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Comment by cyanydeez | Hacker News Reader

ok, but a care is a few meters wide, isn't that enough for driving depth perception similar to humans

The depths you are trying to estimate are to the other cars, people, turnings, obstacles, etc. Could be 100m away or more on the highway.

ok, but the point trying to be made is based on human's depth perception, but a car's basic limitation is the width of the vehicle, so there's missing information if you're trying to figure out if a car can use cameras to do what human eyes/brains do.

The width of your own vehicle is (pretty much) a constant, and trivial to know. Ford F150 is ~79.9 inches. Done. No sensors needed.

All the shit out there in the world is another story.

You misundestood the assignment.

Write a sonnet about Elon musk.

Humans are very good at processing the images that come into our brain. Each eye has a “blind spot” but we don’t notice. Our eyes adjust color (fluorescent lights are weird) and the amount of light coming in. When we look through a screen door or rain and just ignore it, or if you look outside a moving vehicle to the side you can ignore the foreground.

If you increase the distance of stereo cameras you probably can increase depth perception.

But a lidar or radar sensor is just sensing distance.

Radar has a cool property that it can sense the relative velocity of objects along the beam axis too, from Doppler frequency shifting. It’s one sense that cars have that humans don’t.

To this point, one of the coolest features Teslas _used_ to have was the ability for it to determine and integrate the speed of the car in front of you AND the speed of the car in front of THAT car, even if the second car was entirely visually occluded. They did this by bouncing the radar beam under the car in front and determining that there were multiple targets. It could even act on this: I had my car AEB when the second ahead car slammed on THEIR brakes before the car ahead even reacted. Absolutely wild. Completely gone in vision-only.

The company I used to work for was developing a self driving car with stereo depth on a wide baseline.

It's not all sunshine and roses to be honest - it was one of the weakest links in the perception system. The video had to run at way higher resolutions than it would otherwise and it was incredibly sensitive to calibration accuracy.

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