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Grand Theft Auto V Is Being Used To Help Teach Self-Driving Cars (bloomberg.com)
An anonymous reader quotes Bloomberg:
In the race to the autonomous revolution, developers have realized there aren't enough hours in a day to clock the real-world miles needed to teach cars how to drive themselves. Which is why Grand Theft Auto V is in the mix... Last year, scientists from Darmstadt University of Technology in Germany and Intel Labs developed a way to pull visual information from Grand Theft Auto V. Now some researchers are deriving algorithms from GTAV software that's been tweaked for use in the burgeoning self-driving sector. The latest in the franchise from publisher Rockstar Games Inc. is just about as good as reality, with 262 types of vehicles, more than 1,000 different unpredictable pedestrians and animals, 14 weather conditions and countless bridges, traffic signals, tunnels and intersections...
The idea isn't that the highways and byways of the fictional city of Los Santos would ever be a substitute for bona fide asphalt. But the game "is the richest virtual environment that we could extract data from," said Alain Kornhauser, a Princeton University professor of operations research and financial engineering who advises the Princeton Autonomous Vehicle Engineering team.
The idea isn't that the highways and byways of the fictional city of Los Santos would ever be a substitute for bona fide asphalt. But the game "is the richest virtual environment that we could extract data from," said Alain Kornhauser, a Princeton University professor of operations research and financial engineering who advises the Princeton Autonomous Vehicle Engineering team.
Your eyes are far better at matching light frequencies between both eyes to get the depth mapping correct. Your standard camera can only distinguish 24 bits of light frequency. At that level you get somewhat of a depth map but not a very good one.
Lasers try to get around that limitation by using a frequency the camera can easily pick up and compare between the two images. If you could use the whole image and any frequency, you'd be a lot better off.
That's ultimately the challenge: getting cameras that are not only incredibly sensitive to light frequency, but also very high resolution. Or they'll need to get the cameras looking around just like your eyeballs.
In a 3D mapped world, all the depth information is 100% accurate.
They'd need to render 48-64 bit color to emulate what might be possible in the real world to get accurate depth information.
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