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

310 points by jpm_sd 9y ago

altotrees 9y ago
Clearly the progress being made in the area of self-driving cars is undeniable. Seeing the articles and discussions crop up on a daily basis are making me wonder if we are headed for an AI Winter scenario in this area within the next decade or if this is the real deal and we will see self-driving cars at dealerships within 20 years. This is so far from being my area of expertise. Just one observer's thoughts/questions. Insane how far we have come so quickly, at any rate.
- arcanus 9y ago
  I don't disagree that AI is over-hyped. However, I think the research environment is not as likely to dry up this time. That is because much of the machine learning research is coming from industry, particularly the mega-corps. And for extremely important disruptive events such as AI, they are willing to drop $$ into collecting a stable of research scientists to not fall behind in this space. So while the AI winter was driven by a drop in academic and government spending on research, I think our present situation is far less likely to result in a similar drying up. Start ups could get hit, however.
  - altotrees 9y ago
    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.
    - RcouF1uZ4gsC 9y ago
      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 through "anti-poaching" agreements, that the term "poaching" is long due for retirement in describing situations other than when animals are illegally killed.
      - taneq 9y ago
        > I fail to see why such an action is termed "poaching". Because the company is a king, and the employees are the property of the crown?
      - altotrees 9y ago
        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.
  - dlubarov 9y ago
    Agreed. As a Google engineer, I think a lot of our AI efforts are "safe" (as in we'll keep investing in them for a long time) because they're already providing substantial business value. For example, - TTS and speech synthesis have lots of uses in Android (phones, Wear, Auto, etc.) - Object recognition is very useful for photo search - Face recognition is also useful for photo search (if you tag people in Google Photos) - Neural machine translation provides better translation accuracy (for languages which we have enough training data for) It's possible Google will cut back on some more speculative ML research efforts, but certainly not those four, I would think.
    - joshuamorton 9y ago
      As a fellow google engineer, I'd be curious to know which (public) research you think isn't marketable/valuable. As you've mentioned, object detection (which is a considerable portion of CV) is marketable. Meta learning (Vizier, "Learning to learn with gradient descent with gradient descent") are incredibly valuable from a business perspective. Model compression is important for neural networks on mobile/embedded devices, etc. One of the very interesting things about ML being such a corporation driven field is that it's incredible how quickly relatively recent research makes its way into products.
      - zjaffee 9y ago
        > One of the very interesting things about ML being such a corporation driven field is that it's incredible how quickly relatively recent research makes its way into products. I think this is just true for really anything that falls purely within the domain of the computational sciences. For a ground breaking drug to hit the market, it takes 10 years of FDA trials, for high speed trains it requires large teams of construction workers only after years of safety work. In the world of software as it stands today, deploying a new model for something can be virtually instant in some cases, and even in the worst cases, it isn't taking people years to improve a small attribute of their product.
    - peoplewindow 9y ago
      I doubt Google will cut back any time soon, but as a former Google engineer, I find this an entertaining definition of business value ;) How much money does Google Photos make? Last time I used it, there were no ads in it. Isn't speech recognition nearly at human levels of comprehension, at least for US English and outside of highly technical jargon? Speech patterns change slowly, so would Android continue to make money if investment in speech R&D were cut back? My guess is yes, it'd be fine. Does Google Translate make money in some specific, measurable way? I don't mean "well it's neat to have translation links in web search", I mean, would people cut back on the commercial queries that are Google's main source of income if Translate quality stopped improving? I doubt it. Much of their products are like this. They're products but they aren't businesses. It's very easy to lose sight of the basics of business when inside the Google bubble. The things you mention are not providing business value in the conventional sense of the term because they aren't yielding independent profits. So they're all vulnerable. That said, vulnerable to what? I think Google is at risk of losing a lot of trust around web search and political and informational search more generally, but commercial queries are probably pretty much impregnable.
- jacquesm 9y ago
  > Seeing the articles and discussions crop up on a daily basis are making me wonder if we are headed for an AI Winter scenario in this area within the next decade or if this is the real deal and we will see self-driving cars at dealerships within 20 years. It will be either one of those two, if it doesn't happen in the next 20 years I would bet against it happening at all until AGI is a reality, assuming it will ever happen in the first place. But if it is possible with an incremental change to present day technology I fully expect it to happen and likely a lot faster than those 20 years. The economic incentives are too large to ignore and there are many players wealthy enough to finance such an incremental step.
  - ghaff 9y ago
    For a lot of people, true hands-off autonomous driving on limited access divided highways is by itself a huge convenience feature and, potentially, a huge safety feature. And this seems like relatively low hanging fruit. People will pay for this. (And are, in a limited way, on more and more cars today.) It's not sexy and doesn't fulfill autonomous taxis everywhere fantasies but for the vast majority of people who don't live in or near urban cores it would likely be a significant quality of life improvement.
Animats 9y ago
Now this is doing it right. That's how car companies do it. Big test tracks, and years of test track time, plus simulation and test rigs. As the article points out, Google has far more autonomous driving miles than everybody else put together. They're on the hard cases, too; not just driving on freeways.
- hueving 9y ago
  Do they have anything that works in rain/snow?
  - deleted 9y ago
    [deleted]
  - cbhl 9y ago
    Snow is challenging because the lane markers are obscured by the snow -- human drivers guess at where the lanes should be, or remember where the lanes were yesterday. Tesla being able to record sensor/map data from human drivers driving through snow will help them mitigate this. On the other hand, electric batteries have less range in cold whether, so I imagine that in the near term electric cars will be less popular in snowy markets versus, say, California.
    - turkeywelder 9y ago
      While I take the point cold weather affects range. Norway, Sweden, Finland and many other cold climates have very high electric car usage. Mostly due to the subsidies, but it appears range isn't a major concern there. https://cleantechnica.com/2017/06/23/tesla-electric-cars-conquered-norway/ https://cleantechnica.com/2017/06/23/tesla-electric-cars-con...
- peoplewindow 9y ago
