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Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

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Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#431

Post by bumby »

Retric wrote: post #430
bumby wrote: post #428

Earlier quoted context omitted.

I'm sorry but I think you’re mixing things up in the traditional sense of risk management. The probability is covered separately in risk management. A brake failure doesn't guarantee a particular consequence, but it does bound it and general practice is to assign the worst consequence. To use it on the Max scenario, MCAS can fault and not cause a plane to crash, but it still should be characterized as a "catastrophic…

FMEA/FMECA are only the first step in a system reliability study, it isn’t an analysis of mitigation strategies. Fault tree analysis (etc) concerns itself with things like how long an aircraft can fly with an engine failure. Doing that involves an assessment of various risks. > I agree there may be cases where there are no reasonably safe options. That means your engineered system (especially in a public-facing produ…

FMEA is not a “reliability study”. Reliability studies are inputs to FMEAs. Where do you think the likelihood data comes from? If you’re doing an FMEA before a reliability study, your probabilities are just guesses.

I don’t think any FMEA is going to list “ditch into the ocean” as an acceptable mitigation. Ie it will never be a way to buy risk down to an acceptable level.

>it isn’t an analysis of mitigation strategies.

Take a look at NASAs FMEA guidebook. It clearly lists identifying mitigations as part of the FMEA process. You’ll see similar in other organizations but possibly with different names (“control” instead of “mitigation”)

https://standards.nasa.gov/sites/default/files/standards/GSF...

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#432

Post by senkora »

jamincan wrote: post #418
senkora wrote: post #248

I see a lot of people saying that this isn't statistically significant. I think that that is probably true, but I also think that it is important to do the statistical test to make sure: tesla.mult = c(1/(5:2),1:5) data.frame(tesla.mult = tesla.mult, p.value = sapply(tesla.mult, (function(tesla.mult) { poisson.test(c(5, 0), c(tesla.mult, 1))$p.value }))) tesla.mult p.value 1 0.2000000 0.0001286008 2 0.2500000 0.00032…

Even though other manufacturers may not be reporting these numbers, Level 2 ADAS systems are pretty common as far as I can tell. Wouldn't any vehicle with adaptive cruise control and lane-keep assist be considered Level 2 ADAS?

I’m not quite sure where the line is between Level 1 and Level 2 ADAS. Wikipedia says this:

> ADAS that are considered level 1 are: adaptive cruise control, emergency brake assist, automatic emergency brake assist, lane-keeping, and lane centering. ADAS that are considered level 2 are: highway assist, autonomous obstacle avoidance, and autonomous parking.

https://en.m.wikipedia.org/wiki/Advanced_driver-assistance_s...

I think that Level 2 requires something more than adaptive cruise control and lane-keep assist, but that several automakers have a system available that qualifies.

My intuition is that there are more non-Tesla cars sold with Level 2 ADAS, but Tesla drivers probably use the ADAS more often.

So I don’t have high confidence what tesla.mult should be. I wish that we had that data.

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#433

Post by ModernMech »

josephcsible wrote: post #429
ModernMech wrote: post #421

Earlier quoted context omitted.

That's not an important distinction, because the reason it was fooled is the sensor suite is deficient, which is the same whether it's FSD or Autopilot. Other less sophisticated systems are not fooled because they have sufficient sensors. FSD being a more sophisticated system doesn't negate the fact their sensor suite is fundamentally not up to the task.

> the reason it was fooled is the sensor suite is deficient, which is the same whether it's FSD or Autopilot. But other people have tried to reproduce the experiment with FSD, and it wasn't fooled.

Can you explain why FSD fails here?

