Improving airport performance is at the heart of the SESAR’s airport operations centre (APOC)* solution. By providing access to real-time data from various data sources of different APOC stakeholders, airports can make accurate predictions about their operations, including passenger movements.
As part of its contribution to SESAR, Eurocontrol launched a study early 2016 to identify the key APOC processes that could be enhanced by data-driven predictions and by machine learning algorithms (DDP&ML) with a view to provide a case study illustrating how shared data and advanced analytics can be used successfully to support the development of APOC.
The selected consortium, led by University College London (UCL) together with University of Virginia and Heathrow Airport, provides the optimum balance between analytical and operational expertise while ensuring access to the best possible available data.
More than a quarter of all passengers passing through Heathrow are making a flight transfer, so it is critical to ensure that all the processes involved in these connections are optimised. The study team therefore focused on the prediction of passengers’ transfer journey using various databases and applying a classical and regression trees (CART) technique to build the predictive model.
A live trial took place during 8 hours on 19 July, providing 2-hour window predictions every five minutes. The predictions were checked visually with the camera looking at the specific area in Terminal 5 and are being further analyzed against actual data.
The live trial demonstrated clearly that such techniques can provide accurate forecasts (together with prediction intervals) which can help flow managers better understand the key factors that influence passengers’ connection time as well as help improving passenger services in real time. In addition, better predictions of passengers’ transfer activities can also improve the accuracy and stability of the target-off-block-time (TOBT), which is critical for optimised air traffic flow management in Europe. The live trial also highlighted how all stakeholders benefit from having the joint conversation around the availability, use, and sharing of the data. The output from the machine learning technique offered insights beyond what any single stakeholder group could learn.
The final report will be available at the end of September.
Tom Garside, Head of Integrated Planning & Performance at Heathrow, said: “This study has demonstrated how the latest analytical techniques, using real-time data, can be used to improve the experience of connecting passengers, and to support aircraft punctuality. We are now looking at how we deploy this approach into live operations and to apply similar techniques to other airport processes”.
The APOC solution is part of the broader SESAR Solution that sees the integration of the airport operations plan into the network operations plan. Plans are underway to deploy this broader solution across Europe as part of the European Commission’s Pilot Common Project.
*Within SESAR Project 06.03.01 / OFA05.01.01.
