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I mean what does lidar do but tell you distance? A rangefinder optic from 1940 can also tell you distance with two little offset windows purely optically and ac

I mean what does lidar do but tell you distance? A rangefinder optic from 1940 can also tell you distance with two little offset windows purely optically and accurately. Millions of rolls of films shot on this principle of optical distance finding. And yet, this is no good now, because IMO its musks idea and thats enough to poison it among the armchair engineers than any other reason. Telling to this point is how everyone just parrots the same comment that optical self driving is bad without actually providing evidence to support their point. Just arguing on precedent established in forums and social media.

ModernMech 2y ago
What poisons the idea among engineers is not that Musk came up with it (he didn't), but that he can't justify it using the language we speak, either by theory or by practice. Instead what we get from him is marketing, stunts, keynotes, sleights of hand, bravado, exaggerations, unfulfilled promises, premature rollouts of untested tech... the man is an anti-engineer, it's hard to trust him. What made cars successful at the DUC was omnidirectional 3D distances to everything around you provided by the Velodyne LiDAR. So if we have a way to get that kind of data without a LiDAR, that would be fine. Moreover, what a LIDAR gives you is an honest-to-god measurement. This whole idea of using deep learning to get range data from camera data is not measuring anything, it's making an inference. Which is why it's fooled by a looney tunes wall. And like I said, we lack any inference engine that is better than the human brain. So betting your entire strategy on an inference engine that doesn't exist, bucking industry practice and the consensus of the engineering community, gets the following results: - The NHTSA’s self-driving crash data reveals that Tesla’s self-driving technology is, by far, the most dangerous for motorcyclists, with five fatal crashes that we know of. - This issue is unique to Tesla. Other self-driving manufacturers have logged zero motorcycle fatalities in the same time frame. - The crashes are overwhelmingly Teslas rear-ending motorcyclists. If this problem is unique to Tesla, and Tesla is unique in relying solely on optical sensory input, then we can conclude relying solely on optical sensory input is bad. Nothing to do with the fact that Musk is the champion.
crote 2y ago
There is a huge difference between measuring the distance to a single target a few miles away, and measuring the distance to dozens of moving, accelerating, and overlapping objects in close proximity to each other and to the reference point. Besides, rangefinding optics weren't exactly amazing in the 1940s either. It's why the introduction of radar made such a massive difference in naval warfare.
- kjkjadksj 2y ago
  Autofocus systems are designed to stop race cars in travel today already. And besides, why argue hypotheticals here when I look out my window and I see teslas self driving just fine? The system is proven despite your feelings about it. And if it was truly unsafe or compromised we'd have seen a good deal of evidence a this point what with the amount of users self driving and the mileage they've been traveling, not to mention how many people in the media are so desperate to find such evidence and publish some pulitzer attempt about it given the sentiment around Musk these days.
  - ModernMech 2y ago
    > why argue hypotheticals here when I look out my window and I see teslas self driving just fine? I'll reiterate: 2019 - Tesla didn’t fix an Autopilot problem for three years, and now another person is dead That's not a hypothetical. How do you figure this result indicates the Tesla theory of camera-only navigation is working out "just fine"? This level of professional negligence should be considered a crime. > And if it was truly unsafe or compromised we'd have seen a good deal of evidence We see that evidence all the time. Teslas veering into oncoming traffic, hitting parked vehicles, driving through loony tunes walls where other cars stop, being fooled by smokescreens where other cars are not, and decapitating multiple people in a similar way that would have been mitigated by LiDAR. And now apparently real-ending motorcyclists. This whole self driving scam is an exercise in the 80/20 rule. They spent 20% of the time to get 80% of the results, and that's why you claim "I see teslas self driving just fine" But Tesla has been promising the other 20% will be here in 5 years for 10 years. That last 20% is the difference between the system being "Full" self driving and a fraud. Right now what we see is a vaporware fraud, and they're not going to be able to deliver.
ndsipa_pomu 2y ago
The important thing about LIDAR is not so much that it is reporting a distance, but that it is reporting distances to actual objects. Cameras don't distinguish objects and so there has to be a lot of processing to try to tease out the objects from the background and this appears to be what's causing issues with Teslas.
mturmon 2y ago
It does not seem like you have much experience with either LiDAR or stereo vision. These systems have well known performance characteristics and advantages. LiDAR has its limitations (in terms of point density and scan rate, and cost), but its range estimate accuracy just blows stereo vision away for automotive settings. The error on range estimates from stereo “disparity” goes up as range squared for fundamental-physics reasons. Accurate calculation of disparity relies on well calibrated optics (clean, physically rigid) and it’s easy to disrupt that. Stereo is also target-sensitive. Stereo ranging is enhanced by certain target features, like large, smooth surfaces with texture (say, stucco walls, or car grilles). It is made more difficult by smaller target surfaces with weird curvature. I’m sure that stereo that did well on auto-sized surfaces would do much worse for pedestrian or motorcycle (size and shape) surfaces.

