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Why Tesla removed radar and ultrasonic sensors [video]

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Re: Why Tesla removed radar and ultrasonic sensors [video]

#151

Post by galangalalgol »

YZF wrote: post #113
aeternum wrote: post #93

Earlier quoted context omitted.

Lack of focus is a major problem for companies and we all know that tech debt leads to increased bug counts. Team focus on vision which is by far the highest accuracy and bandwidth sensor allows for a faster rate of safety innovation given a constant team size.

Tesla's cameras often get blocked by rain or blinded by the sun or not see that well in the dark. It's really hard to imagine those cameras replacing the ultrasonic sensors which do a pretty good job at telling you where you are when you're parking etc. I can't see how the camera is going to detect an object at pitch dark and estimate the distance to it better than an ultrasonic sensor. But hey, if people ding their…

One interesting side effect of only using visual sensors is that the failure modes will be more likely to resemble human ones. So people will say "yeah, I would have crashed in that situation too!". With ultrasonic and radar and ladar it may make far fewer mistakes but it is possible they might not be the same ones people make, so people will say "how did it mess that up?"

Re: Why Tesla removed radar and ultrasonic sensors [video]

#152

Post by mynameisvlad »

jfabre wrote: post #111
jeffbee wrote: post #97

Earlier quoted context omitted.

Tesla engineers are currently doing post-commit review of Twitter source code. Focus is the last thing I would credit them with.

do you have data to back this claim?

Have you been keeping up with the Twitter deal? This was covered Friday.

https://www.bloomberg.com/news/articles/2022-10-27/tesla-eng...

And the corresponding HN thread: https://news.ycombinator.com/item?id=33365065

Re: Why Tesla removed radar and ultrasonic sensors [video]

#153

Post by moffkalast »

aeternum wrote: post #124
petilon wrote: post #108

Earlier quoted context omitted.

But it doesn't appear to be helping. Here's an example accident where depth data from Lidar would have helped: "Tesla later said that during the crash, Autopilot’s camera could not distinguish between the white truck and the bright sky." https://www.nytimes.com/2021/12/06/technology/tesla-autopilo...

The crash you referenced occurred in 2016 when they were using radar on the cars and I don't believe they were yet using raw photon counts nor did the NN have any voxel-based memory as it does now.

> any voxel-based memory

Haha, any WHAT?

Seriously though do you have any more info on that, it sounds intriguing. Where and how do voxels come into play in a 2D NN?

Re: Why Tesla removed radar and ultrasonic sensors [video]

#154

Post by dreamcompiler »

It's obviously a stupid decision to remove a direct source of range data (radar and ultrasound) in favor of an indirect one (vision).

But on second thought this doesn't bother me that much because Tesla FSD is absolute garbage even with radar (and I don't think Tesla will get away with selling the FSD snake oil for much longer), so if vision-only is good enough for the base-level lane-keeping autopilot functionality and it makes the cars cheaper, maybe that's a good thing.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#155

Post by Nomentatus »

dreamcompiler wrote: post #146
3apo wrote: post #20

Earlier quoted context omitted.

I feel the other reason is that Tesla has not figured out a way to put Radar into their ML pipeline. If you take the Range-Doppler Map from the radar as the 'pixel' map, that data is inherently very dependent on the scenario and the radar sensor intrinsic parameters. This variability in what the radar sees in the RD space is what makes this a challenge for ML/AI pipelines. If Tesla were to 'fuse' information from the…

Exactly. Radar gives you direct range data; camera pixels need to be processed by ML to infer range data, and the latter is never going to be as close to ground truth as the former, so the former should be prioritized.

Not quite. Light waves are so short you'll get some return from almost any surface, because the surface is rough at the scale of such a small wavelength. This isn't true of radar, and it's not just what substance the outbound radar hits but how flat it is, too. You may get no return. Or almost none. Even smooth, round steel posts give very little return IIRC. There's also an echo problem with long waves such as sound and radar, particularly in urban areas. In which case what you think is a firm direct return may be a very indirect return that happens to be in synch with the signal you were expecting.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#156

Post by mynameisvlad »

ajross wrote: post #14
elteto wrote: post #6

Earlier quoted context omitted.

> The LIDAR folks were wrong, basically. This is far, far from settled at this point.

No, it's over. Look, the LIDAR value proposition was necessarily "Yes, we're outrageously expensive and involve major tradeoffs in physical design of the vehicle, but vision can simply never do what we do". And... vision does. It does, every day. On hundreds of thousands of cars. In point of fact FSD beta vehicles are out there every day in environments where LIDAR has never been deployed, nor likely ever tested. And…

Do you actually have FSD Beta? I do. It's not anywhere near the level of polish that you seem to imply it is. It gets things wrong all the time. Turns are downright dangerous.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#157

Post by lostsock »

petilon wrote: post #107
lostsock wrote: post #74

Earlier quoted context omitted.

