Driverless car learns to perform high-speed turns without crashing

J. Christian Gerdes and his colleagues at Stanford University in California used a type of artificial intelligence algorithm called a neural network, which is loosely based on the neural networks in our brains, to create the self-driving system.

They trained the neural network on data from more than 200,000 motion samples taken from test drives on a variety of surfaces, including on a mix of snow and ice at a track near the Arctic circle…

One challenge of the neural network is a lack of insight into how it works, says Gerdes. “If you give it a set of conditions it hasn’t seen before, it may extrapolate in ways that are completely wrong,” resulting in potentially dangerous steering controls, he says.

The researchers are now building safety features into the system to check its decisions are reasonable.