AI opens up new possibilities for air traffic control and the cockpit

AI as a future team partner in aviation

The aviation industry is currently working intensively on introducing AI systems. Unlike conventional assistance systems, these can process large volumes of data, be trained on the basis of this data and so adapt flexibly to new situations. AI systems offer the potential to increase the efficiency of air traffic and relieve the workload on highly qualified specialists, while at the same time ensuring safety, transparency and human control at all times.

"In the DLR LOKI project, we investigated how humans and AI systems can cooperate successfully in aviation. Our aim was to make this collaboration trustworthy, transparent and user-centred," says the project’s scientific lead, Carmen Bruder from the DLR Institute of Aerospace Medicine.

One focus of the research was the development of the digital air traffic controller DIRC (Digital Interactive Reliable Controller). Unlike traditional assistance systems, the DIRC not only supports human controllers with information or recommendations but can also take on certain tasks independently. This allows for dynamic coordination with human air traffic controllers regarding which tasks are to be undertaken.

Simulations showed that human and digital air traffic controllers can divide their tasks efficiently. Together, they managed up to 25 percent more than the current maximum traffic volume specified for an airspace sector. The research thus addresses a key challenge facing European air traffic: rising traffic volumes coupled with the increasing challenge of maintaining staffing levels in air traffic control.

Supporting pilots: AI helps decisions when time is critical

In addition to air traffic control, the researchers developed the Intelligent Pilot Assistance System (IPAS), a demonstrator designed to support pilots in the cockpit.

The system is designed to support crews particularly in time-critical situations, for example when selecting alternative flight routes or suitable alternate airports. The AI analyses large amounts of relevant information and processes it to aid decision-making. At the same time, the team investigated what information pilots need in order to understand and reliably assess the recommendations of an AI system.

Building trust in AI systems

In addition to technical developments, the project investigated the conditions necessary for trustworthy collaboration between humans and AI systems. The researchers analysed the expectations and requirements of aviation personnel and assessed how collaboration between humans and AI in aviation should be structured.

A key finding is that trust is not built solely on a system’s performance. Crucial factors include transparent information about the AI's capabilities and limitations, suitable training opportunities and the gradual introduction of new functions. Based on the project findings, important recommendations were formulated; taking these into account will help ensure the successful development and introduction of AI systems in aviation.

Next steps towards practical application

The findings form a basis for the further development of AI systems in aviation and will feed into the European debate on the safe introduction of such systems.

"Systems such as DIRC and IPAS can make air transport more flexible, reliable and efficient in the future – while maintaining consistently high safety standards and keeping people in control," says Bruder.

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