Airbus has concluded the flight test campaign for UpNext Optimate, a demonstrator that spent the past three years testing an automated, gate-to-gate mission profile on a commercial aircraft. Central to the programme was “Optibus,” a fully electric experimental ground vehicle fitted with a virtual replica of an Airbus A350 flight deck, a familiar sight on the taxiways of Toulouse-Blagnac and Paris-Charles de Gaulle airports throughout the trial.

Building on the earlier UpNext DragonFly demonstrator, Optimate set out to test end-to-end smart automation across four areas: taxiing, pilot assistance, dynamic trajectory protection and digital communication systems. By the end of its campaign, the demonstrator had logged more than 500 hours on the tarmac and 14 hours in the air.

With the global commercial aircraft fleet projected to nearly double over the next two decades, Airbus says ground congestion at airports will progressively increase, since runway, taxiway and gate capacity cannot easily expand at the same rate; this will demand increasing attention from flight crews managing taxiway navigation, ground vehicle traffic and air traffic control instructions. Optimate aimed to evaluate how smart automation, artificial intelligence and advanced sensors could support pilots from the start to the end of each journey, using a three-tiered approach that began with virtual simulation and algorithmic design, moved on to ground testing with Optibus, and finished with full-scale trials on an A350-1000 test aircraft under realistic operational flight conditions.

“This demonstrator allowed us to evaluate, de-risk and mature cutting-edge technologies at an accelerated pace,” said Jonathan Rigaud, Airbus UpNext Optimate Director. “By testing early and incrementally, first digitally, then on the Optibus, and finally in the air, we were able to refine our algorithms with real-world feedback on safety and operational improvements while reducing fuel burn associated with flight testing.”

INTEGRATING THE TECHNOLOGY

The first area of exploration focused on high-precision automation of taxiing. Multi-sensor data, including computer vision, LIDAR and four-dimensional radar, was complemented by experimental quantum sensing to achieve centimetre-level positioning, which can also offer robust, accurate positioning in challenging or remote environments where satellite-based navigation signals may be compromised or unavailable. Inside the flight deck, an AI assistant analysed traffic and weather feeds as well as airport constraints to anticipate routing changes and recommend optimal taxi and cruise trajectories; these automated trajectories remained fully overridable by the pilots throughout, in keeping with Airbus’ commitment to human-in-the-loop automation.

Optimate also demonstrated how communication between automated systems, flight crews, air traffic control and airline operations control centres could be reshaped to improve efficiency, computing dynamic routes and displaying them to all parties, while testing hybrid combinations of high-bandwidth 5G, satellite communications and traditional radio channels to address connectivity gaps around heavy airport infrastructure; in flight, this digital link supports real-time collaborative decision-making, weather avoidance and automated diversion planning to optimise fuel efficiency.

Ground testing with Optibus provided practical insights that allowed improvements to be made before any technology moved onto the flight test aircraft, including refining computer vision to better distinguish runway features, calibrating sensors to adjust for glare from low sun angles and heat shimmer on the tarmac, and establishing a dynamic envelope to avoid ground collisions.

Airbus says the pilot-centric philosophy behind its approach to automation has only been reinforced by the project: as airport density increases, smart automation is intended to enhance and empower human expertise rather than replace it, freeing flight crews to prioritise high-level strategic decisions, passenger safety and mission optimisation. The operational lessons learned will feed into a variety of future Airbus engineering programmes.