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In the last couple of years the idea of self-driving cars has become less of a pipe dream. Companies such as Google, Tesla, and Apple, which began to produce and test their fully functional autonomous vehicles, and companies like Uber, have raised millions to fund their efforts. One of the challenges is that these companies do not yet have the expertise to build their own driverless cars; thus, their cars simply act more like a real-life driving machine.

Now comes the first car in this new range to hit the streets. A research prototype by a company named B2B Mobility, based out of the U.K, is a concept car that is based on technologies from Google’s Waymo autonomous driving project. The car’s main focus is on technology for autonomous vehicles.

A quick peek reveals that this technology has not yet seen any tests of its abilities in the real world, hence its name. In this car, which was tested in London last month, it is possible to see what is possible with these new technology developments.

This car is driven by an autonomous system, one that relies on an onboard computer, and is capable of driving itself. However, as per Google’s autonomous car website, they still have a lot of work to do: “In the real world we don’t yet know what a semi-autonomous car is doing at speed, what information the car has and when it is doing what it is doing.”

This is probably what is behind the decision to name the car after the late, amazing computer scientist Alan Turing, who helped develop computers that could break codes with his work on the BEAM supercomputers.

A look at the technology can be seen below:

So far, this car shows to be able to handle its own steering and braking, making it a lot better than the self-driving cars that are on the road today. That said, there have still been some failures in regards to accidents involving these vehicles. At the time of writing, they have to date had 15 incidents since they began testing in 2017.

The car has an onboard computer at the rear of the car. This allows the computers to learn from every test and even from its own past mistakes, allowing it to improve the system for future trials.

So far, the tech has been

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