The APACHE project proposes a new framework to assess European ATM performance based on simulation, optimization and performance assessment tools that will be able to capture complex interdependencies between KPAs at different modelling scales (micro, meso and macro).In this context, the purpose of APACHE is threefold: - to evolve the Performance Scheme towards new methodologies and metrics capable of capturing with proportional detail the performance drivers of ATM to foster a progressive and performance-driven introduction of new operational and technical ATM concepts in line with SESAR; - to make an (initial) impact assessment of long-term ATM concepts with the new APACHE Performance Scheme, to measure the impact on ATM KPAs under different assumptions in line with the SESAR ConOps 2020+; and - to analyse the interdependencies between the different KPAs at the Pareto-frontier of the ATM performance, by finding the theoretical optimal limits for each KPA and assessing how the promotion of one KPA may actually reduce the performance of the other KPAs An initial performance assessment of new concepts of operations will be required, covering the new concepts t: free-routing in 2D (2DFR) and in 3D (3DFR) for airline operators; dynamic airspace configuration (DAC) for air navigation service providers (ANSPs); and dynamic demand and capacity balance (dDCB) for the Network Manager (NM). All these concepts will be analysed at EU-wide and/or functional airspace block (FAB) level combined under different scenarios and case studies. The optimization tools will be used to model the ATM performance drivers underpinning each of the the stakeholder’s business models, in particular regarding the optimization of processes for aircraft trajectory planning, sectorization planning and network safety planning. Assessment tools will be used to measure the level of KPA performances in the simulations. Tools will be provided by partners and initial versions are already available.

ATM performance results from the complex interaction of interdependent policies and regulations, stakeholders, technologies and market conditions. Trade-offs arise not only between KPAs, but also between stakeholders, as well as between short-term and long-term objectives. 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 KPIs 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 and evaluate their potential to inform the development of new indicators and modelling approaches; 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 and evaluate their potential 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 multi-dimensional performance assessment and decision making for both monitoring and management purposes.