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Comment by tim333 | Hacker News Reader

It's hard to say for sure they are no where near full autonomy in their research although their current vehicles crashing into barriers and fire trucks obviously don't cut it.

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I'm only commenting on what little there is to glean about the compute, but there are so many other red flags about their autonomous development strategy. Crippling per-unit cost constraints, No Lidar, SLAM-lite, ANN heavy, insufficient redundancy and they've got a major data collection problem because they're relying on what they can get over the air. Plus Musk scared away most of their their top engineers.

Serious question- why is LIDAR so important? Obviously it’s possible to drive without it (humans do it), so it’s conceivable that eventually machines will be able to do it as well... So I’m guessing your point is, that won’t happen anytime soon and LIDAR is the fastest way to market; can you confirm/expand/clarify?

Estimating distances robustly is very important for navigation. LIDAR is accurate at relevant distances and most importantly very robust against environmental effects. Without LIDAR you can use stereoscopic vision (like human with two eyes) but that is very demanding, not that accurate, and very error prone. Sure, human can do it somewhat well, but eye and brain are extremely complex things to implement (and it still takes years to learn to understand what you see).

Personally, I’d refuse to implement self-driving vehicle without at least a ”backup LIDAR” to check vision system results. Otherwise you are forced to assume stuff like ”things at stand still are either above the road, beside it, or just shadows”, causing crashes when there is suddenly a stopped car in front of you. (If you didn’t do that assumption, you would be dodging shadows and other clutter..)

[source: I’ve been researching vision algorithms in a related field.]

>> Without LIDAR you can use stereoscopic vision (like human with two eyes) but that is very demanding, not that accurate, and very error prone.

Because that isn't how people judge distances, at least not distances beyond a few feet in front of their faces. Plenty of people with only one eye do very well. It is a difficult problem because we use a variety of techniques and 'hardware' when estimating distances and speeds. Car companies are trying to do with one tool (ie lidar) something we do with many.

Yep, we do huge amount of assumptions to derive ”model of a world” from quite limited amount of data. And we do lots of mistakes without ever realising it. Fortunately, most of those mistakes are irrelevant, and safety margins let us correct most of the relevant mistakes. Rest become accidents.

I guess the same logic applies directly to self-driving cars as well..

> Without LIDAR you can use stereoscopic vision (like human with two eyes)

At any but very close distance, don't humans mostly use a combination of lighting cues, a priori knowledge of actual size vs. apparent size, motion parallax, and other flat-image cues instead of stereoscopy?

But, yeah, LIDAR cuts through all that, too.

You can use stereoscopic using the full width of the car as the baseline instead of eye distance. Humans have a pupillary distance of about 60mm which is good for about 10 meters (possibly much more: https://jov.arvojournals.org/article.aspx?articleid=2191614). A Model 3 is over 6 feet in width, so the pupillary distance is thus 30 times that of humans, and so should be good to about 300 meters, which is comparable to high end LIDARs (although the stereoscopic approach won't be as precise at those distances).

Anyway, if LIDAR becomes small and cheap, Tesla can just strap it on.

Waiting for someone to state that last point. Lidar is still not cheap enough.

That is until it rains and LIDAR falls flat on its face. LIDAR Is Great for training in perfect rainless conditions. For everything else we’ll have to use other tech, very likely camera based. Which is what tesla is doing.

Whether this will succeed is another question.

I find the "humans can do it with eyes" argument pretty weak. Humans also have brains, which are doing most of the heavy lifting. With something like LIDAR, you're shifting more of that heavy lifting into the sensors, so that you don't have to go as deep into trying emulate the human brain in processing. It's such an obvious point.

Yeah, a direct a distance measurement is much more straightforward than the integration of all the monocular and binocular depth cues human perception relies on.

The standard of safety for autonomous drivers will have to be far beyond parity with humans. Humans cause car accidents all the time. LIDAR gives unambiguous depth and probably much easier object segmentation, no complexity or reasoning required like computing from stereo images.

Good point, plus if you have to choose between having LIDAR and acceptable self-driving capability in 3 years, or no LIDAR and acceptable self-driving capability in 10 years, I think most people would prefer the first option.

Sure, but then you're still left with the unsolved problem of getting lidar quality depth maps out of video in all lighting and weather conditions.

Musk commented about LIDAR in a prior earnings call[1]. Tl;dr he believes that LIDAR is a short-term crutch that distracts from the real long-term challenge, which is the machine learning, not the sensors.

[1] https://www.youtube.com/watch?v=FaW85fIos64&t=21m40s

Tesla autopilot needs all the short term crutches it can get.

Supposed to be fully autonomous since, what, 18 months ago? How about that SF->NY demo?

He can say whatever he likes, the proof is in the pudding.

If they were anywhere near full autonomy that LA-to-NYC demo they keep promising would have already happened.

Elon mentioned on the Q2 conference call yesterday that specific demo is easily doable.

He also added that it would be sort of cheating, because that's a very defined route and he prefers it to be able to be much more dynamic. i.e. pick any two US cites and the car will drive you there.

Elon said the exact same thing in the Q4 2017 earnings call. And then said they would still do the demo in the next 3-6 months. It's been 6 months and this "easily doable" demo has still not been done. Tesla has shown zero evidence of their self driving program making any meaningful progress.

http://www.autonews.com/article/20180208/MOBILITY/180209770/...

>Tesla has shown zero evidence of their self driving program making any meaningful progress.

Google's autonomous efforts far precedes Tesla, yet they have not out in the market yet. I would say on the contrary, they made significant strides in a short amount of time even after a complete overhaul Mobileye (AP1) to an in-house solution (AP2/2.5) https://vimeo.com/192179727

Has Tesla demonstrated any progress whatsoever since that 3 minute demo video they posted over a year and a half ago? If they were really making amazing progress they would have shown it off. Tesla LOVES showing off their tech when it's actually working, and it is often very impressive.

Waymo has been operating a real actual passenger service for over a year now. They drive tens of thousands of miles a day. They're "not out in the market yet" only in the sense that they're not charging money for it yet, which they seem to plan on doing soon.

https://www.bloomberg.com/news/features/2018-07-31/inside-th...

There are a number of routes one can take to get from LA to NY. Elon is stalling because he knows that "Autopilot" isn't capable of making the trip.

>Elon is stalling because he knows that "Autopilot" isn't capable of making the trip.

I can only assume then that you have some kind of insider info to support your claim?

I'm not the one claiming that Autopilot is able to make a cross-country trip but delaying the test because it would be "too easy" to prove anything. If it were actually that easy, Tesla would have done it, because Musk has never passed up the chance for that sort of publicity.

Ergo, logically, if Tesla has not performed such a test, it is strong evidence that Autopilot is not currently capable of passing it.

Is "finding roads between two arbitrary cities" the hard part of self-driving?

I think that "using arbitrary roads" is a relatively hard part of self-driving.

That's navigation, and that's actually a solved problem. Actually following the roads...oh look, that's a nice set of traffic cones. What could that possibly mean? IDK, just continue through it.

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