

Volkswagen’s Quantum Shuttle: A Real-World Quantum Leap for Traffic Logistics in Lisbon
September 25, 2023
Between 2019 and 2023, Volkswagen Group partnered with CARRIS—the public transit operator in Lisbon—and quantum computing firm D-Wave Systems to develop and deploy the Quantum Shuttle project. This pilot used a quantum annealer to optimize routing for nine MAN city buses serving 26 stops each across Lisbon’s urban network. On September 25, 2023, Volkswagen celebrated the initiative’s success, emphasizing it as the first real-world deployment of quantum computing applied directly to urban logistics.
The pilot leveraged anonymized passenger demand forecasts and live traffic data, integrating them into a hybrid quantum-classical system. Passenger demand prediction employed classical analytics on historical transit data to identify dynamic “demand spots.” Meanwhile, D-Wave’s quantum annealer solved the combinatorial vehicle routing problem under real-world constraints, including traffic conditions and passenger volumes. Route updates were delivered in real time to drivers via a custom navigation app, enabling the fleet to dynamically adapt and reduce wait times while preventing congestion buildup.
This project stands out because it was conducted on active city streets with actual vehicles and passengers, not simulations or closed test tracks. By integrating with public infrastructure and transit management, it bridged the gap between theoretical quantum optimization and practical urban mobility improvements.
Volkswagen reported notable benefits, including reduced passenger wait times during peak demand, more even bus spacing to avoid overcrowding, and improved overall traffic flow by proactively rerouting buses around developing congestion. These results validate quantum computing’s potential to handle multi-agent logistical challenges in unpredictable, real-world environments—a crucial step toward broader adoption in transport and supply chain sectors.
The technical architecture combined classical data ingestion and forecasting modules with D-Wave’s quantum annealer for route optimization, illustrating a hybrid approach that many logistics platforms are adopting even before universal gate-based quantum computers mature.
Looking forward, Volkswagen and project leaders, including former CODE Lab scientist Florian Neukart, see strong potential for scaling this model to larger fleets, other vehicle types (such as freight trucks or rail), and different cities. The core framework—combining demand prediction, app integration, and quantum optimization—can be adapted for diverse logistics scenarios like parcel dispatch, emergency vehicle routing, rail yard scheduling, and container port crane sequencing.
The Lisbon Quantum Shuttle sets a global benchmark. Unlike earlier quantum logistics experiments limited to research labs or small-scale simulations, this project demonstrated a fully operational, city-integrated quantum logistics system with real passenger impact. It has inspired increased industry attention and media coverage, positioning Lisbon as a pioneering example of quantum technology’s practical value in urban transport.
Challenges remain for broader rollout, including data availability in less sensor-equipped cities, network reliability, driver app adoption, and regulatory compliance. Volkswagen is reportedly preparing expanded pilots with larger fleets and longer deployments to test scalability, network resilience, and user acceptance.
As quantum and transportation continue converging, Volkswagen plans to extend the platform to large-scale events requiring adaptive mobility, complex freight logistics, and port coordination—indicating that Lisbon’s Quantum Shuttle is the start of a broader quantum-enabled logistics transformation.
In sum, the Lisbon Quantum Shuttle proves quantum logistics is no longer hypothetical. By September 2023, Volkswagen and D-Wave delivered a working model demonstrating that quantum-enhanced systems can optimize live, complex urban logistics—ushering quantum computing from the lab to the streets.
