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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 wh
by 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 agoAt 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 agoRight, 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 agoDespite 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.