The Information sometimes unlocks articles for HN readers, but for those that don't have access the biggest takeaway to me is that Uber has made relatively little progress towards fully autonomous cars despite a huge amount of investment.
The most shocking detail:
> Uber’s vehicles had also been having what the company refers to as a bad experience—such as a sudden jerk or a potentially dangerous movement—every one-third of a mile on average.
That's really bad. While there are no uniform standards for what a "bad experience" entails, my general sense is that Waymo and Cruise (widely considered first and second) are doing 10-100x better by that metric.
Another damning bit:
> Uber couldn’t even get the prototype to drive a one-mile stretch between the unit’s two Pittsburgh offices, with the goal of shuttling employees back and forth
I don't even know what to say to that. If you can't make your cars work reliably on a known, one-mile stretch of road, what have you been doing for so many years?
[Disclaimer: I work for Lyft, but not on the self-driving car program.]
Autonomous driving to me seems a lot like the domain of robotic crowd navigation, and the crowd navigation research seems to show us that most of the methods suspected in-use by AV programs tend to fall apart under trivial thresholds of uncertainty/congestion. So, I'm less surprised that Uber didn't make much fundamental progress here, and more surprised that anybody else has done better.
edit: I say this as someone who very much wants to see this class of science & technology succeed, but I often wonder if we're 2 or 3 Fields Medals away from really getting fundamentally closer to success.
Indeed amazing because I know employees at Tesla who take it home on autopilot in the freeway! It’s also very unsafe ans I dot believe camera only is the way to go, but at least it can drive for more than a mile.
Freeway driving is much, much easier than in-town roads - there's been successful autonomous freeway driving since the 90s.
When you drive on the freeway, everyone's going the same way (or at least you'd hope), the configuration of the road is well known, lines are consistent, etc. It's all the little things that need to be accounted for - opposing traffic, pedestrians, parked cars, random obstacles, and any number of other road, traffic and obstacle configurations that exist, that make consistently and safely driving elsewhere difficult for autonomous systems.
>Indeed amazing because I know employees at Tesla who take it home on autopilot in the freeway! It’s also very unsafe ans I dot believe camera only is the way to go, but at least it can drive for more than a mile.
Google/Waymo did a pilot - letting employees commute - and canceled because the system was too good and staff stopped paying attention.
This is a clip, there was a longer clip and description in a Waymo CEO speech in the past year or two.
The problem isn't that it's "so good", it's that it's "usually perfect".
Most California weather driving is very mundane and boring. ...but the moment you throw an outside variable into the mix - the computer cannot identify objects, and therefore cannot predict outcomes.
We're still teaching them to recognize Stop signs. How are they supposed to distinguish between a floating plastic bag and a 5 year old child?
At this point I'm starting to be willing to consider it fairly safe when the driver is paying attention. Every press article about an autopilot crash seems to involve somebody who is completely inattentive. I can't recall any published incidents involving a driver using it as an assist, while continuing to pay attention.
I bought an iRobot and I really think if they incorporated a camera it could be significantly better. There are obvious things it picks up and gets stuck in like shoelaces and power cables. Obviously a vacuum is not self driving but it’s a similar problem and at least my casual observation is that proximity sensors along won’t solve real world navigation because we need some kind of inference to understand what the impact of an objects presence would be if we ran over it or not... I believe there has to be a solution with many sensors visual and lidar mapping makes sense too
The iRobot is actually not really a similar problem in scope at all.
I can appreciate why the lay person may believe them to be similar, but it's hard to express just how much more challenging even the most basic form of driver assistance technology is in comparison to an autonomous vacuum.
The biggest challenge is speed. Just look at the napkin math of detection range of sensors versus stopping distance of a car. The higher the speed, the more range you need... and lidar, radar, etc. all have a fixed maximum detection range.
The rule of thumb is 50m for radar/lidar depending on how much you are willing to pay for the sensor. To stop the car safely, will take 56m at 100km/h.
