Development of Next-Generation Navigation Compression Technology Using Quantum Computers
Overcoming the Limits of Memory Capacity: Navigation Compression with QAOA and HOBO Optimization
The map apps and in-car navigation systems we use every day perform a process called “route compression” to compactly store and transmit map information. However, as routes become more complex, the efficiency of compression decreases, putting a strain on memory and communication bandwidth.
To tackle this challenge, we introduced a quantum optimization approach and proposed a new route compression method in collaboration with Keio University, utilizing HOBO (Higher Order Binary Optimization).
What is Quantum Optimization? What is HOBO?
HOBO is an extended form of the widely studied QUBO (Quadratic Unconstrained Binary Optimization), a combinatorial optimization algorithm used in quantum computing. HOBO incorporates higher-order interactions, enabling it to represent complex route structures with greater precision.
Comparison with the RDP Algorithm
When compared with the conventional Ramer-Douglas-Peucker (RDP) algorithm, our HOBO-based method achieved a significantly higher compression rate, while maintaining route accuracy within acceptable limits for navigation purposes.
In this study, we used actual map data to construct a HOBO model and used QAOA (Quantum Approximate Optimization Algorithm) to find optimized solutions, achieving better compression performance than traditional methods.
Toward Real-World Applications
These results demonstrate that algorithms inspired by quantum computing technology can be effectively applied to real-world mobility and navigation systems.
At Blueqat, we will continue validating and developing this technology for deployment in transportation, logistics, and smart city domains.
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