  Well, do they have hard cases? I was surprised to read in the article that they were flummoxed by roundabouts, of all things. And that they were apparently surprised to discover that multi-lane roundabouts even exist at all. Have none of these engineers ever gone on holiday to Europe? If they think a multi-lane roundabout is an advanced case, what will they make of this? https://www.wired.com/2016/08/brilliant-sorcery-englands-7-circle-magic-roundabout/ https://www.wired.com/2016/08/brilliant-sorcery-englands-7-c...
senatorobama 9y ago
Can they simulate a hurricane?
- jacquesm 9y ago
  They don't have to simulate one, merely reliably detect one and then refuse to drive. One of the most important lessons drilled into new drivers is that the best way to avoid accidents is to know when not to drive, self driving cars should not be an exception to that rule. If you are going to attempt to drive in hurricane you are essentially committing suicide, your best cause of action is to find a safe place to weather the storm. And if you really want to drive a self driving car might give you the option to override the safeties but those should only be used in actual emergencies, not just to putter around in really bad and possibly dangerous weather. The same goes for dense fog, flooding and other situations where normal driving is no longer possible and/or responsible.
  - jvolkman 9y ago
    And Waymo has already said that its cars will safely pull over when the weather gets too rough.
    - jpindar 9y ago
      So during each winter storm, the roads will be lined with cars full of people freezing to death (literally) because their cars decided they can't drive home. And people trying to walk (in the roadway) to shelter, which isn't much safer.
      - bluGill 9y ago
        Most cars can stay warm for several days just running the engine at idle. Assuming you get enough fresh air (not always a given in a snow storm that can block air vents) stopping and just running the engine for heat is safe unless your fuel tank is low - which it shouldn't be.
jacquesm 9y ago
Interesting stuff. I wonder to what extent Google and Tesla could benefit from sharing each others datasets, Tesla has far more real world data than Google at this point in time but Google has the better virtual environment to test in.
- kyrra 9y ago
  Not all data is equal. Waymo test vehicled likely record a bunch of data from all the sensors and can download them all at the end of the data. Tesla just enabled in the last few months the option for people to upload data to them. Determining which data to upload is its own problem as well.
  - mandeepj 9y ago
    > Tesla just enabled in the last few months the option for people to upload data to them. Did you mean Tesla never captured data before that? If yes then I disagree. Sorry. More here - https://electrek.co/2017/07/12/tesla-global-fleet-electric-miles-model-3-launch/ https://electrek.co/2017/07/12/tesla-global-fleet-electric-m...
    - kyrra 9y ago
      What does that article have to do with self driving car sensor data. It talks about miles driven. Tesla just put out there an opt-in upload of video data 3 months ago. And even then it is not clear how useful that data is. Especially since a v2 of the autopilot hardware was recently announced. https://electrek.co/2017/05/06/tesla-data-sharing-policy-collecting-video-self-driving/ https://electrek.co/2017/05/06/tesla-data-sharing-policy-col...
  - jacquesm 9y ago
    https://qz.com/694520/tesla-has-780-million-miles-of-driving-data-and-adds-another-million-every-10-hours/ https://qz.com/694520/tesla-has-780-million-miles-of-driving... Tesla has an enormous amount of data at their disposal. The recent change concerned video footage from the onboard cameras.
deleted 9y ago
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monkpit 9y ago
> for an average of once every 890 miles, or 0.80 disengagements per 1,000 miles. Isn’t that 1.12~ per 1000mi?
- 0xB31B1B 9y ago
  Wow, and I must think we're looking to squeeze ~3 more orders of magnitude or more of the reliability before going full driverless ~(1m miles/disengagement)
  - notatoad 9y ago
    is there a specific reason you think that, or is a million just a sufficiently impressive-sounding number?
    - nopinsight 9y ago
      Motor vehicles are interestingly less fatal than our intuition suggests: "only" 11.3 deaths per billion vehicle-miles. [1] To my surprise, railroad travel is more fatal at 29.0 deaths per billion miles traveled. [2] [1] https://en.wikipedia.org/wiki/Transportation_safety_in_the_United_States#Traffic_safety_by_mode_by_traveled_distance https://en.wikipedia.org/wiki/Transportation_safety_in_the_U... [2] http://www.caranddriver.com/features/safety-in-numbers-charting-traffic-safety-and-fatality-data http://www.caranddriver.com/features/safety-in-numbers-chart...
      - Judgmentality 9y ago
        Does that mean trains are more dangerous than cars? It seems that way, I just wonder if I'm missing something.
        waqf 9y ago
        Looking at the BTS statistics: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_02_01.html_mfd https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/pu... you can see that 95% of railroad fatalities are classified as either "Trespassers" or "Highway–rail grade crossing". In both of those cases it seems likely that the victims are generally not actually passengers on the train, but rather are people doing something obviously dangerous near railroad tracks. (Also the denominator wasn't clear for the quoted statistic: is it per passenger-mile, or per vehicle-mile? In any case here is a sensible denominator: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_01_40.html. https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/pu...)
nopinsight 9y ago
The fact that Waymo revealed their "secret" tools for advancing this crucial technology implies that either: 1) They believe no one can quite catch up before they can launch the technology. Since they know several competitors have huge resources and brilliant people, it means they are quite close to launch. 2) These tools have become open secret within the industry, so no harm is done to their competitive position by revealing it to the public, only good PR to be gained perhaps to attract more bright engineers. I suspect 2) is more likely since several key players have moved around so much in the past couple of years. Relatively high-level knowledge about how autonomous vehicles are being developed at Waymo might have become well-known within the industry by now.
- paulcole 9y ago
  3) this is a pr puff piece that shares no real secrets
  - Judgmentality 9y ago
    Did you read his comment? That's 2)
- jpace121 9y ago
  The strategy of combining simulation with real world data isn't particularly original, nor is the idea of using test tracks. The challenging part is how you do it. This article barely touched on that.
- nharada 9y ago
  No doubt it's number 2, I've seen quite a few articles about other self driving efforts and the general sentiment I've seen on HN is "Cruise looks like they're far ahead" and "What about Waymo? Did they fall behind?" This seems like Waymo PR is showing off some secrets to re-assert their technical strength.
- baq 9y ago
  I'd also say it's 2 and the piece is about bringing the cool factor up so recruiting is easier.
Judgmentality 9y ago
That's pretty fucking cool.
deleted 9y ago
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pgodzin 9y ago
Really well-written and engaging article. It seems the main point of an article like this from Google's perspective is gaining the public's trust. I'm sure most people are worried about the edge-cases that are so hard to run into in the real world, but are so important to get right. This is Google saying "we may not see that edge-case exactly, but we know when it could happen and simulate the situation a million times to make sure we get it right if we ever see it again."
- stevenwoo 9y ago
