Volkswagen to improve traffic with quantum computing

  • TECH
  • Wednesday, 07 Nov 2018

Volkswagen's newly developed quantum algorithm has the potential to make traffic more efficient than ever. — AFP Relaxnews

On Nov 6 at the 2018 Web Summit in Lisbon, Portugal, Volkswagen Group announced its development of a smart traffic management system powered by quantum computers to increase global road transport efficiency.

The German manufacturer's team of IT experts have recently developed a traffic management algorithm powered by quantum computers to precisely predict urban traffic movement.

With this information, "public transportation organisations, taxi companies, and transport service providers will be able to deploy their fleets considerably more efficiently while minimising wait time for passengers."

The benefit of using quantum computing for such a complex task is its speed and enormous capacity to crunch extensive datasets. Supercomputers are often not advanced enough to use such immense volumes of information to develop an optimised solution, so quantum computers are currently the best option to forecast traffic volume, transport demand, and travel times.

In the case of traffic optimisation, Volkswagen's process consists of two main steps: the analysis of anonymous user movement data with conventional computers, and the optimisation of traffic flow thanks to predictive analytics with quantum computers.

If machines can simultaneously predict what vehicles are doing and where their final destinations are, traffic can be organised and managed to move faster, safer and more efficiently. This could considerably reduce excessive passenger wait times, vehicle shortages, and barren public transport routes.

The group intends to test the algorithm in Barcelona where the traffic database is abundant.

Volkswagen is presenting this project, along with D-Wave, the quantum computing company providing VW with quantum computers for the project, at the Web Summit tech conference in Lisbon, underway now. – AFP Relaxnews
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