Then ofcourse, the rest of the struggle is all in exception handling (getting from 70% to 99%).
Comparatively, the iRobot can use the dumbest and cheapest sensors and still be fully aware of everything around it in its relatively slow path of travel. It also does not need to predict the paths of travel of everything around it. It's enough for it to slow down or stop, especially at such low speed. If it hits something or fails to recognise an obstacle, it's not really a big deal. In comparison, lives can be lost in the car and there will be enquiries and legal battles.
I would put good money on the camera based automation delivering the best product at the end of the day, but requiring an order of magnitude more research and development than a comparitively "dumb" lidar setup. The lidar setup will have better immediate results, but probably will never reach the 99.999% effectiveness that everyone is chasing, and will probably never be safe at higher speeds.
It is. And it's a nice feature that at least the luxury car makers are iterating on. The problem is that it isn't very interesting for folks who don't want to own a car and/or want a robo-driver to take them door-to-door all the time. A real freeway autopilot feature is still a nice convenience/safety feature but you still need a licensed sober driver for the endpoints of the trip.
much higher stakes and much less response time. There are plenty of city drivers that get confused and, well, pull over or even just stop. it's irritating, but a sensible thing to do.
On a freeway, that's terrifying.
It _seems_ like lots of parallel systems, each with the capability to reduce speed or stop could cope with city traffic about as well as a tourist. but, uh, I guess $2.5B says otherwise.
People manage to drive with eyes only - and with a far more restricted perspective than a ring of cameras around the car.
I do think Musk was (in part) wrong about LIDAR - I imagine that it could provide a valuable source of supplemental data to be used in training and classification.
The relative safety and performance of autonomous anything is very, very hard to measure - there are so many variables.
Even on identical systems, different parameters will create totally different outcomes.
Maybe it has 'sudden movements' because it's actually a lot after and designed to react to things that Waymo would just plow right through. Maybe they're using crappy non-production sensors. Maybe they are entirely relying on instruments and not indirect data like GPS. I have no idea really, other than to say, these are very sophisticated systems and given the obvious opacity of the work ... it's going to be hard to tell what's what.
Absolutely. Great comment, however it's probably worth pointing out that the research and trial sensors are going to be high end, while the finished product will use the cheapest available or commericial sensors.
> That's really bad. While there are no uniform standards for what a "bad experience" entails, my general sense is that Waymo and Cruise (widely considered first and second) are doing 10-100x better by that metric.
For for that matter, ever 3 or 30 miles would also be really bad in my book.
Everyone has made disappointingly little progress on full self-driving in the sense of driving little Johnny from the house to soccer practice by himself.
There are possibly opportunities on freeways but anyone who expects to be able to get robo-Ubers door-to-door for decades is likely to be disappointed.
> Everyone has made disappointingly little progress on full self-driving in the sense of driving little Johnny from the house to soccer practice by himself.
Here's a video of Waymo CTO Dmitri Dolgov claiming that he's perfectly comfortable putting his children in a Waymo car without a driver: https://youtu.be/fZHDvKw0QTA?t=952. Whether he's bluffing or not, we don't know.
It will possibly be safe enough under some well-tested limited circumstances/locations. I'm skeptical that translates into something made generally available.
It blows my mind to see people write things like this. We have two companies, Cruise and Waymo, who have built nothing but toy cars, but they are in the lead while Tesla has years of real-world driving data in cars that are in a manufacturing production operation, receive over the air updates, recognize real world objects, can change lanes automatically, but Waymo is ahead?
I’m open to being convinced that I’m not correct here, but it’s really difficult for me to see how Tesla is anything but 1000x ahead of everybody else.
It reminds me of people who build great models on Jupyter Notebook, but have no clue how about the data engineering that goes into serving those models (90% of the work).
