Volkswagen and Google Announce Quantum Routing Pilot for Urban Logistics

Volkswagen Taps Google’s Quantum Engine for Urban Logistics Breakthrough

On November 8, 2017, Volkswagen Group and Google made headlines by announcing a collaboration to apply quantum computing to urban mobility logistics, marking the first time a global automaker publicly explored quantum optimization for real-time traffic and delivery routing.

The partnership focused on harnessing quantum algorithms to tackle the exponentially complex challenge of route optimization for urban fleet logistics—an issue central to the future of sustainable, efficient delivery in megacities. The trial was conducted using Google's early quantum processors via its Quantum AI Lab in California, with the work built on Volkswagen's research in mobility-as-a-service (MaaS).

The Quantum Routing Problem

Delivery vehicles in metropolitan areas are subject to a vast number of ever-changing variables: traffic congestion, weather patterns, construction delays, and service time windows. Traditional algorithms, such as Dijkstra’s or A* search, struggle when scaled across hundreds of vehicles and thousands of delivery points in real time.

Quantum computing, by contrast, can evaluate millions of route permutations simultaneously through quantum annealing or hybrid variational methods, identifying optimal or near-optimal paths in dramatically shorter periods.

“Classical computers take a lot of time to simulate all potential traffic flows and vehicle permutations. Quantum computing can perform a huge portion of this workload simultaneously,” said Martin Hofmann, Volkswagen’s Chief Information Officer at the time.

Use Case: Lisbon Smart City Pilot

Volkswagen’s quantum pilot was tested on traffic flow optimization in Lisbon, Portugal, during the Web Summit conference in early November. The company simulated the most efficient deployment of ten buses through heavy downtown congestion using Google’s quantum computers.

By modeling millions of potential routing options under real-time traffic scenarios and commuter demand profiles, the quantum algorithm helped reduce the expected delay time across the fleet by over 20% compared to baseline AI methods.

Though the buses were not routed in real time using quantum systems (due to current hardware constraints), the simulation results were validated with historical data and mobility models.

Technical Foundation

The project used quantum annealing techniques compatible with Google’s early hardware, alongside hybrid models combining classical pre-processing and quantum-assisted optimization. Researchers deployed Quadratic Unconstrained Binary Optimization (QUBO) formulations to encode routing problems.

The algorithm was optimized for:

• Minimizing total distance traveled

• Reducing overlap between vehicles

• Accounting for predicted congestion windows

Volkswagen’s software development team worked directly with researchers from Google’s Quantum AI group, led by Hartmut Neven, to translate logistical problems into QUBO-ready formats.

Broader Implications for Logistics

While the pilot focused on public transit, Volkswagen indicated the technology’s broader applicability to logistics and delivery operations. Commercial vehicle fleets—ranging from last-mile couriers to large-scale distribution—face routing problems that are mathematically similar to those solved in the pilot.

If scaled, the solution could improve:

• Fuel efficiency by reducing idle time and mileage

• Customer experience through tighter delivery windows

• CO2 emissions by optimizing vehicle deployment in dense urban areas

“This is not just about traffic flow; it’s about logistics competitiveness and environmental responsibility,” noted Hofmann.

Automotive Industry Watching Closely

Following the announcement, several automotive and logistics firms began exploring quantum logistics potential:

• Daimler reportedly engaged with D-Wave on quantum vehicle simulations.

• Bosch expanded its quantum R&D team for logistics-focused applications.

• Ford and UPS began reviewing hybrid quantum optimization literature for potential pilots.

Volkswagen, with its software subsidiary Cariad and ongoing investments in connected mobility, positioned itself as a first-mover.

Public Sector and Smart City Integration

The Lisbon trial aligned with broader smart city initiatives, many of which are funded by EU Horizon 2020. City governments increasingly seek tools that allow real-time, predictive modeling of transport and logistics infrastructure.

Volkswagen’s results from Lisbon were shared with the city’s transit authority and sparked conversations about future pilot expansions to freight deliveries and autonomous vehicle routing.

Challenges and Technical Realities

While promising, the project was still exploratory. Google’s quantum hardware in 2017 was limited in qubit count and coherence, making it suitable primarily for small-to-medium optimization problems.

Moreover, integrating quantum solutions into live logistics systems requires robust hybrid architectures and training for operations teams—both still under development.

Nevertheless, the project demonstrated a credible path to value, even under hardware constraints.

Conclusion

The Volkswagen–Google quantum logistics pilot in November 2017 marked a pivotal moment for the transport and delivery sector’s engagement with quantum computing. It served as a proof-of-concept for how quantum optimization could tackle long-standing routing inefficiencies in urban environments. While hardware capabilities were still maturing, the project's implications for emissions reduction, cost savings, and smart city synergy signaled a future where quantum logistics could reshape how goods and people move through cities.