The robo racing cars accelerating driverless tech

Johannes Betz is not your typical racing car driver.

For a start, he doesn’t get in the vehicle – it’s driverless. As a post-doctoral researcher, he is in charge of the Technical University of Munich’s entry in the Roborace motorsport competition, now in its first competitive season.

All these cars are electric and self-driving. “We started in early 2017, when my professor saw this in a newspaper,” he says.

“Each month, we have to develop our software a little further, and then go to an event – yeah, like Formula 1,” he laughs.

Each team – the University of Pisa and electric van start-up Arrival also compete – writes software for an identical racing car, currently the DevBot 2.0, which is capable of speeds over 200mph (322km/h).

It is guided by six cameras, two radars, 18 ultrasound sensors, and five lidar [light detection and ranging] sensors. The onboard computer processor is capable of 24 trillion operations a second.

It was the first racing car to establish a fully autonomous official record at the Goodwood Hill Climb, an important motorsport event in England’s West Sussex, on 13 July.

This narrow, winding 1.86 km (1.16-mile) track climbs 150m (492ft) round slippery bends, hay bales, and flint walls.

And DevBot navigated it in 66.96 seconds – eight seconds faster than an unofficial attempt last year.

Now “there’s around twelve seconds left for the AI (artificial intelligence) to find” before it can match the best human drivers, says Bryn Balcombe, Roborace’s chief strategy officer.

Of that, “six seconds we think is easily gained, and then you’re starting to get into the unknowns.”

But what is the point of racing driverless cars?

It’s an important way to assess the quality of the sensors and cameras which autonomous vehicles (AVs) will rely on, explains Mr Balcombe.

And “testing performance limits on real roads is not something, as a member of society, I’m 100% comfortable with,” he says.

He plans to introduce obstacles for the DevBots to navigate, such as slower-moving lorries and tractors. Overtaking is the hardest race course task to automate, says Dr Betz.

The ultimate aim is to find out whether driverless cars can eventually perform at a level so you can’t detect it’s an AI.