You can't drive a Tesla in "self-driving" mode in non-highway traffic. Solving Adaptive Cruise Control (ACC) and Automated Lane Centering (ALC) on highway traffic are much easier tasks than what Waymo and Cruise are solving. You can buy a device from comma.ai that gives you 90% of Tesla's functionality for a few hundred dollars.
I can’t drive a Waymo or Cruise car at all. So they may as well not exist. But Tesla is supposed to be releasing self-driving on city streets soon. And let’s make sure we are clear here, you don’t need to be on a highway to use Autopilot.
Do you own a Tesla? We previously had a car with ACC/ALC and I don’t find it to be even close to the same thing, but that’s me.
Comma.Ai’s device is great. It’s better than anything anybody else (Waymo/Cruise included) has put out there.
> But Tesla is supposed to be releasing self-driving on city streets soon.
Soon as it was in 2016 [1], 2018 [2] in Feb 2019 [3], Mar 2020 [4], or July 2020 [5]?
They have been hyping this up for years, why should I still believe those claims that it will soon be here™? Not only that but they have already advertised and sold "full self-driving" for people that can't use it yet, no beta, no alpha, just doesn't exist and is a paid feature. How far is this from fraud?
I think this is regulatory. I have seen multiple articles like the attached which have caused Tesla to basically handicap it's own autopilot. As another said I have no idea how a company with a car is not ahead of a company without one.
Tesla didn't support stop signs or traffic lights until a few months ago but Waymo did that years ago. And AFAIK Tesla still can't recognize stopped vehicles on the highway and has no public plan to fix that.
Waymo hasn’t produce a single production car. I doubt their software works on random stop signs in Cleveland. Until I see them on the road, I’m ok watching incremental improvement happen. Being first doesn’t matter.
> And AFAIK Tesla still can't recognize stopped vehicles on the highway and has no public plan to fix that.
Can you elaborate on what you mean by this? I do have a Tesla (without full self-driving) and it comes to a complete stop when cars in front of me stop on the highway.
I guess the question is how you rank a prototype that's actually autonomous against a production car that's far from autonomous. IMO manufacturing cars sounds a lot easier than autonomy. There's also the fact that Waymo's goal is only autonomy within areas that have been mapped in hyper-detail while Tesla apparently wants to drive anywhere. How do you rank more progress towards a smaller goal vs. less progress towards a more ambitious goal?
I don’t give it much rank because it doesn’t matter to me. I’d rather have good, incremental progress toward a larger goal for sure. In my day-to-day I can use a Tesla. I have no use for Waymo so the progress isn’t relevant. Will Waymo map every street in hyper detail, or just Mountain View and New York? If I don’t care about the underlying goal, what reason do I have to care about progress toward that goal?
> “ Just before the crash, a large vehicle — a sport utility vehicle or pickup truck — changed lanes in front of him, the driver told the NTSB.”
If there is a stationary car and I turn on autopilot as I approach my car doesn’t ram into it. If I turn autopilot on when I’m stationary and the car in front of me is stationary it does not drive into the other car. If autopilot is on and a car is stopped at a red light in front of me my car does not slam into that car. I do this on a daily basis. Do you?
I don't drive a Tesla, but I’m guessing that’s done via image classifiers which recognize car rear ends, which have failed Tesla drivers on stopped fire trucks, police SUVs, Chinese garbage trucks, trailers crossing the freeway, etc.
The radar returns on stationary objects are discarded AFAIK because of poor radar resolution leading to inability to precisely locate objects both horizontally and vertically, leading to roadside and overhead signs being mistaken for cars.
Common auto radars have limited vertical discrimination, and this is partly intrinsic due to radar wavelengths.
I can't say I've come across these cases (stopped Firetruck for example on a highway) where AutoPilot has driven me straight into something. I'm also paying attention, as you should.
