Piloted and non-piloted passenger electric aerial vehicles (EAVs) are taking off, with a surge of investments underway and the FAA having set 2028 as the year in which EAVs will be commercialized in a major way.
Quantum computing is experiencing similar growth, with the market predicted to be worth $170 billion by 2032 and many current real-life use cases already proving its value.
However, the commercialization of flying cars will introduce several challenges in determining the optimum flight path to save money and fuel while staying safe.
Flight path calculation is a critical risk-management use case that needs to consider factors including the time, speed and route of the journey while satisfying airspace constraints and minimizing risks related to weather, obstacles and other aircraft.
This risk-based, multifactor
Scaling Quantum Drone Routing for Flying Cars
Quantum Computing Inc. (QCI) launched a partnership with the Virginia Innovation Partnership Corporation (VIPC) last October to
using QCI’s Qatalyst software and Quantum Photonic Systems hardware.
Giving an update on the program, QCI chief technology officer Bill McGann said the lessons learned could easily scale to passenger aircraft.
“The VIPC heavy-lift drone project is probably the best example of a transportation routing optimization program we’ve done. It's multi-dimensional, with things moving in X, Y and Z planes,” McGann explained.
“When you’re doing routing for a flying car, you have the ordinary optimization problem challenges, but also imagine if it crashes you don’t want it to be in a heavily populated area. This extra degree of freedom of motion is good for collision avoidance, but it makes the complexity of the problem much greater.”
McGann said QCI discovered that when the constraints for an on-time delivery are added to the routing problem, it quickly becomes intractable for classical computers. The project demonstrated that it was feasible on QCI’s entropy quantum computer and that it could scale as the hardware becomes more capable.
“I think the VIPC problem would scale very well into passenger transportation, manned or unmanned, like your Air Uber or Lyft,” he said. “But there'd be additional constraints, like on-time delivery points, which makes the problem very challenging, plus a lot more safety constraints with people on board.
“We can imagine that when you put a person inside of a vehicle that's now being autonomously flown or driven you have other criteria caused by the interaction between the vehicle and the person. That would add constraints, which would multiply the complexity of the problem. Safety and payload would be the most significant constraints in adding complexity.”
Practical quantum computers are still some years away, and sufficiently powerful machines machines that would be small and light enough to mount in a flying car could take much longer. QCI's project, for example, saw a lab-based quantum computer carry out the optimization calculations that then informed the drone routing.
“Quantum computers are not yet portable, typically resembling laboratory-mounted, bright metallic chandeliers of connecting tubes and wires, connected to supporting pumps and cooling systems," said partner at intellectual property law firm Reddie & Grose Nick Reeve.
"Real-time control of autonomous vehicles would therefore remain challenging since the computer could not be on board. You would need robust telecommunications networks to upload a flight plan in real time or would need to schedule time on the computer in advance and download the result to the vehicle before departure. The development of a room temperature superconductor, as recently reported from a lab in Korea, might change this.”
Reeve added that the computing power required by futuristic transportation is a factor that has been overlooked in even the biggest science fiction franchises.
“Autonomous and aerial vehicles loom large in popular science fiction culture – the Mr. Fusion powered flying DeLorean in the Back to the Future films, the stream of airborne traffic in the skies of Coruscant in the Star Wars universe, even Bruce Willis’ taxi in Luc Besson's’ The Fifth Element. The imaginations behind these creations envisioned some kind of futuristic propulsion technology but seldom pictured vastly more powerful computers to enable the vehicles to navigate and avoid collisions,” he said.
Other Use Cases
QCI was not the first company to explore the potential of quantum solutions for flying cars. Japan-based Sumitomo Corporation, Tohoku University and unmanned traffic management solutions specialist OneSky Systems started investigating quantum solutions specifically for flying cars back in 2021.
demonstrated using quantum computing to develop a real-time three-dimensional traffic control system for the era when hundreds or even thousands of air mobility vehicles would be flying in the sky. The researchers claimed their simulation improved the number of flying vehicles that could fly simultaneously by about 70%.
Beyond efficient routing and safe flying, quantum computing could also help the design of flying cars. Automobile and aircraft manufacturers are using quantum algorithms to develop novel materials and chassis shapes optimized for efficient aerodynamics and impact resistance. And several quantum research projects are revolutionizing battery design by studying the very quantum physics that underlies the technology.
From the design, development and powering of passenger EAVs to getting to the office on time and safely, quantum computing could deliver a future with practical flying cars that is closer than may be imagined.
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