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Deep learning for self driving cars is insane. You might need it for stop signs, but not hitting people should be done with lidar, sonar, radar, and stereo dep

Deep learning for self driving cars is insane. You might need it for stop signs, but not hitting people should be done with lidar, sonar, radar, and stereo depth mapping. A computer does not need to recognize an object to know that it shouldn't hit it if it can safely stop. It should have front and rear lidars, and just stop if anything is ahead no matter what it is, unless something is about to hit you from behind or the side. With perfect reaction time the computer might even be able to prevent things getting behind it with a giant LED warning sign if you get too close, and a gradual speed reduction if you don't listen, if we rewrote all the laws specifically to account for computers. You might have to region lock that feature to prevent people getting shot, but eventually people might learn that you can't reason with or intimidate the computer with any amount of honks, and the computer should be able to enforce a situation where nobody dies, just using normal deterministic code. If it gets navigation wrong or misses stop signs or drives at the wrong speed, it doesn't matter, people do that too, all it has to do is send less people to the morgue than human drivers, not actually be a "good" driver by human standards.

jeffreygoesto 5y ago
The general idea of not caring about the class of objects you want to avoid is ok, but if you drive in rain and snow with a lidar (or even radar), you'll see why it does not work. Way too many false positives. Then you start classifying again.
- eternityforest 5y ago
  At that point you need multiple sensors and stereo depth(Which is usually still learning, but it seems to be pretty good these days). If a person can see it clearly with headlights, LIDAR and radar should be able to, with good enough tech. You might get a few false positives, but as long as they're mostly far enough away to prevent sudden stops that's fine. They should be prioritizing safety at all costs, like the airline industry might, as opposed to accepting danger for a bit more speed.
  - jeffreygoesto 5y ago
    Right, multiple modalities help a lot here. With radar you get pretty close and pretty consistent false positives (that is the reason Tesla dropped it) and with Lidar, instead of a point cloud for the object, snowflakes turn it into two seemingly random ones (the flakes and the remaining object ones). We're not there (yet?) in terms of proper lifting from measurement to object models. You can track long and survive some clutter, but then emergency breaking is hard, because you lack the history of that object.
    - eternityforest 5y ago
      Despite how much I really want them to happen, and how much of my future I planned based on them already existing by now.... I'm not sure we have any business making them until we can do so without AI, or at least without object detection, unless object detection gets a whole lot better, and can be trained to recognize "Tall thing that is not the road" reliably.

jeffreygoesto 5y ago

The general idea of not caring about the class of objects you want to avoid is ok, but if you drive in rain and snow with a lidar (or even radar), you'll see why it does not work. Way too many false positives. Then you start classifying again.

eternityforest 5y ago
At that point you need multiple sensors and stereo depth(Which is usually still learning, but it seems to be pretty good these days). If a person can see it clearly with headlights, LIDAR and radar should be able to, with good enough tech. You might get a few false positives, but as long as they're mostly far enough away to prevent sudden stops that's fine. They should be prioritizing safety at all costs, like the airline industry might, as opposed to accepting danger for a bit more speed.
- jeffreygoesto 5y ago
  Right, multiple modalities help a lot here. With radar you get pretty close and pretty consistent false positives (that is the reason Tesla dropped it) and with Lidar, instead of a point cloud for the object, snowflakes turn it into two seemingly random ones (the flakes and the remaining object ones). We're not there (yet?) in terms of proper lifting from measurement to object models. You can track long and survive some clutter, but then emergency breaking is hard, because you lack the history of that object.
  - eternityforest 5y ago
    Despite how much I really want them to happen, and how much of my future I planned based on them already existing by now.... I'm not sure we have any business making them until we can do so without AI, or at least without object detection, unless object detection gets a whole lot better, and can be trained to recognize "Tall thing that is not the road" reliably.