To throw you a bone, I do think that the names of the software lead people to believe that it's something more than what it is. Full self-driving is going to do things like swerve to avoid an obstacle in the middle of the road and it probably doesn't do that right now. But if we go back to the original post, the discussion was about comparisons to Waymo and Cruise. I'm not sure I trust their "more advanced systems" to do that either, and on top of that they haven't made a single production car that works in Erie, Pennsylvania and drives in the snow, changes lanes automatically, and navigates on and off ramps.
Tesla is making progress toward general self-driving, which is far and away more valuable in my opinion. Even if that progress is incremental. I look at it as more of a safety feature and something to make driving on the highway much easier.
If we want to take this a step further, I'm actually not a fan of self-driving cars because it makes it too easy to drive everywhere, and I view driving as a problem. We should be walking.
This seems pretty accurate, $8k for something that was called "Full self driving" that was supposed to be close to ready years ago and instead won't be ready for the lifetime of the car. This would have been a class-action lawsuit if Tesla customers weren't so spectacularly loyal.
I just drove from Dallas to southwestern Colorado and back. Of that, I estimate I drove ~15% of the entire miles driven. The rest was the car driving itself.
I see people keep stating this but I'm not so sure about it. Do we know what critically important data Tesla cars collect at scale _and_ are able to send back to mothership and who pays for that bandwidth/traffic? To my mind most of the useful information (video recordings or pictures of moments when the AI driver wasn't sure about things and/or human intervened) seems like it would take a lot of bandwidth to send back from moving cars.
Yes, according to Karpathy. The cars upload data (typically still images) which are then labeled by humans and used as training data to improve the models.
The impression I got from GTC a few years ago was that they're probably doing synthetic graphics simulations, based on edge cases identified by real world data.
You don't really need 1000x real examples of a scenario, if one still image provides enough information for you to mimic it in simulation. (E.g. toppled barrel, weathered paint color and reflective stripe, in front of exit guard rail)
I don’t have the link, but watch Karpathy’s recent talk on this topic on YouTube. He goes into detail about how this works. I’m not sure what their approach was years ago but it has changed significantly since.
There's a community of reverse engineers on Twitter that have demonstrated most of Musk's claims about their data pipelines aren't true. Check out greentheonly's Twitter.
>> Uber’s vehicles had also been having what the company refers to as a bad experience—such as a sudden jerk or a potentially dangerous movement—every one-third of a mile on average.
Pretty sure my wife would claim that I'm worse than that...
Self driving cars are dumping an insane amount of time and effort into computer vision and AI for the wrong problem. For the amount of tax subsidies, our money, given to these companies, we could have put down insane amounts of rail. Hell, we could even do small personal autonomous rail car test programs in some cities and it would still be more useful than the current state of self-diving tech.
Self driving solves the wrong problem, and it's a good 15+ years until we see this vehicles, if we even see them at all.
I'd offer Kurzweil's (I believe?) observation that the futurist predictions that come true are those that substantially improve peoples' needs.
Even substantially expanded rail will never solve the problem of "I want to get from point A to point B, as quickly as possible, whenever I'm ready to leave" in a fundamentally different way. The transit to the starting station might be shorter, and the transit from the ending station will be shorter, but it's still the same experience.
Autonomous cars solve that in the same way an personal automobile currently does, albeit removing the inconvenience of actually driving.
The former is like-in-kind. The latter is fundamentally-different. Consequently, if I am a consumer, how much would I be willing to pay for the former vs the latter?
Cell phones became ubiquitous because they were a fundamentally-different communication experience ("Call a person instead of a location"). Transit will be the same way, if it changes.
> Autonomous cars solve that in the same way an personal automobile currently does, albeit removing the inconvenience of actually driving.
The problem with autonomous cars as compared to rail is that autonomy doesn't solve the other fundamental problem of cars: congestion. If I waved my magic wand and replaced every car in the bay area with a self-driving one overnight, roads would still clog at rush hour.
