NOSTROMO (Next-generation Open-Source Tools for ATM PeRfOrmance Modelling and Optimisation) project addresses the SESAR 2020 Exploratory Research topic SESAR-ER4-26-2019, ‘ATM Validation for a Digitalised ATM’, with focus on the ‘Macro-modelling applied to Air Traffic Management’ area. 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.  The development of methodologies to evaluate the impact of new ATM concepts and technologies on high-level has been a long-time objective of the ATM research community. Low-level validation activities based on fast-time simulation, human-in-the-loop 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. The approaches to this problem can be classified into two broad categories:

·       Top-down macroscopic models:

Macroscopic models, such as the influence diagrams are the most commonly used for strategic decision-making because of their parsimonious character, which renders them easy to compute and facilitates the task of explaining and communicating results to decision makers. However, they suffer from two major shortcomings. First, they avoid the explicit modelling of the complex interrelationships between the components of the ATM system, which prevents them from capturing the resulting emergent behaviour and network effects. Second, they are, to a large extent, based on the use of experience and expert judgement; given the impossibility of conducting validation experiments at a network-wide scale, their mathematical formulation is thus supported by little or no empirical evidence.

·       Bottom-up microscopic models:

As opposed to the previous approach, ATM performance modelling has also been approached through the development of microscopic models with stronger behavioural foundations, which explicitly model the influence of new solutions on the behaviour and interactions of individual entities at the disaggregated level (e.g., individual flights) with the aim to observe the performance that emerges at the macroscopic level. Different models of this type, usually operationalised through fast time and agent-based simulations, have shown their ability to capture a rich variety of behaviours in a very realistic manner. However, these models also face some limitations that hinder their operational use: the richness of the model comes at the cost of computational complexity, which makes it difficult to explore the simulation space in a systematic manner, and also hampers the task of analysing, interpreting and communicating the modelling results.

The NOSTROMO project aims to tackle these limitations, in order to develop new approaches to ATM performance modelling able to reconcile model transparency, computational tractability and ease of use with the necessary sophistication required for a realistic representation of the ATM system. The next diagram shows NOSTROMO Aproach, which will take the benefits of cost and interpretability from Macroscopic models, and the advantages in accuracy and behaviours capturing from Microscopic models.