Driving simulator teaches autonomous cars to drive properly
An open-source driving simulator has been launched that automakers can use to test their autonomous vehicle technology in realistic environments. CARLA (Car Learning to Act) repeatedly retests vehicles against certain criteria, increasing the performance of the technology by forcing it to evaluate scenarios in different ways. Researchers at Intel Labs have collaborated with the Toyota Research Institute and the Computer Vision Center in Spain to create the technology.

In each of these circumstances, a self-driving car must make good decisions, even though the likelihood of coming across them is small. And that raises an important question: how can carmakers train and test their vehicles when these events are so rare?

Today, we get an answer of sorts thanks to the work of Alexey Dosovitskiy at Intel Labs and a few pals at the Toyota Research Institute and the Computer Vision Center in Barcelona, Spain. They’ve created an open-source driving simulator that carmakers can use to test self-driving technologies under realistic driving conditions.

The system, called CARLA (Car Learning to Act), simulates a wide range of driving conditions and repeats dangerous situations endlessly to help learning. The team has already used it to evaluate the performance of several different approaches to autonomous driving.

Driving simulators are not new. There are numerous realistic driving and racing simulators, many designed for gaming. Various autonomous driving groups have used them to test their technologies.

But none of these simulators provide the kind of feedback that autonomous driving systems need to train effectively. Neither do these systems allow significant control over driving conditions or the actions of other agents.

Racing simulators do not usually have crossing traffic or pedestrians. And city simulators such as Grand Theft Auto do not give control over the weather, the position of the sun, the behavior of other cars, traffic signals and pedestrians, cyclists, and so on.

And these proprietary systems do not give the kind of technical feedback that autonomous driving systems need to learn.