data science, solutions

How Air Traffic Management Is Taking off with Artificial Intelligence


Our client, an international organisation working to achieve safe and seamless air traffic management in Europe, wanted to enhance the performance of air traffic management systems.


Safety, capacity, cost of the service, efficiency and the environment are the drivers of air traffic management. Increased traffic or extreme weather events have an impact on traffic flows in the European network. Typically, a staffing problem, a thunderstorm or a blocked runway at a busy airport can create significant disturbances to traffic patterns.

In this context, artificial intelligence can enable the digital transformation of the aviation sector to increase the performance of air traffic management systems by improving the accuracy and speed of existing tasks while enhancing the predictability of traffic.


Using artificial intelligence, we were able to address many challenges, starting with airport capacity, finding the best landing or take-off route to reduce airport delays.

We helped our client to improve flight path management by predicting aircraft behaviour during landing or take-off. Overall, the separation time between aircraft in strong headwinds has been reduced by 10 to 15%. This represents 3 to 4 more aircraft landing per hour, allowing them to manage runway throughput safely, predictably and efficiently.

Safety assessment was also in scope. As the speed profiles are subject to many variables and parameters, the safety buffer times were long. We helped our client to more accurately predict how aircraft decelerate along their trajectory using analysis tools. With this solution, air traffic controllers had a tool that provides aircraft separation distance indicators to accurately and safely provide target time separation on final approach, based on aircraft speed profiles during descent.

All in all, our solutions contribute to better tools and decision making for air traffic managers and controllers.



While our solutions are already in full swing in a couple of airports in Europe, the future holds further applications linked to artificial intelligence.

We see that flight planning could be on the agenda, by managing 30,000 flight plans every day without human intervention.

Artificial intelligence could also address resource scarcity, provided IT systems are up to speed, enabling better use of aeronautical data, resulting in more accurate forecasts and more sophisticated tools, increased productivity and better use of resources, e.g. airspace, runways, personnel.