  I occassionally come across construction that is marked in an unusual way - at 65 miles an hour when the speed limit is 75. Also, when they are changing freeways and restriping them (leaving the original old faded lanes and before new lines go up) sometimes it's confusing to me and the traffic is flowing at 80 miles an hour, IIRC this was happening on 880 for a while about 10 years back. If the AI is confused by a roundabout as described I wonder how they handle that or if this is something that only fools me because I am only using visual sensors.
  - pgodzin 9y ago
    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?
    - stevenwoo 9y ago
      I don't know what a good answer is, my recollection of those examples is no one else is slowing down so I need to go the same speed in order to not be rear ended and hope the car in front of me knows what they are doing. This feels pretty unsatisfactory. The speed limit is kind of interesting, occassionally see someone go the speed limit on I-5 but it's hard to maintain because there's always an eighteen wheeler going slower than that, and then it hits a hill, and then there's a cascade reaction where the slow lane hits 45-50 for an extended period but the fast lane is going 75-95, though just being patient and waiting in the slow lane isn't a big deal for a autodriving car, or 280 between San Francisco and San Jose with sections where it appears almost everyone is going 85 miles per hour (not sure why CHP doesn't just camp out there). I see Teslas in both these places but I've never seen a Waymo.
skoocda 9y ago
Recently got turned down for a job here, now I'm remarkably glad I did - this is an incredibly difficult problem to tackle, and they need absolutely brilliant people to achieve success. I wish them the best of luck in their continued progress! I'll stick to easier stuff :)
foota 9y ago
I found this to be especially interesting "She spent countless hours going up and down 101 and 280, the highways that lead between San Francisco and Mountain View. Like the rest of the drivers, she came to develop a feel for how the cars performed on the open road. And this came to be seen as an important kind of knowledge within the self-driving program. They developed an intuition about what might be hard for the cars. “Doing some testing on newer software and having a bit of tenure on the team, I began to think about ways that we could potentially challenge the system,” she tells me."
stirlo 9y ago
Looks like this is the location of the test facility they talk about... https://www.google.com.au/maps/@37.3705986,-120.5747932,237m/data=!3m1!1e3 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 https://maps.apple.com/?q=37.3718,-120.5749&t=k
- ipsum2 9y ago
  Curious - does anyone know why the Apple maps redirect to Google maps? I'm on Chrome.
  - slazaro 9y ago
    https://techcrunch.com/2012/09/22/mapsception/ https://techcrunch.com/2012/09/22/mapsception/ Apparently it's been doing this for years, and in different platforms.
  - apk17 9y ago
    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…)
- youngtaff 9y ago
  StreetView shows one of the cars at work - https://www.google.com.au/maps/@37.3693527,-120.5767177,3a,60y,57.85h,91.1t/data=!3m6!1e1!3m4!1sWOak0ZDYstb77S80tPmIgA!2e0!7i13312!8i6656 https://www.google.com.au/maps/@37.3693527,-120.5767177,3a,6...
Animats 9y ago
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 obstacle? That comes from processing multiple frames and range rate data from radars. Moving objects have to be tracked. Only then does object recognition come into play. Moving objects should be classified if possible, and fixed objects of special interest (signs, barricades, etc.) identified. Not all objects will be identified, but that's OK. If it can't be identified and it's moving, you have to assume the worst case - it's vulnerable and it doesn't follow the road rules. This will force a slowdown and careful maneuvering around the unknown object. (See Chris Urmson's SXSW video of their vehicle encountering someone in a powered wheelchair chasing a duck with a broom.) Predicting the behavior of moving objects is a big part of handling heavy traffic. That's what Google is working hard on now. Machine learning is a part of this, but not the whole thing. You can't really trust machine learning; it's a statistical method and sometimes it will be totally wrong. You can trust geometry. If you want to do it wrong, you start out with lane keeping and smart cruise control, tack on recognition of common objects, throw in some machine learning and hope for the best. This produced the Tesla self-crashing car, noted for running into unusual obstacles which partially block the lane and for trusting lane markings way too much. Look closely at the videos from Tesla and Cruise, slowing them down to real time. They speed them up so you can't easily see how bad the object recognition is.
- kozhevnikov 9y ago
  Chris Urmson's SXSW video: https://youtu.be/Uj-rK8V-rik https://youtu.be/Uj-rK8V-rik
  - spyspy 9y ago
    Timestamp for duck part https://youtu.be/Uj-rK8V-rik?t=26m11s https://youtu.be/Uj-rK8V-rik?t=26m11s
- agumonkey 9y ago
bit_logic 9y ago
Self driving cars is based on machine learning which is basically processing massive amounts of past data. This is great for routine situations and it seems Waymo is making good progress covering most of these. However the key weakness is the lack of true intelligence. When anything unusual or unexpected happens, the best it can do is simply safely shutdown and wait for a human to intervene. And the car can't really analyze and understand its environment because that requires intelligence. It seems a best of both worlds solution would be a new type of job: Data gathering driver. It would be basically like the Google Streetview cars, but with much more sensors and input from the driver. These drivers would be assigned neighborhoods to drive through and note anything unusual or noteworthy. Stop sign is down because of last night's storm? Driver notes this and now all Waymo cars know. Street closed due to construction? All Waymo cars will avoid that street. This type of data requires intelligence to analyze and understand and it would be fed into the Waymo system for all self driving cars to benefit from it. There could be millions of self driving cars and a few thousands of these drivers feeding daily updated data to the system. You could even increase the frequency of the drivers depending on weather conditions. Maybe if there's a storm, the drivers keep driving in a loop hourly instead of once daily.
- iUsedToCode 9y ago
  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 of work ahead of them, but don't be so pessimistic. Most people drive shitty (myself included), we aren't impossible to improve upon.
  - notahacker 9y ago
    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 occur). So if you want Level 5 driving, and not just a very impressive demo which is safe provided a human watches it attentively enough to take emergency measures and is able to override it when it decides it can't process a situation well enough to proceed, you need the AI to be pretty damn close to perfect in its judgement of how to react to a huge number of edge cases.
flamedoge 9y ago
> 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 finder on top of a car, with an automaker like Chevy that might see $40,000 as its price ceiling for mass-market adoption. > “GM, Ford, Toyota, and others are saying ‘Let me reduce the number of crashes and fatalities and increase safety for the mass market.’ Their target is totally different,” Peng said. “We need to think about the millions of vehicles, not just a few thousand.” I wonder if an easier task to reduce fatalities is to target impaired driving and develop a detection mechanism that tries to identify whether the driver is impaired. It seems like an easier and more localized problem than building a fully autonomous vehicle.
