Volkswagen and Google Collaborate on Quantum Traffic Flow Optimization for Global Supply Chains
June 22, 2018
A Landmark in Quantum-Logistics Convergence
In late June 2018, Volkswagen Group revealed new milestones in its partnership with Google, detailing how the two had used quantum computing to optimize traffic flow prediction models in real-time urban networks.
The announcement, made at the Web Summit Tokyo 2018, highlighted how quantum algorithms could reduce city congestion, streamline route management, and potentially revolutionize freight logistics and long-haul transport planning.
While urban-centric at first glance, Volkswagen emphasized that their Quantum Routing Research Initiative had applications far beyond individual drivers. It was a pilot for global logistics optimization, setting the stage for quantum-enabled freight network design.
Inside the Project: From Traffic Jams to Global Supply Chains
The project, first launched in 2017 and expanded in 2018, leveraged Google’s D-Wave 2000Q system to process complex route optimization challenges involving:
Real-time vehicle density
Traffic signal timing
Predictive congestion mapping
Environmental variables (e.g., weather, events)
Volkswagen’s Data Lab in Munich used quantum annealing to process this information and build models that could recommend:
The fastest and most fuel-efficient routes across dynamic city environments
Optimal times for departure and arrival to minimize traffic bottlenecks
Vehicle clustering to reduce stop-and-go patterns
In June 2018, the team expanded its scope to simulate these capabilities on a global logistics scale, particularly in fleet-based cargo transport — targeting European trucking routes from Germany to the Netherlands, France, and Austria.
Applying Urban Models to Freight Operations
“We see no reason why these same routing techniques cannot be applied to cargo trucks, delivery fleets, and logistics corridors,” said Martin Hofmann, Volkswagen’s CIO, during a press conference on June 22.
Using anonymized logistics fleet data, Volkswagen fed delivery schedules into a D-Wave-based quantum optimization algorithm to test:
How truck convoys could avoid delays at known congestion zones
Real-time route switching based on accidents or weather
Multi-drop deliveries with optimal segment ordering
Initial tests showed that quantum-enhanced models outperformed traditional heuristics in identifying ideal routes under tight scheduling constraints — improving delivery accuracy by 16% in test scenarios.
From City Streets to Intermodal Logistics
In parallel with traffic experiments in Beijing, Lisbon, and San Francisco, Volkswagen ran freight logistics simulations using:
Delivery data from German retailers and suppliers
Traffic inputs from real-time telematics APIs
Historical port congestion records
They also explored use cases for intermodal optimization, including:
Efficient container handoff between road and rail
Port arrival timing to avoid queueing delays
Depot placement for predictive inventory restocking
Volkswagen’s IT research division confirmed that the quantum algorithm achieved significant improvements in scenarios with more than five route variables and over ten delivery nodes, where classical systems began to falter due to combinatorial complexity.
The Quantum Annealing Advantage
Unlike universal gate-based quantum systems still in early stages, D-Wave’s quantum annealer was well-suited for the type of optimization problems inherent in logistics.
Quantum annealing allowed Volkswagen’s engineers to:
Define logistics routing as a Quadratic Unconstrained Binary Optimization (QUBO) problem.
Encode route tradeoffs, delivery time windows, and cost factors into a quantum cost function.
Sample many potential solutions in parallel, seeking global optima rather than getting stuck in local ones.
This approach proved especially useful in last-mile delivery simulations — where timing, traffic, and route precision directly impact cost and customer satisfaction.
Key Metrics and Test Results
Volkswagen released the following results for their June simulations:
Average travel time reduction: 7% across tested urban corridors.
Freight delivery consistency improvement: 16% vs. classical systems.
Congestion avoidance success rate: 24% better than static routing.
These findings indicated that quantum computing could augment — not replace — classical AI route planners, helping logistics operators make faster, more accurate decisions.
Future Applications in Global Freight
The implications for global logistics were clear:
Freight forwarders could use quantum tools to plan multi-modal journeys across unpredictable conditions.
Port authorities might adopt similar models to better schedule truck entry times and avoid yard congestion.
Retailers and eCommerce brands could reduce delivery errors and late shipments.
While the current scale was limited to small problem sets due to the qubit count of D-Wave’s machine, Volkswagen’s quantum team expressed optimism that:
Larger quantum annealers (with >5000 qubits) could solve real-time logistics planning within the next five years.
Hybrid quantum-classical orchestration systems would be critical — with classical systems managing known routes and quantum engines tackling high-variable anomalies.
Collaboration Beyond the Auto Industry
Volkswagen’s partnership with Google served as a blueprint for cross-industry collaboration in quantum logistics. By June 2018:
Talks were underway with DHL Supply Chain and DB Schenker to test similar quantum routing concepts in warehouse-to-store distribution.
The German Federal Ministry of Transport and Digital Infrastructure (BMVI) expressed interest in funding future proof-of-concepts.
Research institutions such as Fraunhofer Society were exploring quantum logistics training programs for future supply chain engineers.
Addressing Limitations and Ethical Concerns
Despite encouraging results, Volkswagen and Google acknowledged the system’s limitations in June 2018:
Noisy qubits limited problem complexity.
No secure multi-tenant systems existed yet for commercial deployments.
Ethical concerns around data privacy in vehicle tracking required ongoing policy oversight.
Nonetheless, both companies emphasized that failing to explore quantum logistics early would mean playing catch-up later.
Conclusion: A Roadmap to Quantum Supply Chain Management
Volkswagen’s work with Google in June 2018 provided more than a proof-of-concept — it offered a roadmap to quantum-enhanced supply chain decision-making.
By applying quantum annealing to traffic and freight routing, Volkswagen not only reduced travel inefficiencies, but also laid the foundation for predictive logistics frameworks that can adapt to real-world chaos.
As global supply chains become increasingly complex and responsive to real-time demand shifts, the ability to dynamically plan optimal routes — at quantum speed — may soon be one of the most valuable capabilities in the logistics industry.