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Inside Waymo's Secret World for Training Self-Driving Cars

theatlantic.com

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Re: Inside Waymo's Secret World for Training Self-Driving Cars

#101

Post by grkvlt »

jooke wrote: post #64
flamedoge wrote: post #57

> But Peng also presented the position of the traditional automakers. He said that they are trying to do something fundamentally different. Instead of aiming for the full autonomy moon shot, they are trying to add driver-assistance technologies, “make a little money,” and then step forward toward full autonomy. It’s not fair to compare Waymo, which has the resources and corporate freedom to put a $70,000 laser range…

Who's going to buy a car that might tell them they can't drive?

Someone who saves a huge amount on their car insurance because they own such a vehicle (and therefore should never be subjecting the insurance company to claims caused by their impaired driving) I assume?

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#102

Post by 60654 »

Animats wrote: post #46

There's a lot of misunderstanding about self-driving. Mostly because nobody is publishing much. If you want to do it right, you start with geometry. The first step is capturing range imagery and grinding it down to a 3D model of the world. This tells you where you physically can go. That's where we were at the DARPA Grand Challenge over a decade ago. Then comes moving object popout. What out there isn't a stationary…

Thank you! It's so good to see hype free discussion of this stuff.

I would also add that using simulations to test (or train) robots is also not new, and has significant limitations. Robotics has been using simulation since before the Grand Challenge, but what we find is that simulations make simplifying assumptions that don't bear out in real life: simulated sensors are more idealized than in real life, object recognition is idealized, actuators are idealized. But that makes it hard to apply any learnings to the real world, where sensors hallucinate and actuators lie all the time.

And yeah, we _could_ be fuzzing the simulation and adding failure modes, but not many people do. It's hard to simulate these kinds of defects in a usefully realistic way.

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#103

Post by apk17 »

ipsum2 wrote: post #60
stirlo wrote: post #41

Looks like this is the location of the test facility they talk about... https://www.google.com.au/maps/@37.3705986,-120.5747932,237m... Interesting choice of name for their Expressway... EDIT: Apple maps has up to date satellite imagery https://maps.apple.com/?q=37.3718,-120.5749&t=k

Curious - does anyone know why the Apple maps redirect to Google maps? I'm on Chrome.

Fun fact: In tor browser google maps shows the newer imagery, in firefox it's using older images (and also talks german). (Ok, it seems to be tied to the browser language…still…)

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#104

Post by altotrees »

RcouF1uZ4gsC wrote: post #5
altotrees wrote: post #4

Earlier quoted context omitted.

This is kind of what I figured. I get the distinct feeling that any startup that is unable to keep pace (or break new ground) with AI research & development is going to be hurting badly within the next five years. Uber is poaching AI and Robotics talent, read:profs, from Carnegie Mellon for a reason. It is a do-or-die situation it seems.

Great comment. As a nit, I think "poaching" is a bad term. Uber offered to pay these professors what it viewed as what they were worth to it, which happened to be a lot more than what CMU was paying them. The professors accepted of their own free choice. I fail to see why such an action is termed "poaching". We have had enough problems with industry illegally conspiring (see Steve Jobs) to suppress developer pay thro…

Hey there, thanks for the nit. I am kind of a language nerd, so always appreciate a bit of analysis. I see your point "poaching" as a word has had a somewhat problematic historical context attached to it. I guess I used the term relating to it's sub-definition "take or acquire in an unfair or clandestine way."

I found the migration of experts from CMU to Uber fascinating — for two reasons: 1. The geographical proximity in which the acquisition occurred (i.e. a rust belt town with an awesome CS school and a well known Silicon Valley startup on location). 2. The moving from the academy to the private sector of said professors/researchers happened in a way I hadn't seen before. I mean lots of academics work within industry at some point, but this move seemed to carry more weight in the media — maybe because of the institution involved.

Anyway, with that said, lots of the articles and speculation I read about it, for better or worse, painted the acquisition of academics by Uber as a bit unfair. I.e. Uber could and did pay way more than CMU and provided super interesting problems maybe outside the realm of what a professor normally faces in their research, I don't know. It was the "unfair" element portrayed in articles/opinion pieces I based my wording off of. I am in no way suggesting these profs and researchers did anything wrong or did anything but make the right choice for themselves, something we all have to do.