That video is from 2020, but Tesla didn't remove radar until 2021. Meaning that the crash occurred with radar still active, which I feel just backs up what Karpathy was saying.

Well, the car may have had radar hardware but there are questions as to whether the software was using it: https://www.nytimes.com/2021/07/05/business/tesla-autopilot-... Excerpt: Mr. Rajkumar of Carnegie Mellon, who reviewed the video and data at the request of The Times, said Autopilot might have failed to brake for the Explorer because the Tesla’s cameras were facing the sun or were confused by the truck ahead of…

Because radar is not good at picking up stationary objects and/or has to filter them out:

https://www.wired.com/story/tesla-autopilot-why-crash-radar/

Re: Why Tesla removed radar and ultrasonic sensors [video]

#158

Post by dmix »

YZF wrote: post #132
FreakLegion wrote: post #62

Earlier quoted context omitted.

> In other words, the results are better, but not enough to make up for the fact that Telsa can't support additional sensors without incurring a prohibitive amount of additional risk to Tesla. Risk to passengers doesn't appear to be a consideration. You may be right about the actual decision process Tesla went through, but Karpathy is right in principle. One of the first things he says is "there can be problems with…

Taking his point to the extreme why use 8 cameras? just use 4? 1? One photo-diode? Cameras can also fail at run-time there can (and is) be variability in how they're mounted, in the lenses, in the sensors. They can get blinded or not get enough light. Their cabling can fail random components can fail. Tesla has claimed that vision outperforms vision+radar but anecdotal reports don't seem to support that conclusion. I…

You could take any one single point in a complex multifaceted argument to the extreme and basically strawman it to death. But that’s not helpful.

I believe his point was to provide a new perspective on the problem, not to reduce the problem to a single reason. I highly doubt the only reason Tesla chose to use vision only in the short term was motivated by a single datapoint.

Even if it was the most important point... in this one person (on a large team’s) mind... it doesn’t necessarily mean it was the most important in the sum of the complex process it took to get to the decision.

So I don’t really see the value in taking it to the logical maximum because it’s not only illogical that they would be evaluating this one idea in isolation but even on its own they would still be balancing the optimal performance they got from x vs the optimized value they got from y, then compare it to the teams ability to work with both x+y(+z) at the same time.

For ex: You’d probably need 8 cameras pointing different directions vs one highly capable rapidly spinning LiDAR to even compete with it, so why even ask? These problems a) always have context and b) can't be so easily simplified and broken down.

Although you might make a good point that Tesla used this same poor logical-maximum reasoning to determine why not get rid of ALL sensors besides vision.

Re: Why Tesla removed radar and ultrasonic sensors [video]

#159

Post by dreamcompiler »

api wrote: post #77
Nomentatus wrote: post #58

Earlier quoted context omitted.

They do "fall off the edge of the world" a lot; but so do human neural networks; I've seen a bad crash as a result of a human simply pulling out of a driveway right in front of a motorcycle, 'cause they're rare. She had tagged the motorcycle as a bike while it was farther away, then boom. Her interpolation (while checking the other side) didn't work, and her averaging over uncertainty didn't work either because motor…

I see surprisingly little discussion of overall statistics on safety of self drive vs humans, and what I do see is often self reported by companies or by equally potentially biased sources in the media. I’ve searched many times and a straightforward stat seems hard to find.

There's still too much apples and oranges for direct comparison. Tesla FSD doesn't make some of the mistakes human drivers do (like dozing off or being drunk) but it introduces new mistakes humans rarely make (like driving under semi trailers crossing the road).

Re: Why Tesla removed radar and ultrasonic sensors [video]

#160

Post by davidgay »

aeternum wrote: post #96
petilon wrote: post #33

I didn't find his answers particularly convincing. His answer focused on costs mainly, and how "the best part is no part". We have already seen multiple accidents caused by camera's limitations [1] which would not have happened if Tesla used Lidars. Cameras have poor dynamic range and can be easily blinded by bright surfaces. While it is true that humans do fine with only eyes, our eyes are significantly better than…

The dynamic range is the reason Tesla know counts photons rather than use traditional camera processing. They basically remove the concept of exposure entirely and simply pass the sensor photon counts to the neural net. This approach not only simpler as it removes photo processing/encoding but the result is that the NN can operate with a very high dynamic range similar to the human eye and in many cases can be sensit…

> They basically remove the concept of exposure entirely and simply pass the sensor photon counts to the neural net.

That sentence does not make sense. There's no such thing as a count without a corresponding interval that count occurred over. That interval is the exposure.

You can of course do lots of (very) short exposures to avoid sensor saturation. That's "just" a movie at a very high frame rate. And then you can post-process this in lots of exciting ways, align the frames, average them, etc, etc.

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