Community Research and Development Information Service - CORDIS


INTUIT Report Summary

Project ID: 699303
Funded under: H2020-EU.

Periodic Reporting for period 2 - INTUIT (Interactive Toolset for Understanding Trade-offs in ATM Performance)

Reporting period: 2016-09-01 to 2017-02-28

Summary of the context and overall objectives of the project

The ongoing ATM modernisation programmes, including SESAR, build on ICAO Global ATM Operational Concept, one of whose cornerstones is performance orientation. A performance-based approach is defined by ICAO as one based on: (i) strong focus on desired/required results; (ii) informed decision making, driven by the desired/required results; and (iii) reliance on facts and data for decision making. While a lot of effort has traditionally been devoted to the development of microscopic performance models, there is a lack of useful macro approaches able to translate local improvements or specific regulations into their impact on high-level, system-wide KPIs. The goal of INTUIT is to explore the potential of visual analytics, machine learning and systems modelling techniques to improve our understanding of the trade-offs between ATM KPAs, identify cause-effect relationships between indicators at different scales, and develop new decision support tools for ATM performance monitoring and management. The specific objectives of the project are:
1. to conduct a systematic characterisation of the ATM performance datasets available at different spatial and temporal scales;
2. to propose new metrics and indicators providing new angles of analysis of ATM performance;
3. to develop a set of visual analytics and machine learning algorithms for the extraction of relevant and understandable patterns from ATM performance data;
4. to investigate new data-driven modelling techniques able to provide new insights about cause-effect relationships between performance drivers and performance indicators;
5. to integrate the newly developed analytical and visualisation functionalities into an interactive dashboard supporting multidimensional performance assessment and decision making.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The work done during the first year of the project (1 March 2016 - 28 February 2017) includes:
• producing the Project Management Plan and other management documentation,
• gathering the different datasets that will be analysed throughout the project,
• selecting a number of case studies based on the research questions previously identified,
• launching the first of these case studies, focused on the analysis of the drivers of airlines' route choice decisions and the influence of these decisions on ATM performance.

The work dealing with data acquisition and quality assessment has been documented in deliverables D2.1 Performance Data Inventory and Quality Assessment and D2.2 Qualitative analysis of performance drivers and trade-offs.

The main outcomes documented in D2.1 are:
• the INTUIT data repository, which provides all Consortium members with access to a variety of datasets;
• data quality factsheets, which describe the characteristics of the different datasets (indicators covered, spatial and temporal resolution, etc.);
• a performance data guide, which helps identify the most suitable database to find the desired performance data.

D2.2 includes a set of research challenges grouped into seven threads:
• ATCO workload, addressing the relationship between airspace complexity and capacity as well as the interrelationship between complexity in different airspace sectors;
• Cost-efficiency, where we will focus on the interdependencies between environment, capacity and cost efficiency;
• Uncertainty, dealing with the effects of uncertainty on the performance of the network;
• Safety, addressing the question of how safety may be influenced by the performance targets in other KPAs;
• Equity and access, focused on the definition of quantitative indicators to assess access and equity;
• New KPIs, addressing those areas where indicators are insufficiently developed, in order to propose significant metrics for future SES reference periods;
• KPI visualization, which aims to improve current dashboards to enhance their usefulness as decision support tools for different ATM stakeholders, by increasing the level of spatial and temporal disaggregation and exploring new forms of data visualisation.

Taking these research challenges as a starting point, a combination of visual analytics and machine learning techniques are being used to study interdependencies between KPAs/KPIs. The work has been structured in the form of case studies that address one or more of the research questions outlined above. During the first year of the project, a first case study has been conducted which has addressed the trade-offs between cost-efficiency, capacity and environment, by studying the factors that determine airlines' route choice decisions and the influence of these decisions on ATM performance. The case study has comprised two main stages:
• First, airline route choices have been studied by means of different visual analytics techniques to extract temporal and spatial patterns and identify relevant variables to be considered in the development of route choice predictive models.
• In a second stage, we have developed a variety of machine learning models to predict airline route choices and evaluate the performance trade-offs arising from these decisions.

During the second year of the project, several other case studies will be launched, which will follow a similar approach, based on the synergistic combination of visual analytics and machine learning techniques. Finally, the visualisation tools and the new modelling approaches developed in the context of these case studies will be integrated into a prototype ATM performance monitoring and management dashboard.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

After this first year, INTUIT has analysed the main public and restricted-access databases regarding performance data in the ECAC area. This work, documented in deliverables D2.1 and D2.2, will be helpful for other research projects in order to select the data necessary for their research. The project has also performed a thorough literature review and an extensive stakeholder consultation to select the most relevant research threads in the field of ATM performance modelling, and has selected a set of research questions focused on the development of the performance approach followed by the Performance Review Unit (PRU) towards RP3.

The outcomes of this work, which is currently ongoing and will be completed during the second year of the project, are expected to impact positively on the competitiveness and sustainability of the European aviation sector at different levels. The methods and tools developed by the project will help set effective mechanisms in order to encourage ANSPs to improve performance and lead to a better tuning of local regulatory targets, by providing a deeper understanding of the high-level impact of local improvements or specific regulations. The contributions to the improvement of the performance of the ATM system will ultimate benefit all the stakeholders of the aviation sector. Additionally, the INTUIT partners are taking advantage of the project to strengthen their position in the aviation and ATM market, in particular to take a leading position in the application of data analytics to ATM performance analysis. The first project outcomes have been positively valued by ATM community, which makes us confident that the INTUIT results will feed into the subsequent stages of the R&I lifecycle and will be the basis for the future development of marketable products and services for ATM performance monitoring and management.
Record Number: 195105 / Last updated on: 2017-02-17
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