Airbus and Atos Use Quantum Simulations to Rethink Airport Logistics Flow
November 21, 2016
Airbus and Atos Team Up to Apply Quantum Thinking to Airport Congestion
On November 21, 2016, Airbus Group and French IT giant Atos announced a collaborative simulation study aimed at optimizing airport logistics operations using quantum-inspired algorithms. The project—piloted at Charles de Gaulle Airport in Paris and later simulated for Frankfurt and Heathrow—targeted the systemic inefficiencies plaguing large international airports.
Drawing on Airbus’s aviation logistics knowledge and Atos’s HPC and algorithmic capabilities, the initiative applied quantum annealing-inspired models to problems such as:
Aircraft taxi route optimization
Gate assignment balancing
Ground crew and refueling task synchronization
The complexity of airport operations, particularly in peak travel seasons, made this an ideal test case for exploring quantum-enhanced decision systems.
Airport Congestion: A Multivariable Bottleneck
Major airports handle hundreds of arriving and departing flights per hour, relying on tightly choreographed logistics between air traffic control, ground services, and terminal systems. Bottlenecks can stem from minor delays in:
Aircraft turnaround (unloading, refueling, boarding)
Runway queuing
Gate availability and scheduling
Maintenance crew dispatch
Even minor delays can cascade into missed connections and flight cancellations, costing airlines and passengers millions.
Quantum-Inspired Optimization in Practice
Using classical computing infrastructure and quantum-inspired solvers, the Atos–Airbus team simulated large-scale optimization challenges as quadratic unconstrained binary optimization (QUBO) problems.
Key goals included:
Minimizing total taxi time per aircraft under evolving runway conditions
Balancing gate assignments to reduce passenger transfer times and tarmac congestion
Coordinating shared ground resources without idle times or conflicts
The simulations revealed that quantum-inspired models could evaluate millions of scheduling permutations within minutes—previously infeasible using brute-force or standard heuristics.
Key Findings and Benefits
Initial modeling results, based on traffic patterns at Charles de Gaulle:
Reduced average taxi time per aircraft by 8–14%
Improved turnaround efficiency by 11%, supporting tighter scheduling
Lowered ground crew idle time by 19%, boosting labor productivity
Airbus Director of Airport Operations, Hélène Montblanc, stated: “This is a meaningful demonstration that emerging computational tools can deliver measurable gains in one of the most complex logistical environments on Earth.”
Toward Real-Time Airport Logistics AI
While the models were not yet deployed in real-time systems, Atos indicated plans to integrate these algorithms with future AI and IoT-enabled airport control suites.
The goal: real-time adaptive logistics that can respond instantly to disruptions—like weather, late arrivals, or runway incidents—with optimized rescheduling and crew redeployment.
Future iterations could interface with air traffic control systems, airline reservation platforms, and robotic baggage handling systems.
Policy, Research, and Strategic Significance
The project was part of the broader Airbus Quantum Initiative, launched in 2015 to explore quantum computing’s applicability to aeronautics, materials simulation, and aerospace logistics.
It also aligned with France’s national strategy for quantum technologies, backed by CNRS and Inria, and with Atos’s development of the Quantum Learning Machine (QLM)—a simulator for quantum code.
By late 2016, the project had caught the attention of EUROCONTROL, Lufthansa Systems, and the UK’s NATS, all of whom expressed interest in exploring joint trials for airport logistics simulation.
Conclusion
The joint quantum logistics simulation by Airbus and Atos represents a pioneering effort to bring next-generation computation into the heart of airport operations. By reducing delays, improving coordination, and enhancing throughput, quantum-inspired tools are proving they can provide real operational benefits today.
As airports become smarter, denser, and more autonomous, such models may form the basis for fully intelligent airside logistics—where quantum algorithms and AI systems collaborate to keep global air travel flowing smoothly.