Volkswagen is delving into quantum computing. BMW is building a giant new data centre. And Bosch this week announced plans to construct a factory to build chips for self-driving cars. The moves are part of an expanding effort by European car makers and suppliers to build the computing capacity — so-called big data — they will need as vehicles digitise and become driver less.
Cars will need to constantly communicate, absorbing and analyzing information from thousands of vehicles at once, to make decisions to smooth traffic flow, save fuel and avoid hazards. That presents a huge new challenge for companies traditionally focused on manufacturing.
“The processing power needed to deal with all this data is orders of magnitude larger than what we are used to,” said Reinhard Stolle, a vice president in charge of artificial intelligence at the German automaker BMW, which is building a data centre near Munich that is 10 times the size of the company’s existing facility. “The traditional control engineering techniques are just not able to handle the complexity anymore.”
Big data is a challenge for all automakers, but especially German companies because they target affluent customers who want the latest technology. At the same time, the focus on computing pits the automakers against Silicon Valley tech companies with far more experience in the field, and creates an opening for firms like Apple and Google, which are already encroaching on the car business.
Google has long been working on self-driving or “autonomous” cars, and Tim Cook, the chief executive of Apple, said this month that the company best known for making iPhones is focusing on autonomous systems for cars and other applications.
That has put pressure on automakers. German companies in particular have already made investments in ride-sharing services, in part to combat the rise of Uber, and are now looking further into the future.
Efforts by Volkswagen, trying to remake itself as a technology leader as it recovers from an emissions scandal, show how far into exotic realms of technology carmakers are willing to go.
Volkswagen, a German company, recently joined the handful of large corporations worldwide that are customers of D-Wave Systems, a Canadian maker of computers that apply the mind-bending principles of quantum physics.
While some experts question their usefulness, D-Wave computers — housed in tall, matte black cases that recall the obelisks in the science fiction classic “2001: A Space Odyssey” — can in theory process massive amounts of information at unheard-of speeds. Martin Hofmann, Volkswagen’s chief information officer, is a believer.
“For us, it’s a new era of technology,” Mr. Hofmann said in an interview at Volkswagen’s vast factory complex in Wolfsburg, Germany.
First theorized in the 1980’s, quantum computers seek to harness the strange and counterintuitive world of quantum physics, which studies the behaviour of particles at the atomic and subatomic level. While classical computers are based on bits with a value of either 1 or 0, the qubits in a quantum computer can exist in multiple states at the same time. That allows them, in theory, to perform calculations that would be beyond the powers of a typical computer.
This year Volkswagen used a D-Wave computer to demonstrate how it could steer the movements of 10,000 taxis in Beijing at once, optimizing their routes and thereby reducing congestion.
Because traffic patterns morph constantly, the challenge is to gather and analyze vehicle flows quickly enough for the data to be useful. The D-Wave computer was able to process in a few seconds information that would take a conventional supercomputer 30 minutes, said Florian Neukart, a scientist at a Volkswagen lab in San Francisco.
Such claims are met with skepticism by some experts, who say there is no convincing proof that D-Wave computers are faster than a well-programmed conventional supercomputer. And unlike a quantum computer, a supercomputer does not have components that must be kept at temperatures colder than deep space.
“If this were an application where D-Wave were actually faster, then it would be the first time we’d ever seen that,” said Scott Aaronson, a vocal D-Wave skeptic who is a professor of theoretical computer science at the University of Texas at Austin.
“It would be particularly astonishing that this milestone should happen first for a Volkswagen application problem,” Mr. Aaronson said in an email.
Volkswagen executives say they will publish the results of their work with D-Wave computers, allowing outsiders to try to debunk them.
If the D-Wave collaboration proves to be a misstep for Volkswagen, it would illustrate the hazards of big data for companies whose main focus for the past century has been the internal combustion engine. It also reflects the stakes for one of the world’s biggest carmakers.
Suppliers are also gearing up for an era of automotive big data. Bosch, the electronics maker based in a suburb of Stuttgart, said Monday that it would invest 1 billion euros, or $1.1 billion, to build a new factory in Dresden to produce chips for a variety of applications, including the sensors used in self-driving cars.
Bosch prefers to build its own chips rather than buy them from a supplier, said Christine Haas, director for connected services at the company. “When you have done it yourself, then you have a much deeper understanding of the technology,” she said.
Some car companies have decided to concentrate on what they do best and let others handle the computing.
Volvo Cars has been a pioneer in marrying digital technology and automobiles. It has turned to outside providers like Ericsson, a Swedish maker of telecommunications equipment, for computer technology. In May, Volvo said it would install Google’s Android operating system in new cars beginning in 2019. And the company is cooperating with Uber to develop self-driving cars.
But, like Volkswagen, many are trying to develop capabilities in-house. Mr. Stolle of BMW said that the car maker — which hired more information technology specialists last year than mechanical engineers — needs huge data-crunching capability.