- jooke 9y ago
  Who's going to buy a car that might tell them they can't drive?
  - dsfyu404ed 9y ago
    rich parents will buy them as high-school graduation presents. It's a very, very tiny market.
  - lightbyte 9y ago
    People that get convicted of DUIs and want to keep their license. We already have modifications to cars that require people to blow into to start their car, this seems like the logical next step in that.
  - grkvlt 9y ago
    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?
  - flamedoge 9y ago
jpelecanos 9y ago
Recently, Waymo and Lyft launched a self-driving vehicle partnership [0]. With Trump nomination of Derek Kan (Lyft General Manager in Southern California) to serve as Under Secretary of Transportation for Policy [1], would it ease Waymo path towards autonomous car supremacy? [0] https://www.reuters.com/article/us-lyft-waymo-collaboration-idUSKCN18B02L https://www.reuters.com/article/us-lyft-waymo-collaboration-... [1] https://www.whitehouse.gov/the-press-office/2017/04/06/president-donald-j-trump-announces-intent-nominate-derek-kan-department https://www.whitehouse.gov/the-press-office/2017/04/06/presi...
philjohn 9y ago
Unless I didn't understand correctly, on the animated image of the car turning, which included a wireframe representation of the scene, as well as the cameras: https://cdn.theatlantic.com/assets/media/img/posts/2017/08/WaymoMovieGIF/a7325709f.gif https://cdn.theatlantic.com/assets/media/img/posts/2017/08/W... The generated geometry doesn't seem to include the Bike that quickly passes behind the car at the intersection ...
- underwater 9y ago
  The video is a real event where the car behaved suboptimally. It stopped because it couldn't understand what it should do about the bike. The wireframe is an artificial simulation that is inspired by the same scenario.
- londons_explore 9y ago
  The bike is shown as a red wireframe.
- euyyn 9y ago
  The bike is the red box that crosses the intersection. It doesn't pass behind the car, but by its side. The white wireframe box that "detaches" from the Waymo car is where the cameras are (so what the car actually did). I assume the Waymo car that doesn't stop in the animation is what it should have done instead.
  - jvolkman 9y ago
    More specifically, the article indicates that the car that doesn't stop is what the software - after changes to fix the original problem - would do now if it encountered the same situation.
joering2 9y ago
Great to see such progress made by Waymo and Co. But as the Murphy's law says, if something might break, it will eventually break. With possibly millions of self driving cars and trillions of unique situations, its inevitable that someone will get hurt. So my question is: what kind of progress is being made to draft a legal framework for situation in which I rode my bike in bike lane and for whatever reason self-driving vehicle struck me. Who do I go after in regards to my pilling up medical expenses? Do I sue driver? The car company? The company who delivered self-driving hardware? The software manufacturer? I get that self-driving cars comes with incredible advantages: less crashes (hopefully), no drink drivers, etc. But a legal framework for such automobiles should be in works as we speak. Edited: of course Murphy's law; thanks for pointing it out!
- danielbln 9y ago
  I think you meant Murphy's law. Moore's law is the one about transistor density doubling every x years.
- whipoodle 9y ago
  To me it just has to be better than human drivers, who are actually pretty awful. I think it's unfortunate that we all seem focused on having self-driving cars be basically perfect. If they were only twice as good as human drivers we should jump at the chance to reduce fatalities.
- Zigurd 9y ago
  Globally, the death toll on roads is about 1 million per year. If autonomous vehicles make a significant cut in that number, people will start to see human drivers as the more-difficult liability issue.
- organsnyder 9y ago
  In your hypothetical situation, you'd probably deal with the owner's insurance company, just like with a human driver. The insurer will have already priced the policy lower based on underwriters' analysis that AI is safer than human drivers. In the case where the AI made an egregious error, I'm sure the insurer would be interested in pursuing legal action. In my medium-sized metro area, I can recall at least a half-dozen deaths of cyclists this year caused by humans making similar errors. It doesn't take much for software to be better than that.
diasp 9y ago
Machine Learning for Self-Driving Cars. High-level Development Process for Autonomous Vehicles. https://www.slideshare.net/jwiegelmann/machine-learning-for-selfdriving-cars https://www.slideshare.net/jwiegelmann/machine-learning-for-...
senatorobama 9y ago
Waymo should just get training data in India.
- pault 9y ago
  I'm having a nightmarish vision of a fleet of self driving cars trained to ceaselessly honk and drive on the sidewalks.
- deleted 9y ago
  [deleted]
skywhopper 9y ago
I'm disappointed the article wasn't a bit more skeptical of some of the claims. Certainly the simulation-based testing is a good thing, but stats about how many billions of simulated miles have been driven can create a self-reinforcing delusion if everyone involved isn't careful to remember that the simulations can only work with well-known and expected situations. It sounds like Waymo realizes this and is building a huge library of scenarios to evaluate, but one million simulated miles are not worth a hundred real miles in terms of confidence in the system, and that is not the message this article portrays. Overall this article does give hints though that autonomous vehicles are truly much further away than anyone wants to admit. The story about being flummoxed by multilane roundabouts is depressing. If they didn't know such things existed then they were incredibly sloppy in their data gathering. If they truly thought scaling from a simple roundabout to a multilane one would be trivial then their staff don't have the right mindset for this problem space. Also note that all the testing is happening in flat, desert landscapes where there are no weather or lighting challenges. Their pictured model residential street only has stubs of driveways. No houses, no trees. I'm sure they know these are gaps but I worry they underestimate the challenges of adapting to entirely different driving environments. Especially when machine learning is involved and you're simulating 99% of your mileage... Looking forward to checking back in 2040 though.
- ghshephard 9y ago
  "One million simulated miles are not worth a hundred real miles in terms of confidence in the system" I'm wondering why you say that? Wouldn't the more relevant factor be the type of miles, regardless of whether they are simulated or real? For example, 1 mile of simulated "Interesting Scenarios" (Duck on Street, Bicyclist going wrong way, pedestrian running onto road) is likely worth 100,000 miles of normal Freeway driving.
- bluGill 9y ago
  One millions miles of different situations is worth more than 100 miles anywhere. Even your most carefully chosen worst case route won't cover all situations. To get close you have to pay people to send their kid running between parked cars into the street at just the right moment. Nobody sane will put a real kids into that situation, but the simulation can (should!) have thousands of different variations. The simulation can afford to run all of those situations regularly. Simulation can ensure it is raining when you need it. You need miles of real driving too, but they are too expensive and unpredictable to rely on for more than a final check.
deleted 9y ago
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310 points by jpm_sd 9y ago

