BMW Taps Quantum for Sensor Placement

Quantum company solves complex optimization problem
Scarlett Evans

August 1, 2022

Conceptual art of a high-tech BMW vehicle
QCI used quantum computing to solve a complex vehicle sensor optimization problem.BMW

Quantum Computing Inc. (QCI) has used quantum computing to solve a complex optimization problem for BMW on the placement of vehicle sensors for autonomous driving.

The use case originated as part of the BMW and Amazon Web Services 2021 Quantum Computing Challenge. The Vehicle Sensor Placement problem invited participants to find the best placement for sensors on a given vehicle to provide optimal coverage for autonomous driving at the least cost.

QCI used its Entropy Quantum Computing technology to solve the challenge, which involved more than 3,800 variables, in six minutes. To put this in perspective, today’s Noisy Intermediate Scale Quantum (NISQ) computers can process approximately 127 variables for a problem of similar complexity.

QCI created a sensor configuration consisting of 15 sensors and offering 96% coverage of the vehicle.

“We are very proud to have achieved what we believe to be an important landmark result in the evolution of quantum,” said QCI CEO Bob Liscouski. “We believe

that this proves that innovative quantum computing technologies can solve real business problems today.

“What’s even more significant is the complexity of the problem solved. This wasn’t just a rudimentary problem to show that quantum solutions will be feasible someday; this was a very real and significant problem whose solution can potentially contribute to accelerating the realization of the autonomous vehicle industry,” he added.

“The technological landscape in the field of quantum computing is only just starting to take shape,” said BMW Group research vice president Peter Lehnert. “By launching our crowd innovation initiative, we are hoping to tap into additional innovative power that would be beyond the reach of a standard tendering process.”

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