Airbus’ UpNext innovation advancement subsidiary has begun testing technologies designed to support automatic aircraft taxiing and pilot assistance. The technologies are part of UpNext’s three-year Optimate research project, which combines advanced automation, computer vision, data fusion, and machine learning to improve aircraft navigation systems, human-machine interfacing, and flight safety in general.
The research involves developing and testing automatic taxiing using more accurate and reliable position calculations and assessing the potential of quantum sensing to improve position availability and navigation systems. Further, the research is investigating the capabilities of a collaborative map and virtual flight assistant to support pilot decisions and interactions with air traffic control and operations centers.
UpNext is validating the architecture and algorithms on an electric truck testbed that replicates the functions of a cockpit and can roll down airport runways like an aircraft. The testbed is recreating an Airbus A350 flight deck with advanced automation technologies such as LIDAR and external cameras, combined with GPS technologies, satcom, and 5G. Following these tests, UpNext will demonstrate the virtual system for a fully automated gate-to-gate mission on an A350.
“Our ambition is to use the best technologies to make our aircraft even more aware of their operating conditions, analyzing it in as much detail as possible to become smart and reliable assistants to pilots, providing them with the optimal assistance,” said UpNext CEO Michael Augello. “We are confident that this project will contribute to safer and more efficient air travel.”