Video Game Technology to Make Self-Driving Cars Affordable?

A new software that allows a self-driving car to determine its location using a single video camera instead of several laser scanners can shave thousands of dollars from the cost of such vehicles. Ryan Wolcott, a doctoral candidate in computer science and engineering at the University of Michigan, used video game technology to develop the low-cost self-driving car navigation system.

The technology enables cars to navigate using a single video camera, delivering the same level of accuracy as laser scanners at a fraction of the cost. "The laser scanners used by most self-driving cars in development today cost tens of thousands of dollars, and I thought there must be a cheaper sensor that could do the same job," Wolcott said. "Cameras only cost a few dollars each and they're already in a lot of cars. So they were an obvious choice," he said.

His system builds on the navigation systems used in other self-driving cars that are currently in development. They use three-dimensional laser scanning technology to create a real-time map of their environment, then compare that real-time map to a pre-drawn map stored in the system. By making thousands of comparisons per second, they're able to determine the vehicle's location within a few centimetres.

Wolcott's system uses the same approach, but his software converts the map data into a three-dimensional picture much like a video game. The car's navigation system can then compare these synthetic pictures with the real-world pictures streaming in from a conventional video camera.

Ryan Eustice, a U-M associate professor of naval architecture and marine engineering who is working with Wolcott on the technology, said one of the key challenges was designing a system that could process a massive amount of video data in real time.

The team again turned to the world of video games, building a system out of graphics processing technology that's well known to gamers. The system is inexpensive, yet able to make thousands of complex decisions every second.

The team has successfully tested the system on the streets of downtown Ann Arbor. While they kept the car under manual control for safety, the navigation system successfully provided accurate location information.

The system won't completely replace laser scanners, at least for now as they're still needed for other functions like long-range obstacle detection. But the researchers said it's an important step toward building lower-cost navigation systems.