Clearly the progress being made in the area of self-driving cars is undeniable. Seeing the articles and discussions crop up on a daily basis are making me wonder if we are headed for an AI Winter scenario in this area within the next decade or if this is the real deal and we will see self-driving cars at dealerships within 20 years. This is so far from being my area of expertise. Just one observer's thoughts/questions. Insane how far we have come so quickly, at any rate.

arcanus 9y ago
I don't disagree that AI is over-hyped. However, I think the research environment is not as likely to dry up this time. That is because much of the machine learning research is coming from industry, particularly the mega-corps. And for extremely important disruptive events such as AI, they are willing to drop $$ into collecting a stable of research scientists to not fall behind in this space. So while the AI winter was driven by a drop in academic and government spending on research, I think our present situation is far less likely to result in a similar drying up. Start ups could get hit, however.
- altotrees 9y ago
  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.
  - RcouF1uZ4gsC 9y ago
    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 through "anti-poaching" agreements, that the term "poaching" is long due for retirement in describing situations other than when animals are illegally killed.
    - taneq 9y ago
      > I fail to see why such an action is termed "poaching". Because the company is a king, and the employees are the property of the crown?
    - altotrees 9y ago
      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.
- dlubarov 9y ago
  Agreed. As a Google engineer, I think a lot of our AI efforts are "safe" (as in we'll keep investing in them for a long time) because they're already providing substantial business value. For example, - TTS and speech synthesis have lots of uses in Android (phones, Wear, Auto, etc.) - Object recognition is very useful for photo search - Face recognition is also useful for photo search (if you tag people in Google Photos) - Neural machine translation provides better translation accuracy (for languages which we have enough training data for) It's possible Google will cut back on some more speculative ML research efforts, but certainly not those four, I would think.
  - joshuamorton 9y ago
    As a fellow google engineer, I'd be curious to know which (public) research you think isn't marketable/valuable. As you've mentioned, object detection (which is a considerable portion of CV) is marketable. Meta learning (Vizier, "Learning to learn with gradient descent with gradient descent") are incredibly valuable from a business perspective. Model compression is important for neural networks on mobile/embedded devices, etc. One of the very interesting things about ML being such a corporation driven field is that it's incredible how quickly relatively recent research makes its way into products.
    - zjaffee 9y ago
      > One of the very interesting things about ML being such a corporation driven field is that it's incredible how quickly relatively recent research makes its way into products. I think this is just true for really anything that falls purely within the domain of the computational sciences. For a ground breaking drug to hit the market, it takes 10 years of FDA trials, for high speed trains it requires large teams of construction workers only after years of safety work. In the world of software as it stands today, deploying a new model for something can be virtually instant in some cases, and even in the worst cases, it isn't taking people years to improve a small attribute of their product.
  - peoplewindow 9y ago
    I doubt Google will cut back any time soon, but as a former Google engineer, I find this an entertaining definition of business value ;) How much money does Google Photos make? Last time I used it, there were no ads in it. Isn't speech recognition nearly at human levels of comprehension, at least for US English and outside of highly technical jargon? Speech patterns change slowly, so would Android continue to make money if investment in speech R&D were cut back? My guess is yes, it'd be fine. Does Google Translate make money in some specific, measurable way? I don't mean "well it's neat to have translation links in web search", I mean, would people cut back on the commercial queries that are Google's main source of income if Translate quality stopped improving? I doubt it. Much of their products are like this. They're products but they aren't businesses. It's very easy to lose sight of the basics of business when inside the Google bubble. The things you mention are not providing business value in the conventional sense of the term because they aren't yielding independent profits. So they're all vulnerable. That said, vulnerable to what? I think Google is at risk of losing a lot of trust around web search and political and informational search more generally, but commercial queries are probably pretty much impregnable.
jacquesm 9y ago
> Seeing the articles and discussions crop up on a daily basis are making me wonder if we are headed for an AI Winter scenario in this area within the next decade or if this is the real deal and we will see self-driving cars at dealerships within 20 years. It will be either one of those two, if it doesn't happen in the next 20 years I would bet against it happening at all until AGI is a reality, assuming it will ever happen in the first place. But if it is possible with an incremental change to present day technology I fully expect it to happen and likely a lot faster than those 20 years. The economic incentives are too large to ignore and there are many players wealthy enough to finance such an incremental step.
- ghaff 9y ago
  For a lot of people, true hands-off autonomous driving on limited access divided highways is by itself a huge convenience feature and, potentially, a huge safety feature. And this seems like relatively low hanging fruit. People will pay for this. (And are, in a limited way, on more and more cars today.) It's not sexy and doesn't fulfill autonomous taxis everywhere fantasies but for the vast majority of people who don't live in or near urban cores it would likely be a significant quality of life improvement.

Animats 9y ago

Now this is doing it right. That's how car companies do it. Big test tracks, and years of test track time, plus simulation and test rigs. As the article points out, Google has far more autonomous driving miles than everybody else put together. They're on the hard cases, too; not just driving on freeways.

hueving 9y ago
Do they have anything that works in rain/snow?
- deleted 9y ago
  [deleted]
- cbhl 9y ago
  Snow is challenging because the lane markers are obscured by the snow -- human drivers guess at where the lanes should be, or remember where the lanes were yesterday. Tesla being able to record sensor/map data from human drivers driving through snow will help them mitigate this. On the other hand, electric batteries have less range in cold whether, so I imagine that in the near term electric cars will be less popular in snowy markets versus, say, California.
  - turkeywelder 9y ago
    While I take the point cold weather affects range. Norway, Sweden, Finland and many other cold climates have very high electric car usage. Mostly due to the subsidies, but it appears range isn't a major concern there. https://cleantechnica.com/2017/06/23/tesla-electric-cars-conquered-norway/ https://cleantechnica.com/2017/06/23/tesla-electric-cars-con...
peoplewindow 9y ago
Well, do they have hard cases? I was surprised to read in the article that they were flummoxed by roundabouts, of all things. And that they were apparently surprised to discover that multi-lane roundabouts even exist at all. Have none of these engineers ever gone on holiday to Europe? If they think a multi-lane roundabout is an advanced case, what will they make of this? https://www.wired.com/2016/08/brilliant-sorcery-englands-7-circle-magic-roundabout/ https://www.wired.com/2016/08/brilliant-sorcery-englands-7-c...