ModernMech 2y ago

What poisons the idea among engineers is not that Musk came up with it (he didn't), but that he can't justify it using the language we speak, either by theory or by practice. Instead what we get from him is marketing, stunts, keynotes, sleights of hand, bravado, exaggerations, unfulfilled promises, premature rollouts of untested tech... the man is an anti-engineer, it's hard to trust him. What made cars successful at the DUC was omnidirectional 3D distances to everything around you provided by the Velodyne LiDAR. So if we have a way to get that kind of data without a LiDAR, that would be fine. Moreover, what a LIDAR gives you is an honest-to-god measurement. This whole idea of using deep learning to get range data from camera data is not measuring anything, it's making an inference. Which is why it's fooled by a looney tunes wall. And like I said, we lack any inference engine that is better than the human brain. So betting your entire strategy on an inference engine that doesn't exist, bucking industry practice and the consensus of the engineering community, gets the following results: - The NHTSA’s self-driving crash data reveals that Tesla’s self-driving technology is, by far, the most dangerous for motorcyclists, with five fatal crashes that we know of. - This issue is unique to Tesla. Other self-driving manufacturers have logged zero motorcycle fatalities in the same time frame. - The crashes are overwhelmingly Teslas rear-ending motorcyclists. If this problem is unique to Tesla, and Tesla is unique in relying solely on optical sensory input, then we can conclude relying solely on optical sensory input is bad. Nothing to do with the fact that Musk is the champion.

crote 2y ago

There is a huge difference between measuring the distance to a single target a few miles away, and measuring the distance to dozens of moving, accelerating, and overlapping objects in close proximity to each other and to the reference point. Besides, rangefinding optics weren't exactly amazing in the 1940s either. It's why the introduction of radar made such a massive difference in naval warfare.

kjkjadksj 2y ago
Autofocus systems are designed to stop race cars in travel today already. And besides, why argue hypotheticals here when I look out my window and I see teslas self driving just fine? The system is proven despite your feelings about it. And if it was truly unsafe or compromised we'd have seen a good deal of evidence a this point what with the amount of users self driving and the mileage they've been traveling, not to mention how many people in the media are so desperate to find such evidence and publish some pulitzer attempt about it given the sentiment around Musk these days.
- ModernMech 2y ago
  > why argue hypotheticals here when I look out my window and I see teslas self driving just fine? I'll reiterate: 2019 - Tesla didn’t fix an Autopilot problem for three years, and now another person is dead That's not a hypothetical. How do you figure this result indicates the Tesla theory of camera-only navigation is working out "just fine"? This level of professional negligence should be considered a crime. > And if it was truly unsafe or compromised we'd have seen a good deal of evidence We see that evidence all the time. Teslas veering into oncoming traffic, hitting parked vehicles, driving through loony tunes walls where other cars stop, being fooled by smokescreens where other cars are not, and decapitating multiple people in a similar way that would have been mitigated by LiDAR. And now apparently real-ending motorcyclists. This whole self driving scam is an exercise in the 80/20 rule. They spent 20% of the time to get 80% of the results, and that's why you claim "I see teslas self driving just fine" But Tesla has been promising the other 20% will be here in 5 years for 10 years. That last 20% is the difference between the system being "Full" self driving and a fraud. Right now what we see is a vaporware fraud, and they're not going to be able to deliver.

ndsipa_pomu 2y ago

The important thing about LIDAR is not so much that it is reporting a distance, but that it is reporting distances to actual objects. Cameras don't distinguish objects and so there has to be a lot of processing to try to tease out the objects from the background and this appears to be what's causing issues with Teslas.

mturmon 2y ago

It does not seem like you have much experience with either LiDAR or stereo vision. These systems have well known performance characteristics and advantages. LiDAR has its limitations (in terms of point density and scan rate, and cost), but its range estimate accuracy just blows stereo vision away for automotive settings. The error on range estimates from stereo “disparity” goes up as range squared for fundamental-physics reasons. Accurate calculation of disparity relies on well calibrated optics (clean, physically rigid) and it’s easy to disrupt that. Stereo is also target-sensitive. Stereo ranging is enhanced by certain target features, like large, smooth surfaces with texture (say, stucco walls, or car grilles). It is made more difficult by smaller target surfaces with weird curvature. I’m sure that stereo that did well on auto-sized surfaces would do much worse for pedestrian or motorcycle (size and shape) surfaces.