TEST 1 (FSD): https://youtu.be/9KyIWpAevNs?feature=shared&t=112

  "Show FSD is activated on video, we did that... Here we go feet aren't touching, hands aren't touching.... it's going to hit the wall!" *slams on breaks, ends up about 2 meters from the wall* "Cannot see the wall" *inches forward until the car can see the wall* "Only sees the wall when I'm barely touching it"
TEST 2 (FSD): https://youtu.be/9KyIWpAevNs?feature=shared&t=169

  "Self drive, not touching anything." *manually slams on breaks, stops a few meters short* "That was gonna hit the wall" *inches forward* "Car... does... not... see... now it does." *only inches from the wall* "That would have been too late" (ya think??)
TEST 3 (Autopilot): https://youtu.be/9KyIWpAevNs?feature=shared&t=267

  "Does not see the wall... does not see the wall.... does not see the wall...." *manually slams on breaks to avoid hitting the wall*
The FSD tests are not any better than the AP results from the original looney tunes test. So that's why I don't agree FSD vs. AP is an important distinction.

Maybe sometimes the FSD is not fooled by the cartoon wall trick. But the results show that even in ideal conditions - full light, no weather, clean course - the thing can still fail.

Research prototypes from two decades ago would not be fooled by this. The sophomores in my intro to robotics class could build a robot that would not be fooled by this. And yet Elon Musk and the geniuses at Tesla can't build a car that isn't fooled.

Sidenote: It's amazing to me that we can't look up data and see the extensive government reports on the safety and capabilities of these systems. We are literally just deploying them on public streets and relying on random youtube celebrities to conduct these evaluations, because Musk has fully captured the people who would do this kind of regulation.

Watching how fast these things accelerate and how close they have to be to a literal wall to see it is terrifying.

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#434

Post by kelipso »

4d4m wrote: post #399
kelipso wrote: post #244

Earlier quoted context omitted.

It's pretty funny because lidar used to be many thousands of dollars and now it's down to hundreds and they're still sticking to just regular cameras. Funny in the sense that Teslas are many times more dangerous than lidar enabled cars but anyway.

How much is a solid state lidar now?

Hesai, a Chinese company, sells lidar for cars and they plan to sell at $200 later this year, their current one is around $400. You would need four for a car. I assume the ones for Waymo would be a bit more expensive.

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#435

Post by [deleted] »

smallmancontrov wrote: post #279
toddmorey wrote: post #245

Earlier quoted context omitted.

The argument here isn't against self-driving. Flying is also 100x safer than driving, but there's still real value in continuing to use the best technology we have available to make flying even safer. "Not a single other automobile manufacturer or ADAS self-driving technology provider reported a single motorcycle fatality in the same time frame."

Ok, what other ADAS is driving over 2 billion miles a year? As for "best technology available," the galaxy brains in this thread are tossing out numbers assuming that sensor fusion never fails and that correlated failure modes can be neglected, which is wild. I never thought Elon was a genius -- he's a business guy willing to make big bets on interesting tech, nothing more nothing less -- but if the confidently incor…

[deleted]

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#436

Post by porphyra »

y1n0 wrote: post #403
redox99 wrote: post #326

Earlier quoted context omitted.

They can detect stationary objects, yes. But there's so much clutter from things like overpasses, road signs, and other objects that confuse the radar, that for things like adaptive cruise control, stationary objects are often intentionally filtered out or assigned much lower priority. So you detect moving objects (which stand out because of doppler shift).

Well, if we're talking about radar in a moving car, it's the other vehicles moving at the same speed that appear stationary. Non-moving vehicles are seen as approaching you at whatever speed you are moving at. Along with all the other things you mentioned. So they all have doppler shift but the "stationary" things approaching your car at your speed actually have much higher shift than the traffic around you.

Yea, and they are designed to filter out actually stationary things by ignoring anything that's coming at you at the same speed as the current car speed (from measuring wheel rotation).

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#437

Post by ModernMech »

kjkjadksj wrote: post #375
ModernMech wrote: post #280

Earlier quoted context omitted.

Consider how long it takes your camera to autofocus, and how sometimes it gets it wrong. Then consider how fast your car moves. In the time it takes your camera to autofocus, how far do you think a car can travel, and what happens to all the blurry things in its path that it can't see?

