It is perhaps fitting that SESAR JU partners chose the Spanish word for lighthouse, FARO, as the name for their project. As Christian Verdonk Gallego, FARO Project Manager from CRIDA, explains, the project is hoping to shine a light on how changes in air traffic management systems can impact safety and resilience.

What is the rationale for your project?

FARO seeks to understand better how changes in a system, in this case air traffic management (ATM), can impact its performance, in terms of safety and resilience. A change can be modifications to the operating environment, upgrades to the technology or procedures that are used to run the system. That’s why FARO partners are working on methodologies to help organisations evaluate the impact of these changes.

What do we mean by resilience and why is it important in ATM?

Safety science has advanced in recent years, recognising that ‘systems’ today, such as ATM, are characterised as being ‘socio-technical’ and inherently complex. The environments in which these systems operate are changing continuously, becoming more dynamic, non-linear, complex, and uncertain. So these systems have to be able to reconfigure themselves, often reconciling competing and changing system goals, and performance variables.

Resilience, seen through this lens, addresses and seeks to understand complexity and non-linearity in this operating environment. FARO is looking at the adaptative capacity of a system in response to unforeseen events and challenges, with a view to modelling the system that emerges.

How challenging is it to measure the impact of increasing levels of automation on safety and resilience? What will you use to test your assumptions?

It is very challenging to measure it. Increasing the level of automation because we need to consider that when we provide new tools to users of the system (e.g. planners, controllers, pilots, etc.), they may come up with new ways of using those tools to fulfil their tasks. This of course impacts safety and resilience, so we are trying to identify these methodologies to quantify this, but in a systematised manner. To do so, we have identified three use cases in the Spanish airspace to validate our approach.

Are you using data/AI in your project? If so, how?

The use of data is one of the pillars of the project. For example, we are using NLP (natural language processing) techniques to exploit information from safety-related occurrences (see our recently published article on the topic in Open Research Europe). We also are performing larger analyses, requiring the use of machine learning at every stage of the data science process. For example, we are using Belief Bayesian Networks to identify causal relations to explain safety performance levels.

How could the results of your project be used by the authorities, ANSPs, end users and what benefits do you hope your project will bring?

We hope that our methodologies will help with the development of more indicators to quantify safety levels and also to predict them under different circumstances. In terms of resilience, we hope that we advance in the resilience engineering field with the quantification of sources of adaptative behaviours. Finally, we are working very hard on how to integrate these approaches, with a very promising concept for understanding and visualising these concepts.

Concretely, our methodologies can help air navigation service providers to drill down into the nitty-gritty of change and identify the real impact of a change has on their operations. But not only that, for example, the project has already elicited some recommendations for authorities for the publication of safety-related reports, which may help to create a more exploitable source of knowledge.


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 892542