In short




2016-03-01 > 2018-02-28


EUR 998 125


EUR 998 125



Visualising performance trade-offs in ATM

The performance of the ATM system results from the complex interaction of interdependent policies and regulations, stakeholders, technologies and market conditions. Trade-offs arise not only between key performance areas (KPA), but also between stakeholders, as well as between short-term and long-term objectives.

INTUIT addressed the need for suitable performance modelling techniques and explored the potential of visual analytics and machine learning to improve our understanding of the trade-offs between KPAs and identify cause-effect relationships between indicators at different scales.

As a first step the project carried out a systematic characterisation of available ATM performance datasets, producing a data inventory that can serve as reference for future research activities. Then, a detailed review of the literature on performance interdependencies and a consultation process with ATM stakeholders led to the definition of a research agenda at the intersection of ATM performance and data science. 

From the list of research questions included in this research agenda, three use cases were selected to demonstrate the potential of the investigated techniques. In the first case study, airline route choices were analysed and a model was developed to estimate the impact of changes in route charges on the overall ATM performance. The second case study showed how flight-inefficiencies within a particular area control centre are correlated with flight properties derived from both the flight plan and the ideal route, such as heading, altitude and airspace crossed. The third case study demonstrated how ATM performance can be measured at a finer spatial and temporal level and investigated the relationship between sector configurations and air traffic flow management (ATFM) regulations.

Interactive visual interfaces were developed for all use cases to enable human-information discourse and to facilitate interpretation and communication of the modelling results.


Mapping of ATM performance datasets

Better understanding of interdependencies between KPAs

Visualisation tools for performance monitoring and analysis

Project Members:  Nommon Solutions and Technologies (Coordinator), Advanced Logistics Groups, Fraunhofer Gesellschaft,Universidad Politecnica de Madrid, Transport & Mobility Leuven

This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 699303

European Union