As long as human drivers are still in the mix, no, self-driving cars will not solve congestions. But fully self-driving cars could improve road efficiency by an order of magnitude. There is no need for trafic lights, they can drive in very close formation, they don't need parking space nor search for parking.
Additionally, an inherently safe trafic system doesn't require 2 tons of steel around you for protection. The car can be stripped down massively reducing road footprint and ecological impact. You will also hail the smallest (cheapest) vehicle that serves your purporse, a single commuter can comfortably travel in a bumpercar.
I'd be curious what percentage of congestion is caused by accidents, which one would expect to substantially decrease in rate with autonomous electric cars (fewer impacts & maintenance issues).
If anything, self-driving cars would make congestion a lot worse. If I had a self-driving mini-RV, I would live further from the city, and do my morning routine during my commute. Maybe take a small nap or get some work done.
On the other hand, it'd so radically change the nature of being in a vehicle that it'd be hard to classify it as congestion as we currently understand it. If you're sitting in a comfortable pod with all the conveniences of home and productivity tools available to you in an office, then the impact of taking longer to get to your destination is much less significant.
Disagree - if traffic flowed more evenly, same speed for everyone, less lane changes, didn’t require the “safe distance padding” re-establishment at every light, the congestion would lesson. Probably not eliminated though.
Yes, if the amount of traffic stayed the same, having all self-driving cars would be a big improvement. But what I'm saying is that a lower cost of commuting (in terms of attention, effort, and danger) would induce demand. People would hate commuting a lot less, and therefore more people would do it. To offset that you'd need to either increase the speed dramatically or do something else so that more people can fit on the roads. Maybe smaller cars. Maybe pack self-driving cars automatically into trains. Maybe build a lot more roads.
But whatever it is, you need something major to counter the increase in commuters or else the road system will get swamped.
When you pack people into a train, you fit about 1 person per m². Pack people into a single-occupancy cars, you get about 1 person per 10 m², or 0.1 person per m². That's a 10× capacity loss that has to be made up somehow if you want to move people as efficiently as possible.
Autonomous cars don't solve the problem of inefficient use of land for transportation (actually, they probably make it worse since there will be a decent fraction of cars moving absolutely no one). Space is at an absolute premium in cities, and people really underestimate just how much space cars take up, particularly since that space is incredibly subsidized.
A purely autonomous road system would make much better use of space than the current system. For instance, you could discard with the notion of fixed lanes on a motorway as the system could nearly instantly allocate lanes on the basis of demand. You'd also be able to do away with curb side parking in urban centres, which would free up more land for commuting.
A train is obviously more still more efficient between fixed points, but self-driving cars are far more economical for less-frequented routes and more convenient for last-mile transit than buses.
> Even substantially expanded rail will never solve the problem of "I want to get from point A to point B, as quickly as possible, whenever I'm ready to leave" in a fundamentally different way.
But a substantially improved autonomous car driving experience - with cars communicating with each other (actively or passively) to avoid congestion, avoiding parking needs by being on the move always and increasing "bandwidth" by driving close to there other cars and still being safe - may look like railroads on all our roads. Bringing both these worlds closer to each other.
>Even substantially expanded rail will never solve the problem of "I want to get from point A to point B, as quickly as possible, whenever I'm ready to leave" in a fundamentally different way.
There is nothing ordained about this. If we stopped giving away billions of dollars of the most valuable real estate in the world (in the form of parking mandates and street parking) or stopped ruining neighborhoods with freeways and car-centric development then rail (and transit more generally)_could very well be better by these metrics.
The United States is structurally incapable of large-scale public works projects. There are a lot of reasons for this and they aren’t particularly partisan, rather reflect how decisions are made. My guess is places like China and Singapore will have the first true deployments of self-driving, because they’re actually capable of building road infrastructure to support it when it isn’t fully level 5.
The Hoover Dam was 85 years ago, the moon landing program was 50+ years ago, the interstate buildout was 40-60 years ago.