senatorobama 9y ago

Can they simulate a hurricane?

jacquesm 9y ago
They don't have to simulate one, merely reliably detect one and then refuse to drive. One of the most important lessons drilled into new drivers is that the best way to avoid accidents is to know when not to drive, self driving cars should not be an exception to that rule. If you are going to attempt to drive in hurricane you are essentially committing suicide, your best cause of action is to find a safe place to weather the storm. And if you really want to drive a self driving car might give you the option to override the safeties but those should only be used in actual emergencies, not just to putter around in really bad and possibly dangerous weather. The same goes for dense fog, flooding and other situations where normal driving is no longer possible and/or responsible.
- jvolkman 9y ago
  And Waymo has already said that its cars will safely pull over when the weather gets too rough.
  - jpindar 9y ago
    So during each winter storm, the roads will be lined with cars full of people freezing to death (literally) because their cars decided they can't drive home. And people trying to walk (in the roadway) to shelter, which isn't much safer.
    - bluGill 9y ago
      Most cars can stay warm for several days just running the engine at idle. Assuming you get enough fresh air (not always a given in a snow storm that can block air vents) stopping and just running the engine for heat is safe unless your fuel tank is low - which it shouldn't be.

jacquesm 9y ago

Interesting stuff. I wonder to what extent Google and Tesla could benefit from sharing each others datasets, Tesla has far more real world data than Google at this point in time but Google has the better virtual environment to test in.

kyrra 9y ago
Not all data is equal. Waymo test vehicled likely record a bunch of data from all the sensors and can download them all at the end of the data. Tesla just enabled in the last few months the option for people to upload data to them. Determining which data to upload is its own problem as well.
- mandeepj 9y ago
  > Tesla just enabled in the last few months the option for people to upload data to them. Did you mean Tesla never captured data before that? If yes then I disagree. Sorry. More here - https://electrek.co/2017/07/12/tesla-global-fleet-electric-miles-model-3-launch/ https://electrek.co/2017/07/12/tesla-global-fleet-electric-m...
  - kyrra 9y ago
    What does that article have to do with self driving car sensor data. It talks about miles driven. Tesla just put out there an opt-in upload of video data 3 months ago. And even then it is not clear how useful that data is. Especially since a v2 of the autopilot hardware was recently announced. https://electrek.co/2017/05/06/tesla-data-sharing-policy-collecting-video-self-driving/ https://electrek.co/2017/05/06/tesla-data-sharing-policy-col...
- jacquesm 9y ago
  https://qz.com/694520/tesla-has-780-million-miles-of-driving-data-and-adds-another-million-every-10-hours/ https://qz.com/694520/tesla-has-780-million-miles-of-driving... Tesla has an enormous amount of data at their disposal. The recent change concerned video footage from the onboard cameras.

deleted 9y ago

[deleted]

monkpit 9y ago

> for an average of once every 890 miles, or 0.80 disengagements per 1,000 miles. Isn’t that 1.12~ per 1000mi?

0xB31B1B 9y ago
Wow, and I must think we're looking to squeeze ~3 more orders of magnitude or more of the reliability before going full driverless ~(1m miles/disengagement)
- notatoad 9y ago
  is there a specific reason you think that, or is a million just a sufficiently impressive-sounding number?
  - nopinsight 9y ago
    Motor vehicles are interestingly less fatal than our intuition suggests: "only" 11.3 deaths per billion vehicle-miles. [1] To my surprise, railroad travel is more fatal at 29.0 deaths per billion miles traveled. [2] [1] https://en.wikipedia.org/wiki/Transportation_safety_in_the_United_States#Traffic_safety_by_mode_by_traveled_distance https://en.wikipedia.org/wiki/Transportation_safety_in_the_U... [2] http://www.caranddriver.com/features/safety-in-numbers-charting-traffic-safety-and-fatality-data http://www.caranddriver.com/features/safety-in-numbers-chart...
    - Judgmentality 9y ago
      Does that mean trains are more dangerous than cars? It seems that way, I just wonder if I'm missing something.
      - waqf 9y ago
        Looking at the BTS statistics: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_02_01.html_mfd https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/pu... you can see that 95% of railroad fatalities are classified as either "Trespassers" or "Highway–rail grade crossing". In both of those cases it seems likely that the victims are generally not actually passengers on the train, but rather are people doing something obviously dangerous near railroad tracks. (Also the denominator wasn't clear for the quoted statistic: is it per passenger-mile, or per vehicle-mile? In any case here is a sensible denominator: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_01_40.html. https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/pu...)

nopinsight 9y ago

The fact that Waymo revealed their "secret" tools for advancing this crucial technology implies that either: 1) They believe no one can quite catch up before they can launch the technology. Since they know several competitors have huge resources and brilliant people, it means they are quite close to launch. 2) These tools have become open secret within the industry, so no harm is done to their competitive position by revealing it to the public, only good PR to be gained perhaps to attract more bright engineers. I suspect 2) is more likely since several key players have moved around so much in the past couple of years. Relatively high-level knowledge about how autonomous vehicles are being developed at Waymo might have become well-known within the industry by now.

paulcole 9y ago
3) this is a pr puff piece that shares no real secrets
- Judgmentality 9y ago
  Did you read his comment? That's 2)
jpace121 9y ago
The strategy of combining simulation with real world data isn't particularly original, nor is the idea of using test tracks. The challenging part is how you do it. This article barely touched on that.
nharada 9y ago
No doubt it's number 2, I've seen quite a few articles about other self driving efforts and the general sentiment I've seen on HN is "Cruise looks like they're far ahead" and "What about Waymo? Did they fall behind?" This seems like Waymo PR is showing off some secrets to re-assert their technical strength.
baq 9y ago
I'd also say it's 2 and the piece is about bringing the cool factor up so recruiting is easier.

