We came here with one single purpose, we want to challenge a driver and it's one of the best drivers in the world.
We've had great challenges, you know, AI versus human world champions, whether it's in chess, whether it's in Go. This is an
opportunity for AI to come out of that game environment, that controlled world, into a physical environment and that's unique.
My name is Lucas Di Grassi. I'm a professional racing driver and also a member of the board in Roborace.
We're developing self-driving system that will drive your car so we wanted to actually be better than the human and by better we
mean more reliable, more safe. Here at the racetrack we're given extreme conditions.
The ultimate aim is to prove out the software algorithms which we are going to use in all road vehicles, it's the same software
stack which we'll see in the Arrival commercial vehicles. It uses the same means of developing the trajectory, mapping itself,
localising itself in the world.
It makes sense to compare the system against the driver to see does the system bring some advantage to human being?
Every year we do a challenge, which we take myself against the self-driving algorithm.
The challenge is basically as simple as beating Lucas around the track. So he does a lap in the
DevBot version two, and we do a lap with the autonomous system and we're going to try to beat his lap time.
It's a time attack, so Lucas will go out, we give him a full discharge of the battery, so he'll get eight or nine laps, he'll have to
learn the track on the fly. And then we'll do the same with the software driver.
You need to be able to use all of the circuit and you need to be able to use it as well as Lucas will. Start really wide before a
turn, come all the way into the apex and then out all the other way the other side. If we can harvest all that data and process
it we get an understanding as we go round of what the grip is, how hard we can drive around each part and if we can go faster on
the next lap.
You lose in this last corner. Okay the high speed we also lose a bit but this corner is probably where we lose the most, half a
second, and this is where we need to focus now to make sure that we get a better strategy with the car.
Okay, launching in three... two... one...
It didn't crash. He knew that was going to far and stopped. Actually, good job guys.
What we learned last year was that the human is better in adapting. Lucas was way quicker than us to understand the actual
track conditions and to adjust his driving.
He's pushing the vehicle to its real, real limits and what we learned, we realised
where the limits are itself and we have to define them faster, quicker and safer.
What is very interesting to me is to set a standard that I can repeat year by year. The progress has been consistently closing
this gap between human and machine.
Launching in three... two... one...
So a few minutes ago I did some laps. It started to rain in between so track conditions change. So the team here just put the
car out for a few laps while the track is really wet. So this way we have a comparison with the standard track conditions.
The fact that we're just saying the differences between the drivers is the weather between each session and matching that
just shows you how far we've come with the software.
The most important takeaway is that we can be better than a human in one type of environment, like we can beat Lucas only when it's
dry but we really need to be ready for changing environments.
What Roborace is doing is really pushing the boundaries of autonomous driving to the limits of racing in motorsports. In a
couple of years, the world will look back at what we're doing today as something that pushes technology that eventually change
a little bit the world for a better, safer place in the future.