This project emerged from the Research Councils' Energy Programme Sandpit in Airport Operations held at Shrigley Hall, Cheshire between 10-14 November 2008. It represents a wide ranging multi-disciplinary and cross-institutional initiative to exploit recent research advances in automated search methodologies and decision support techniques for air operations (and other related areas). This project will open up a range of exciting and ambitious research directions in the crucially important area of airport operations. The proposed programme of research will build integrated computational models of four key airport operations: Take-off scheduling, Landing Scheduling, Gate Assignment and Baggage flow. The project will explore how to build computational models that represent the integration of these problems and it will explore how to develop effective multi-objective search methodologies which will employ the models. At the moment, these operations are addressed in an isolated (and often manual) way. The ultimate goal is to develop innovative search methodologies which are able to operate from a global perspective in order to provide airport operators with a much higher level of computer aided decision support than is available today. Integrating these four operations and exploring new and exciting ways of generating high quality solutions to the integrated problem is the broad basic aim of the proposal. We will work closely with colleagues at Manchester and Zurich airports to ensure that we have continuous access to real world expertise and data. The proposal brings together a balanced inter-disciplinary team of scientists and engineers to investigate a series of novel research challenges with the overall goal of underpinning the development of tomorrow's airport operations decision support systems.

This project emerged from the Research Councils' Energy Programme Sandpit in Airport Operations held at Shrigley Hall, Cheshire between 10-14 November 2008. It represents a wide ranging multi-disciplinary and cross-institutional initiative to exploit recent research advances in automated search methodologies and decision support techniques for air operations (and other related areas). This project will open up a range of exciting and ambitious research directions in the crucially important area of airport operations. The proposed programme of research will build integrated computational models of four key airport operations: Take-off scheduling, Landing Scheduling, Gate Assignment and Baggage flow. The project will explore how to build computational models that represent the integration of these problems and it will explore how to develop effective multi-objective search methodologies which will employ the models. At the moment, these operations are addressed in an isolated (and often manual) way. The ultimate goal is to develop innovative search methodologies which are able to operate from a global perspective in order to provide airport operators with a much higher level of computer aided decision support than is available today. Integrating these four operations and exploring new and exciting ways of generating high quality solutions to the integrated problem is the broad basic aim of the proposal. We will work closely with colleagues at Manchester and Zurich airports to ensure that we have continuous access to real world expertise and data. The proposal brings together a balanced inter-disciplinary team of scientists and engineers to investigate a series of novel research challenges with the overall goal of underpinning the development of tomorrow's airport operations decision support systems.

There is a need for inspection systems that are able to detect explosives (or drugs) hidden in for example luggage. These systems are most efficient if they can inspect the object without having to investigate by hand. e.g. a person does not have to search each piece of luggage or container. Explosives almost universally comprise hydrogen, carbon, nitrogen and oxygen is different ratios. A system that will detect elements like these is based on sending a beam of neutrons into the system. The different elements will emit gamma rays of different energies which are unique to the isotopes concerned. These gamma rays can be measured accurately with a germanium gamma-ray detector and hence the amount of each element determined. This information can then be used to determined the ratios of the four elements and hence whether explosives (or drugs etc.) are present. By using modern technology the germanium detector can also be used to make an image of the object under investigate, similar to an airport baggage scanner. In this case the gamma-rays and scattered neutrons will be detected simultaneously to make a clearer image. By the end of the project we hope to have demonstrated in the laboratory that these ideas are effective and to determine the potential sensitivity.

There is a need for inspection systems that are able to detect explosives (or drugs) hidden in for example luggage. These systems are most efficient if they can inspect the object without having to investigate by hand. e.g. a person does not have to search each piece of luggage or container. Explosives almost universally comprise hydrogen, carbon, nitrogen and oxygen is different ratios. A system that will detect elements like these is based on sending a beam of neutrons into the system. The different elements will emit gamma rays of different energies which are unique to the isotopes concerned. These gamma rays can be measured accurately with a germanium gamma-ray detector and hence the amount of each element determined. This information can then be used to determined the ratios of the four elements and hence whether explosives (or drugs etc.) are present. By using modern technology the germanium detector can also be used to make an image of the object under investigate, similar to an airport baggage scanner. In this case the gamma-rays and scattered neutrons will be detected simultaneously to make a clearer image. By the end of the project we hope to have demonstrated in the laboratory that these ideas are effective and to determine the potential sensitivity.

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.