I digress. Word choice noted, problematic history and other associations noted and hopefully I cleared up my choice a bit.

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#106

Post by dxbydt »

Animats wrote: post #46

There's a lot of misunderstanding about self-driving. Mostly because nobody is publishing much. If you want to do it right, you start with geometry. The first step is capturing range imagery and grinding it down to a 3D model of the world. This tells you where you physically can go. That's where we were at the DARPA Grand Challenge over a decade ago. Then comes moving object popout. What out there isn't a stationary…

> If you want to do it wrong, you start out with lane keeping...recognition of common objects...some machine learning....hope for the best

Thank you! Can I ask why the self-driving car programs like the 3-semester Udacity one deliberately focus on going about it the wrong way ? Why spend 1 whole semester on lane detection using trivia like OpenCV, 1 whole semester on object classification using CNNs with Keras, spending so much time on combining lidar & radar data using Kalman filters for moving object tracking .... surely all of these are peripheral issues and the wrong way to go about the business. Then why ? Is it all one big clueless scam ?

To be fair, I am enjoying the course very much as a student. But it's becoming clear from talking to colleagues in the autonomous car industry that what is being taught is not the real deal. This isn't what happens in production, so to speak.

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#107

Post by Retric »

notahacker wrote: post #84
iUsedToCode wrote: post #53

Earlier quoted context omitted.

There arent that many novel scenarios on the road. Sure, Google can't program around the possibility of an airplane falling down on you, but how often does that happen? It doesn't have to be perfect. Just very good and improving. Some time ago google shared a gif of a wheelchair chasing a duck in the middle of the road. The car didn't understand it, so it just stopped. Good enough for me. Obviously, they have a lot o…

Novel scenarios might not be common compared with miles of traffic-following drudgery, but even really bad human drivers deal with novel scenarios on the road more often than they have accidents. Stopping might be a sensible safety protocol in some situations, but it isn't in others (not to mention the situations where the car may stop too late because it doesn't actually recognise that a novel scenario is about to o…

Except self driving cars are paying full attention all the time and can react significantly faster. This causes the difference in stopping distance to be dramatic. Remember, humans are basically going to do the same thing for the first 0.25 seconds in any emergency situation and that's the best case.

So, self driving cars can simply be very cautious without seeming to.

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#108

Post by [deleted] »

Animats wrote: post #46

There's a lot of misunderstanding about self-driving. Mostly because nobody is publishing much. If you want to do it right, you start with geometry. The first step is capturing range imagery and grinding it down to a 3D model of the world. This tells you where you physically can go. That's where we were at the DARPA Grand Challenge over a decade ago. Then comes moving object popout. What out there isn't a stationary…

[deleted]

Re: Inside Waymo's Secret World for Training Self-Driving Cars

#109

Post by losteverything »

dsfyu404ed wrote: post #89
pgodzin wrote: post #28

Earlier quoted context omitted.

Aren't those examples in which it'd be fine for it to be confused? That confusion shouldn't lead to any dangerous situations, just a different speed than other cars. It would also be interesting to know whether Waymo factors in other cars' behavior. If everyone is going 80 while the speed limit is 65, will it factor that in and go 80 or keep with the speed limit?

A slower speed is dangerous to everyone. One car slows down and everyone else needs to get around them. That results in people who would otherwise be content to flow with traffic making aggressive moves to pass the obstruction. These actions catches some people in the other lanes unaware and some of them insensitively hit their brakes (kind of like the people who brake for curves at low speed because "it's what you d…

"Avoid highway braking!" was drilled into us in drivers ed.

Too slow was equal to too fast during drivers ed.

We had a trailer with a simulator screen and a projector, and about 10 or so fake wheels, brakes and accelerator. He would stop the reel and quiz us about the scene (kid on bike about to cross road; kid hidden by truck. ) The instructor had a print out of our actions. Pretty sophisticated for the mid '70s.

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