Volvo reconstructs crashes with AI in virtual worlds to make safer cars

“One thing is that we develop this in-house now, so instead of relying on suppliers with long deadlines and long process and sending requirements back and forth, we develop the software,” said Erik Coelingh, VP of product at Zenseact, an ADAS developer owned by Volvo.

“If there’s something, we solve it in a day,” Coelingh said. “It’s so much faster. So we iterate much faster. As Bakkenes said, we’re all testing with the new software every single day. So the innovation speed is fundamentally different than before, and the way we try to use this is to really build safety and go toward lower accident rates in a pace that we’ve never seen before.”

Among the advantages of moving to SDVs is that it’s much easier to simulate them since the entire software stack can be run virtually. That’s why Volvo has built one of the largest data centers in Europe: to be able to run those sims.

Like a lot of other companies out there, Volvo has turned to AI to speed up the development process. But how does such a safety-conscious company like Volvo know it can trust the output of those end-to-end algorithms?

“Gaussian splatting is a technology where we can take one point, one traffic scenario, and explode it into thousands or tens of thousands of scenarios from this real-world data,” Coelingh said. “And then we can manipulate one scenario into a thousand different scenarios, and then we can enclose the simulation and test our software against this.”

Autonomous vehicle developers have been simulating in environments like Unreal Engine for some time now. “That’s very visual; that works for camera data. But here we’re probing lidar data, camera data, radar data, and we reconstruct the scene with the neural net, and then do the manipulation and use closed-loop simulation,” Coelingh said. “So this is a way of, really fast, be able to test your software against a huge, huge amount of different scenarios that are representative for the real world.”