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Imagine flying from Europe to Australia in just 90 minutes. Or taking a pleasure flight in a dirigible above the Himalayas.

This is fantasy for now, but the stratosphere is the next frontier in aviation, with supersonic flights using that high-altitude space. And one of the keys to making it happen will be the use of Artificial Intelligence (AI) to cope with the increased complexity the sector will face.

“Aviation is being reshaped by a number of powerful forces that are fundamentally impacting the Air Traffic Management sector,” says Beatrice Pesquet-Popescu, Research and Business Innovation Director for Air Traffic Management (ATM) at Thales. “In addition to the growth expected in traditional aircraft, we will have to cope with new vehicles such as drones and stratospheric balloons, circulating in low or high altitude airspace.”

New technologies will be available to support this increased complexity of airspace management, such as increased ATM automation supported through AI-enabled platforms or machine learning.

As a leader in ATM solutions, Thales helps two out of every three aircraft take off and land around the world. The company, which is present in 85 locations across the globe, provides safe and secure airspace management systems and services through pivotal digital transformation technologies such as AI. Thales’s experience helps the company to offer a clearer prediction of traffic flow, trajectories and estimated take-off and arrival times. The  bottom line is simple: improved operations and a reduction in operating costs for all the stakeholders in air safety - air navigation service providers (ANSPs), civil aviation authorities, airlines and airports.

The new generation automated systems increase the efficiency of ATM but “keep the human in the loop by allowing air traffic controllers to have the final say,” Pesquet-Popescu says.

AI leads the way to the new ATM

Thales believes that AI will complement and enhance the capabilities of humans, reducing their involvement in repetitive or low-value tasks, freeing up more time for more critical tasks, where human intervention is crucial.

“In this way, AI will enable controllers to cope with the expected growth in air traffic, as well as the complexity of integrating new vehicles,” says Pesquet-Popescu.

The results are a safe, secured and more efficient management of the airspace, with better predictive capabilities, leading to fewer delays and less fuel burned, so fewer carbon dioxide emissions for an overall smaller aviation carbon footprint.