Judgmentality 9y ago

That's pretty fucking cool.

deleted 9y ago

[deleted]

pgodzin 9y ago

Really well-written and engaging article. It seems the main point of an article like this from Google's perspective is gaining the public's trust. I'm sure most people are worried about the edge-cases that are so hard to run into in the real world, but are so important to get right. This is Google saying "we may not see that edge-case exactly, but we know when it could happen and simulate the situation a million times to make sure we get it right if we ever see it again."

stevenwoo 9y ago
I occassionally come across construction that is marked in an unusual way - at 65 miles an hour when the speed limit is 75. Also, when they are changing freeways and restriping them (leaving the original old faded lanes and before new lines go up) sometimes it's confusing to me and the traffic is flowing at 80 miles an hour, IIRC this was happening on 880 for a while about 10 years back. If the AI is confused by a roundabout as described I wonder how they handle that or if this is something that only fools me because I am only using visual sensors.
- pgodzin 9y ago
  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?
  - stevenwoo 9y ago
    I don't know what a good answer is, my recollection of those examples is no one else is slowing down so I need to go the same speed in order to not be rear ended and hope the car in front of me knows what they are doing. This feels pretty unsatisfactory. The speed limit is kind of interesting, occassionally see someone go the speed limit on I-5 but it's hard to maintain because there's always an eighteen wheeler going slower than that, and then it hits a hill, and then there's a cascade reaction where the slow lane hits 45-50 for an extended period but the fast lane is going 75-95, though just being patient and waiting in the slow lane isn't a big deal for a autodriving car, or 280 between San Francisco and San Jose with sections where it appears almost everyone is going 85 miles per hour (not sure why CHP doesn't just camp out there). I see Teslas in both these places but I've never seen a Waymo.

skoocda 9y ago

Recently got turned down for a job here, now I'm remarkably glad I did - this is an incredibly difficult problem to tackle, and they need absolutely brilliant people to achieve success. I wish them the best of luck in their continued progress! I'll stick to easier stuff :)

foota 9y ago

I found this to be especially interesting "She spent countless hours going up and down 101 and 280, the highways that lead between San Francisco and Mountain View. Like the rest of the drivers, she came to develop a feel for how the cars performed on the open road. And this came to be seen as an important kind of knowledge within the self-driving program. They developed an intuition about what might be hard for the cars. “Doing some testing on newer software and having a bit of tenure on the team, I began to think about ways that we could potentially challenge the system,” she tells me."

stirlo 9y ago

Looks like this is the location of the test facility they talk about... https://www.google.com.au/maps/@37.3705986,-120.5747932,237m/data=!3m1!1e3 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 https://maps.apple.com/?q=37.3718,-120.5749&t=k

ipsum2 9y ago
Curious - does anyone know why the Apple maps redirect to Google maps? I'm on Chrome.
- slazaro 9y ago
  https://techcrunch.com/2012/09/22/mapsception/ https://techcrunch.com/2012/09/22/mapsception/ Apparently it's been doing this for years, and in different platforms.
- apk17 9y ago
  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…)
youngtaff 9y ago
StreetView shows one of the cars at work - https://www.google.com.au/maps/@37.3693527,-120.5767177,3a,60y,57.85h,91.1t/data=!3m6!1e1!3m4!1sWOak0ZDYstb77S80tPmIgA!2e0!7i13312!8i6656 https://www.google.com.au/maps/@37.3693527,-120.5767177,3a,6...

Animats 9y ago

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 obstacle? That comes from processing multiple frames and range rate data from radars. Moving objects have to be tracked. Only then does object recognition come into play. Moving objects should be classified if possible, and fixed objects of special interest (signs, barricades, etc.) identified. Not all objects will be identified, but that's OK. If it can't be identified and it's moving, you have to assume the worst case - it's vulnerable and it doesn't follow the road rules. This will force a slowdown and careful maneuvering around the unknown object. (See Chris Urmson's SXSW video of their vehicle encountering someone in a powered wheelchair chasing a duck with a broom.) Predicting the behavior of moving objects is a big part of handling heavy traffic. That's what Google is working hard on now. Machine learning is a part of this, but not the whole thing. You can't really trust machine learning; it's a statistical method and sometimes it will be totally wrong. You can trust geometry. If you want to do it wrong, you start out with lane keeping and smart cruise control, tack on recognition of common objects, throw in some machine learning and hope for the best. This produced the Tesla self-crashing car, noted for running into unusual obstacles which partially block the lane and for trusting lane markings way too much. Look closely at the videos from Tesla and Cruise, slowing them down to real time. They speed them up so you can't easily see how bad the object recognition is.

kozhevnikov 9y ago
Chris Urmson's SXSW video: https://youtu.be/Uj-rK8V-rik https://youtu.be/Uj-rK8V-rik
- spyspy 9y ago
  Timestamp for duck part https://youtu.be/Uj-rK8V-rik?t=26m11s https://youtu.be/Uj-rK8V-rik?t=26m11s
agumonkey 9y ago

bit_logic 9y ago

Self driving cars is based on machine learning which is basically processing massive amounts of past data. This is great for routine situations and it seems Waymo is making good progress covering most of these. However the key weakness is the lack of true intelligence. When anything unusual or unexpected happens, the best it can do is simply safely shutdown and wait for a human to intervene. And the car can't really analyze and understand its environment because that requires intelligence. It seems a best of both worlds solution would be a new type of job: Data gathering driver. It would be basically like the Google Streetview cars, but with much more sensors and input from the driver. These drivers would be assigned neighborhoods to drive through and note anything unusual or noteworthy. Stop sign is down because of last night's storm? Driver notes this and now all Waymo cars know. Street closed due to construction? All Waymo cars will avoid that street. This type of data requires intelligence to analyze and understand and it would be fed into the Waymo system for all self driving cars to benefit from it. There could be millions of self driving cars and a few thousands of these drivers feeding daily updated data to the system. You could even increase the frequency of the drivers depending on weather conditions. Maybe if there's a storm, the drivers keep driving in a loop hourly instead of once daily.

iUsedToCode 9y ago
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 of work ahead of them, but don't be so pessimistic. Most people drive shitty (myself included), we aren't impossible to improve upon.
- notahacker 9y ago
  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 occur). So if you want Level 5 driving, and not just a very impressive demo which is safe provided a human watches it attentively enough to take emergency measures and is able to override it when it decides it can't process a situation well enough to proceed, you need the AI to be pretty damn close to perfect in its judgement of how to react to a huge number of edge cases.

flamedoge 9y ago

> 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 finder on top of a car, with an automaker like Chevy that might see $40,000 as its price ceiling for mass-market adoption. > “GM, Ford, Toyota, and others are saying ‘Let me reduce the number of crashes and fatalities and increase safety for the mass market.’ Their target is totally different,” Peng said. “We need to think about the millions of vehicles, not just a few thousand.” I wonder if an easier task to reduce fatalities is to target impaired driving and develop a detection mechanism that tries to identify whether the driver is impaired. It seems like an easier and more localized problem than building a fully autonomous vehicle.

