Partnership & Industry Context: This collaboration involves Ford Motor Company and Microsoft, leveraging Microsoft’s Azure Quantum platform.40 Traffic congestion is a major issue in urban areas, leading to wasted time, fuel, and increased pollution. Traditional navigation apps often exacerbate the problem by routing many vehicles onto the same “optimal” paths.41
Business Challenge & Objectives: The challenge is to move beyond “selfish” routing (optimizing for each individual car) to “balanced” routing, considering the routes of thousands of vehicles simultaneously to minimize overall system congestion.41 This requires solving a complex optimization problem involving a vast number of potential route combinations, which is computationally infeasible for classical computers in real-time.41 The objective was to develop and test a solution using quantum-inspired techniques to significantly reduce congestion and average commute times.40
Quantum Solution & Approach: Ford partnered with Azure Quantum to build a traffic optimization solution based on Microsoft’s Quantum-Inspired Optimization (QIO) algorithms.40 QIO algorithms are classical algorithms inspired by quantum principles (like annealing) that can run efficiently on classical hardware (CPUs, FPGAs) available through Azure.40 They are designed to tackle complex combinatorial optimization problems like the balanced routing challenge.40 The research involved simulating scenarios with thousands of vehicles in the Metro Seattle area, each having multiple route choices.41
Key Outcomes & Demonstrated Impact: Preliminary studies and simulations showed promising results. In a scenario with 5,000 vehicles, the QIO-based balanced routing solution delivered results in 20 seconds and achieved a 73% reduction in total congestion compared to selfish routing.41 Average commute times were reduced by 8%, translating to significant time savings across the simulated fleet.40Based on these promising results, Ford expanded the partnership to further refine the algorithm and test its effectiveness in more realistic scenarios, considering factors like road closures and driver behavior.41
Indicators of Importance (Why it’s on the list): This case involves major players (Microsoft, Ford) applying quantum-inspired methods to a relatable, large-scale societal problem (traffic congestion). It demonstrates tangible, significant improvements using QIO on classical hardware, showcasing a pathway to near-term quantum-related value without requiring fault-tolerant quantum computers. It received considerable press coverage.41
Analysis: This partnership is a prime example of leveraging quantum-inspired optimization for immediate impact. The balanced routing problem is computationally hard classically, but by applying algorithms derived from quantum concepts (annealing) onto classical hardware via Azure Quantum 40, Ford and Microsoft demonstrated substantial improvements over traditional methods.41 This highlights a key trend: businesses can benefit from quantum thinking and algorithms today, even before large-scale quantum hardware matures. QIO provides a lower barrier to entry for exploring quantum approaches to optimization compared to developing applications for gate-based quantum computers. The reported percentage reductions in congestion and commute time 40 provide compelling quantitative evidence of the approach’s effectiveness in simulations.