The Air Traffic Management (ATM) system is composed of a myriad of elements that interact with each other, including interdependent policies and regulations, stakeholders, technologies and market conditions. These interactions give rise to a number of properties characteristic of complex adaptive systems, such as non-linearity, emergence and adaptation, which make the ATM system intrinsically difficult to model one of the most challenging modelling problems: the assessment of the performance impact of new solutions at a system-wide level.
The development of methodologies to evaluate the impact of new ATM concepts and technologies on high-level, system wide Key Performance Indicators (KPIs) has been a long-time objective of the ATM research community. Low-level validation activities based on fast-time simulation, human-in-the-loop (HITL) simulation, shadow-mode trials and live trials provide accurate estimates of the performance of a certain solution in a given operational environment; however, implementing such validation approaches for different combinations of solutions at a network-wide scale is infeasible, or at least prohibitive in terms of both cost and time. It is therefore necessary to resort to performance models that consolidate the results of low-level validation experiments conducted for different solutions at a local level and estimate the integrated impact of such solutions at network level.
In this context, the goal of NOSTROMO is to develop, demonstrate and evaluate an innovative modelling approach for the rigorous and comprehensive assessment of the performance impact of future ATM concepts and solutions at ECAC network level. This approach will bring together the ability of bottom-up microscopic models to capture emergent behaviour and interdependencies between different solutions with the level of tractability and interpretability required to effectively support decision-making. The specific objectives of the project are the following:
1. Develop a methodology for the construction of ATM performance metamodels that approximate the behaviour of computationally expensive simulation models so as to allow a systematic and efficient exploration of the model input-output space and a robust handling of the uncertainty associated with the model predictions, by exploiting recent advances in the field of active learning.
2. Implement and validate the proposed metamodeling methodology by developing metamodels of two state-of-the-art microsimulation tools (namely Mercury and FLITAN) able to reproduce ATM performance at ECAC level.
3. Develop a set of visualisation and visual analytics tools that facilitate the analysis, interpretation and communication of the results of the new performance metamodels.
4. Demonstrate and evaluate the maturity of the NOSTROMO approach and the capabilities of the newly developed toolset through a set of case studies addressing the performance assessment of SESAR Solutions at ECAC level. The case studies shall cover a variety of ATM phases, solutions and KPAs/KPIs sufficiently heterogeneous to allow a comprehensive benchmarking against the performance modelling methodologies currently in use, with the aim to analyse the added value and the limitations of the NOSTROMO approach and evaluate the appropriateness of its transition to SESAR IR and its potential to improve of the European Operational Concept Validation Methodology (E-OCVM).
NOSTROMO project has been developed in an incremental approach towards the objectives, by evaluating and refining the proposed methodology in an iterative manner in the light of the results obtained in its specific applications.