jooke 9y ago
Who's going to buy a car that might tell them they can't drive?
- dsfyu404ed 9y ago
  rich parents will buy them as high-school graduation presents. It's a very, very tiny market.
- lightbyte 9y ago
  People that get convicted of DUIs and want to keep their license. We already have modifications to cars that require people to blow into to start their car, this seems like the logical next step in that.
- grkvlt 9y ago
  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?
- flamedoge 9y ago

jpelecanos 9y ago

Recently, Waymo and Lyft launched a self-driving vehicle partnership [0]. With Trump nomination of Derek Kan (Lyft General Manager in Southern California) to serve as Under Secretary of Transportation for Policy [1], would it ease Waymo path towards autonomous car supremacy? [0] https://www.reuters.com/article/us-lyft-waymo-collaboration-idUSKCN18B02L https://www.reuters.com/article/us-lyft-waymo-collaboration-... [1] https://www.whitehouse.gov/the-press-office/2017/04/06/president-donald-j-trump-announces-intent-nominate-derek-kan-department https://www.whitehouse.gov/the-press-office/2017/04/06/presi...

philjohn 9y ago

Unless I didn't understand correctly, on the animated image of the car turning, which included a wireframe representation of the scene, as well as the cameras: https://cdn.theatlantic.com/assets/media/img/posts/2017/08/WaymoMovieGIF/a7325709f.gif https://cdn.theatlantic.com/assets/media/img/posts/2017/08/W... The generated geometry doesn't seem to include the Bike that quickly passes behind the car at the intersection ...

underwater 9y ago
The video is a real event where the car behaved suboptimally. It stopped because it couldn't understand what it should do about the bike. The wireframe is an artificial simulation that is inspired by the same scenario.
londons_explore 9y ago
The bike is shown as a red wireframe.
euyyn 9y ago
The bike is the red box that crosses the intersection. It doesn't pass behind the car, but by its side. The white wireframe box that "detaches" from the Waymo car is where the cameras are (so what the car actually did). I assume the Waymo car that doesn't stop in the animation is what it should have done instead.
- jvolkman 9y ago
  More specifically, the article indicates that the car that doesn't stop is what the software - after changes to fix the original problem - would do now if it encountered the same situation.

joering2 9y ago

Great to see such progress made by Waymo and Co. But as the Murphy's law says, if something might break, it will eventually break. With possibly millions of self driving cars and trillions of unique situations, its inevitable that someone will get hurt. So my question is: what kind of progress is being made to draft a legal framework for situation in which I rode my bike in bike lane and for whatever reason self-driving vehicle struck me. Who do I go after in regards to my pilling up medical expenses? Do I sue driver? The car company? The company who delivered self-driving hardware? The software manufacturer? I get that self-driving cars comes with incredible advantages: less crashes (hopefully), no drink drivers, etc. But a legal framework for such automobiles should be in works as we speak. Edited: of course Murphy's law; thanks for pointing it out!

danielbln 9y ago
I think you meant Murphy's law. Moore's law is the one about transistor density doubling every x years.
whipoodle 9y ago
To me it just has to be better than human drivers, who are actually pretty awful. I think it's unfortunate that we all seem focused on having self-driving cars be basically perfect. If they were only twice as good as human drivers we should jump at the chance to reduce fatalities.
Zigurd 9y ago
Globally, the death toll on roads is about 1 million per year. If autonomous vehicles make a significant cut in that number, people will start to see human drivers as the more-difficult liability issue.
organsnyder 9y ago
In your hypothetical situation, you'd probably deal with the owner's insurance company, just like with a human driver. The insurer will have already priced the policy lower based on underwriters' analysis that AI is safer than human drivers. In the case where the AI made an egregious error, I'm sure the insurer would be interested in pursuing legal action. In my medium-sized metro area, I can recall at least a half-dozen deaths of cyclists this year caused by humans making similar errors. It doesn't take much for software to be better than that.

diasp 9y ago

Machine Learning for Self-Driving Cars. High-level Development Process for Autonomous Vehicles. https://www.slideshare.net/jwiegelmann/machine-learning-for-selfdriving-cars https://www.slideshare.net/jwiegelmann/machine-learning-for-...

senatorobama 9y ago

Waymo should just get training data in India.

pault 9y ago
I'm having a nightmarish vision of a fleet of self driving cars trained to ceaselessly honk and drive on the sidewalks.
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skywhopper 9y ago

I'm disappointed the article wasn't a bit more skeptical of some of the claims. Certainly the simulation-based testing is a good thing, but stats about how many billions of simulated miles have been driven can create a self-reinforcing delusion if everyone involved isn't careful to remember that the simulations can only work with well-known and expected situations. It sounds like Waymo realizes this and is building a huge library of scenarios to evaluate, but one million simulated miles are not worth a hundred real miles in terms of confidence in the system, and that is not the message this article portrays. Overall this article does give hints though that autonomous vehicles are truly much further away than anyone wants to admit. The story about being flummoxed by multilane roundabouts is depressing. If they didn't know such things existed then they were incredibly sloppy in their data gathering. If they truly thought scaling from a simple roundabout to a multilane one would be trivial then their staff don't have the right mindset for this problem space. Also note that all the testing is happening in flat, desert landscapes where there are no weather or lighting challenges. Their pictured model residential street only has stubs of driveways. No houses, no trees. I'm sure they know these are gaps but I worry they underestimate the challenges of adapting to entirely different driving environments. Especially when machine learning is involved and you're simulating 99% of your mileage... Looking forward to checking back in 2040 though.

ghshephard 9y ago
"One million simulated miles are not worth a hundred real miles in terms of confidence in the system" I'm wondering why you say that? Wouldn't the more relevant factor be the type of miles, regardless of whether they are simulated or real? For example, 1 mile of simulated "Interesting Scenarios" (Duck on Street, Bicyclist going wrong way, pedestrian running onto road) is likely worth 100,000 miles of normal Freeway driving.
bluGill 9y ago
One millions miles of different situations is worth more than 100 miles anywhere. Even your most carefully chosen worst case route won't cover all situations. To get close you have to pay people to send their kid running between parked cars into the street at just the right moment. Nobody sane will put a real kids into that situation, but the simulation can (should!) have thousands of different variations. The simulation can afford to run all of those situations regularly. Simulation can ensure it is raining when you need it. You need miles of real driving too, but they are too expensive and unpredictable to rely on for more than a final check.

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