A2URE

Exploring automation in air traffic control decision making

A2URE project

A2URE was an early-stage study undertaken by NATS and the University of York to consider suitable methodology for the development and approval of automation in decision making in air traffic control operations and what changes might be required to operational procedures and policies.

NATS worked with one of the University’s PhD researchers to produce three reports setting a framework for introducing automation to air traffic management.

The first report focused on the current safety assurance process for change in the air traffic management system and how it could be applied to decision-making automation. The second report was aimed at summarising the issues commonly found in controller-automation interactions as identified through a literature review.

The final output was a new methodology for how air navigation service providers (ANSPs) can approach the design and development of automated decision-making tools while also gathering evidence for safety assurance and validation and verification.

The development of the reports was supported by workshops in which NATS experts from safety assurance, validation and human performance departments discussed how some of the current practices identified in the first report can be put into practice when developing an automation decision-making system. The second workshop focused on the methodology developed and refining it through expert input.

The project has helped us understand the current working practices in terms of how automation-decision making tools and systems can be validated as they are designed and developed, as well as understanding how they should be safety assured. It identified gaps and opportunities for further research and how we can continue to develop our procedures and policies as we introduce more automation into our operations.

A2URE was one of the projects chosen to receive support from NATS at the first Research Collaboration Conference in 2019.

Potential benefits

Increased automation

Reduced workload

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