A revolutionary combo of multiband radar, lidar, cameras, and “atomic-norm” computing even handles foggy conditions.
I've just learned it's not entirely our fault, as Homo sapiens, that we cause 95 percent of. That's because we haven't evolved the physiological ability to both see far enough ahead and process visual data sufficiently to eliminate"accidents." I learned this when a California company called Neural Propulsion Systems unveiled its AtomicSense Platform sensor fusion product, which it says can sense and interpret enough data to prevent crashes.
NPS wrote a paper theorizing that perceiving the environment far enough, clear enough, and early enough to eliminate roadway deaths requires a data acquisition and processing rate of 100 terabits per second—that's 10 million times the estimated sensory data rate flowing from your eyes to your brain when you're not drunk or distracted.So NPS devised a fully solid-state, system-on-chip sensor suite to do just that, leveraging Department of Defense research.
Today's 77-GHz automotive radar is great at penetrating fog, but it paints a super-blurry picture of what's out there, and raindrops can scatter it. However, radar at 1 GHz barely notices rain, the waves diffract to"see" around curves and corners, and they can even pass through some solid materials. A focused beam of high-frequency radar gives lidar-like resolution but is limited to line of sight.
By digitally steering the radar and lidar beams, the system can more thoroughly"interrogate" voxels of interest—those containing objects near the direction of travel. Empty voxels may get checked 20 times per second, while occupied ones are scrutinized 100 times. Atomic-norm computing allows the AtomicSense Platform to match the performance of conventional sensor suites with 1/50th the transmission power while yielding much higher resolution and vastly more hits on target.
The world has had a good look at"full self-driving" informed solely by cameras; I know I'll feel 10 million times more comfortable with AtomicSense crunching 100 TB of triply redundant data.
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