructions by pilots. This also opened up collaboration with Safegate company on guidance and control systems leading to a new PhD project on this topic.
(2) We have integrated the detailed aircraft ground movement model with detailed airport digital maps to generate full 4-dimensional trajectories. We found out that the slope of airport taxiways can have a significant impact on fuel efficiency during taxiing.
(3) We have integrated the taxiing planning module with the guidance module using the 'follow-the-greens' concept. We found out that these two usually isolated systems need to be designed together to achieve the best time and fuel efficiency.
Exploitation Route (1) Further collaboration with BAES Systems (project partner) has been laid down to utilise the routing and scheduling results for their flight deck automation projects.
(2) A further collaborative project supported by EPSRC IAA QMUL, AVISU and National Air Traffic Services has been awarded Feb 2020 and will start in June 2020.
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Education,Environment,Transport

Description Simulation platform for airport ground movement
Amount £14,474 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 09/2018 
End 04/2020
Title Airport Ground Movements Simulation Platform 
Description The research team at QMUL has developed a simulation platform for airport ground movements. This platform is capable of handling airport layout data, actual movement data, traffic demand and sequencing, and taxi speeds/safety separations under different conditions, generating virtual traffic, performing statistical analysis, and outputting 2D animation and Key Performance Indices (KPIs) linked to risk and efficiency. The functionalities of the above simulation platform for airport ground movement have been extended to include an integrated multi-objective optimisation engine. This platform is capable of processing traffic surveillance data, simulating different operational concepts and presenting results in a user-friendly manner. The platform renders airport operators making quantifiable decisions based on statistical analysis and Key Performance Indices (KPIs). 
Type Of Material Improvements to research infrastructure 
Year Produced 2020 
Provided To Others? No  
Impact The future aviation market will operate very differently with step changes in technology, automation and consumer behaviour. Autonomous technologies, including Single Crew Operations (e.g. autonomous taxiing) and Smart/Connected/Efficient Sub-systems, are at the centre of this change. To establish these emerging technologies in the market place, it is pressing to demonstrate the safety and efficiency of their integration with existing traffic control through simulation, enabling the public, industry and government to make informed decisions to guide the emergence of automation. The developed tool facilitates simulation of airside operations incorporating intelligent/autonomous taxiing to quantify the benefit compared to baseline scenarios. With AVISU and previous EPSRC IAA support, the research team at QMUL has achieved the following outcomes so far: (1) 1 Proof of Concept project has been successfully completed using one of AVISU's selected airport customers - Jakarta International airport (Soekarno-Hatta); (2) AVISU is now in the process of purchasing the pending IPs arisen from the previous EPSRC project; (3) QMUL has successfully engaged with the biggest UK player in Air Traffic Control - NATS, to further develop the simulation platform as outlined in this proposal, with significant cash and in-kind contribution from NATS. 
Description Featured Article on Ground Handling International 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact An article introducing TRANSIT has been published in Ground Handling International magazine, which has been regularly delivering up-to-date information to all those who are involved in the ground handling business since 1995.
Year(s) Of Engagement Activity 2016