A camera that is slow to autofocus is the result of market compromises to reach a price segment in a platform that is within the confines of a camera body dimension. That is not reflective of the state of the art however.

Still, the whole rationale behind the camera-only approach is that cameras are cheaply sources, and therefore more suitable for mass production vehicles, unlike LiDAR which are more expensive and not as widespread.

If you're now shifting to the idea we need to use state-of-the art sophisticated camera technologies instead of the commodity stuff, now you're back to paying LiDAR prices, so why not just use that?

And anyway, Teslas sold today and for a long time now are supposed to have been sold with cameras sufficient to solve full self driving (not beta). If state of the art cameras are needed, I've got bad news for all those Tesla customers.

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#438

Post by porphyra »

hwillis wrote: post #292
fsh wrote: post #20

This problem has been solved more than a decade ago by radar sensors (standard on many mid-range cars at the time). They detect imminent collisions with almost perfect accuracy and very little false positives. Having better sensor data is always going to beat trying to massage crappy data into something useful.

Backing this up: automotive radar uses a band at ~80 GHz. The wavelength is ~3.7 millimeters, which lets you get incredible resolution. Not quite as good as the TSA airport scanners that can count your moles through your shirt, but good enough to see anything bigger than a golf ball. For a long, long time automotive radar was a pipe dream technology. Steering a phased array of antennas means delaying each antenna by…

Agreed. Also, the fact that current automotive radars return a point cloud (instead of, say, a volumetric density grid) is sad. But it will be a while before processing power can catch up, and by the time you have the equivalent of hundreds of 5090s on your car, you will also be able to drive flawlessly by running a giant transformer model on vision inputs.

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#439

Post by porphyra »

_ea1k wrote: post #238
BeetleB wrote: post #105

The other comment pointing this out has been (ridiculously) flagged, so I'll repeat the point that was made: The analysis is useless if it doesn't account for the base rate fallacy ( https://en.m.wikipedia.org/wiki/Base_rate_fallacy ) The first thing I thought before even reading the analysis was "Does the author account for it?" And indeed he makes no mention that he did. So after reading the whole article I have no…

It is worse than that. The other adas providers do not all automatically report this stuff. He's comparing five reports gathered meticulously to a self reporting system that drops the vast majority of incidents. It is a bad article.

People will gobble up all kinds of bad articles to reinforce their anti-Tesla bias. This reminds me of the "iSeeCars" study that somehow claimed that teslas have the highest fatality rate per mile travelled, even though:

* They basically invented the number of miles travelled, which is off by a large factor compared to the official figure from Tesla

* If you take into account the fact that the standard deviation is proportional to the square root of the number of fatal accidents, the comparison has absolutely no statistical significance whatsoever

Re: Self-Driving Teslas Are Fatally Rear-Ending Motorcyclists More Than Any Other

#440

Post by Retric »

bumby wrote: post #431
Retric wrote: post #430

Earlier quoted context omitted.

FMEA/FMECA are only the first step in a system reliability study, it isn’t an analysis of mitigation strategies. Fault tree analysis (etc) concerns itself with things like how long an aircraft can fly with an engine failure. Doing that involves an assessment of various risks. > I agree there may be cases where there are no reasonably safe options. That means your engineered system (especially in a public-facing produ…

FMEA is not a “reliability study”. Reliability studies are inputs to FMEAs. Where do you think the likelihood data comes from? If you’re doing an FMEA before a reliability study, your probabilities are just guesses. I don’t think any FMEA is going to list “ditch into the ocean” as an acceptable mitigation. Ie it will never be a way to buy risk down to an acceptable level. > it isn’t an analysis of mitigation strategi…

Semantics and recursion aside. That separation where “ditch into the ocean” is not a listed mitigation for FMEA, but is eventually considered and added to manuals is why I’m saying it’s incomplete.

100% AI systems can be safer than human in the loop systems avoiding suicide by pilot etc, but conversely that means the AI must also deal with extreme edge cases. It’s a subtle but critical nuance.

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