As air traffic management increasingly relies on high levels of automation and artificial intelligence, ensuring the resilience, safety and security of these systems becomes critical. While automation delivers major efficiency and capacity benefits, it can also increase vulnerability to rare but severe disruptions, including system failures, cyber incidents, extreme weather, or cascading events that are difficult to anticipate and manage. These high impact low probability events pose significant challenges for highly automated ATM environments, where traditional risk assessment methods and training data are often insufficient.

The ATM-RARE project addresses this challenge by focusing on strengthening the resilience of highly automated ATM solutions when confronted with such rare and disruptive events. The project aims to make air traffic control systems more robust, adaptable and prepared to maintain safe operations under stress, particularly in future ATM concepts with increased autonomy and human–machine interaction. A key element of the project is the provision and use of anonymised data related to high impact low probability events, improving understanding, preparedness and mitigation strategies. By doing so, ATM-RARE contributes to safer, more resilient and secure ATM systems capable of withstanding unexpected disruptions.