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Quantum Decides Faster Emergency Escape Routes

Honda and Terra Quantum researchers use quantum simulation to calculate the optimum route to escape disaster scenarios

September 26, 2023

2 Min Read
A line of traffic and an evacuation route sign
Honda and Terra Quantum used quantum machine learning to establish disaster escape routes. Getty

Researchers have used hybrid quantum computing methods to determine the fastest evacuation routes in a simulated scenario of an earthquake hitting a small town.

Honda Research Institute Europe worked with German quantum technology company Terra Quantum to develop new methods to shorten escape times in emergencies.

The proof of concept (POC) project set out to demonstrate the potential of hybrid quantum computing methods to improve mobility systems in challenging conditions. The solution predicted efficient escape routes for vehicles, minimizing evacuation times.

Quantum computing algorithms are adept at taking many simultaneous dynamic variables into account, as would be needed. The team ran quantum machine learning simulations on classical hardware using only local information, which amounted to less than 1% of the map information, to make decisions.

The application produced results comparable with classical computing methods and can be executed on large-scale quantum computing hardware when it becomes available. Terra Quantum now plans to further develop the solution so it can be applied to a broad range of scenarios in various city landscapes.

“We are very pleased with the results of our collaboration with HRI-EU. This is just the start, we see the huge potential in applying quantum technologies in the automotive and mobility sectors,” said Markus Pflitsch, founder and CEO at Terra Quantum.

Related:Agencies Release Quantum Readiness Factsheet

According to data from the World Meteorological Organization, weather-related disasters have increased five-fold over the last 50 years due to climate change. Being able to respond rapidly saves lives, but these situations are unpredictable and can change rapidly, meaning they are challenging for current technology to manage.

“Identifying realistic problems where quantum technologies may unfold their potential constitutes one of the biggest challenges in the field today. This work represents a promising step in that direction and shows how to employ hybrid quantum-classical learning architectures in a real-world use case,” said HRI-EU principal scientist Sebastian Schmitt.

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