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All we do is hit a button and let it go. Tell us about some of the technology it uses to do that. What information does the car have coming in to figure out where it is, and what the best course to take is? We give the car a sense of where the road boundaries are, and the car tries to figure out a way through those boundaries as quickly as possible.

How much is it using the grip between the tyres and road? Does it have the capability to go faster? What the human drivers do amazingly well is consistently feel out the limits of the car, and push it just a little bit further.

Robot racing car aims for pole position

That is where they have an advantage, and we are trying to learn from them now. We are measuring [ electrocardiography ] signals from race-car drivers, and trying to figure out what is going on in the brain. There are certain patterns that are really suggestive of cognitive workload, and there are other times we can see that signal is absent, and that would suggest to us that it really is a reflexive motion.

We are developing algorithms based on what the humans do.

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For example, by looking at what they are doing with the steering and the brakes and the throttle. So there are some counterintuitive behaviors that racecar drivers are very good at that, that we are learning to encode. How does this research feed back into the development of autonomous vehicles that we might one day drive — or have drive us — on the roads?

One of the nice things about vehicle dynamics is that it is a scalable problem. At the end of the day, you are limited by how much friction you have between the tyres and the road. In our case we are running out of friction because we are going really fast on a racetrack. But you could run out of friction simply because you are driving on a road that has become icy.

The positioning of the camera is purposeful and captures this impossibly accurate near-miss which would more often than not lead to disaster in real life—especially at the speeds cars are traveling at within the game.

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