Quantum Computing-a Key to Automotive Industry Innovations

As quantum computing gains maturity, automotive players are capitalizing on its potential.

FREMONT, CA: Buzz and hype aside, something is going on in quantum computing that is hard to miss, and the technology will have significant implications for the automotive sector. Much of the excitement is connected to the recent scientific leaps in the field and the development of the first industrial applications, including those in the automotive and transportation industries. The automotive sector has been following these developments since quantum computing provides computational enhancements that could boost potentials across the value chain. Here is a review of QC’s maturity and its ability in the automotive sector.

QC can positively impact various areas in the automotive sector, like vehicle routing and route optimization, material and process research, and the security of connected driving. Quantum computers will be leveraged through automakers during vehicle design to offer improvements identifying with minimizing drag and enhancing eco-friendliness. Likewise, quantum computers can perform innovative simulations in vehicle crash behavior and lodge soundproofing, just as to train algorithms used in the improvement of autonomous-driving software. Quantum computer’s potential to decrease computing times from half a month to a couple of moments indicates that OEMs could guarantee vehicle-to-vehicle communications in real-time.

QC can also offer a boost to automotive players transitioning into the electric vehicle age by notably accelerating research and development of the latest technologies. Relevant applications will primarily relate to remediating simple optimization issues or parallel data processing for simple quantum artificial-intelligence algorithms. These quantum-computing use cases will be executed as part of a hybrid solution. Bits of a larger issue, processed by an HPC, are outsourced to a quantum computer, and outcomes are fed back into the HPC flow. Possible optimization applications include the combinatorial optimization of multichannel logistics, highly local traffic-flow optimization, and enhancements in vehicle routing.

Quantum AI and ML might involve the time-efficient training of autonomous-driving algorithms due to a surge in the parallel processing of massive amounts of data.

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