The disfunctionality of the US at large-scale projects emerged in the 80s, possibly to do with both the creation of the modern Republican agenda by Ailes (divisive populism over bipartisanship, and preference of tax cuts over maintaining infrastructure), and the acceptance of the environmental movement by the Democrats. Maybe also by the illusion that the the demise of the USSR meant the "end of history" and the focus can turn from trying to get the US to be #1 to prying to get a bigger slice of the pie domestically...
See "This Is Why Your Holiday Travel Is Awful: The long, sordid history of New York’s Penn Station shows how progressives have made it too hard for the government to do big things—and why, believe it or not, Robert Caro is to blame" https://www.reddit.com/r/gwern/comments/ez0l93/this_is_why_y...
Of course the elephant in the room is money. The public doesn't seem to have enough money to do projects.
One big takeaway point - IMHO - is that there's no scale, no growth in construction. So there's no big market, no new frontier for optimizing it. Sure, there are always a few startups, but that's peanuts.
Where are the trillions of dollars allocated to get good at building things in this century/millenium? Umm, nowhere. (Or basically spent on iPhones, housing and healthcare.) So it's no surprise that everything is custom made, challenged in court, takes forever and costs all the funds available and some.
Not really. Rail in the US is spectacularly expensive; look up a few recent rail projects with dollar figures attached, they're billions of dollars each. That's the same order of magnitude as the cost of an entire self-driving research program (Waymo has taken $3B of investment, according to its Wikipedia page), which, if successful, would scale quickly and easily to the entire world.
The important metric isn't the cost of the project, it's the cost per km (or mile, if you prefer). The construction costs for NYC in particularly are unjustifiably obscene--it's really on the level of "fire everyone involved and make the new hires go on a world tour of transit system agencies to learn how they do cost control before they do anything."
China and Japan aren't exactly low-cost construction countries. Actually, they're among the highest-cost non-Anglosphere countries (which are perhaps best labeled "stratospheric-cost" countries). Instead, you want to look to places like Spain, Italy, Sweden, or South Korea as low-cost countries.
Not sure where you’re located, but when are we gonna stop saying “the US needs more rail”? It’s not a solution in this country and never will be (Not outside major cities). People are too spread out, we’re not like Europe or even Japan, where the habitation area is actually quite small. People want to leave when they want and go exactly where they want. Gasoline is cheap here making cars cheap to own and maintain. It’s tough to move things while carrying them on a train, a reason so many people have trucks and SUVs. This doesn’t even consider all the cost related reasons outlined in other comments.
Electric self driving cars are the future of the US.
From a mile high view, does it matter what the problem is? Early laptops got us the lithium battery. ICBM's got us integrated circuits. Calculators got us microprocessors. Maybe in twenty years we'll look back and say self driving cars got us human-level computer vision- to be applied to anything you please.
I 100% agree with this. A much better endeavor would have been to built a robot highway and only allow autonomous vehicles on it. Like trains but using 4 wheeled vehicles.
Why would that be better? 2.5 billion doesn't get that much highway and even less robot highway. If you're not someone living on or near the robot highway you get no benefit from it and the vast majority of people won't be living anywhere near the robot highway.
Conversely, inventing self-driving cars scales really well. Invented once. Commoditized. Sold worldwide for a profit. Massive benefits to everyone worldwide.
It's disappointing that Uber's research isn't paying off, but it's clearly a bet in pursuit of much higher stakes than making a highway.
I'm uncertain, something like 20 billion dollars (maybe on par with the amount of funding for self driving cars?). wouldn't really go all that far unfortunately for American transport prices.
No one can read this article yet it is instantly upvoted to the very top of HN. Goes to show how discussion forums like this one just serve to amplify people's existing biases rather than actually educate them on anything new.
> No one can read this article yet it is instantly upvoted to the very top of HN. Goes to show how discussion forums like this one just serve to amplify people's existing biases rather than actually educate them on anything new.
Maybe everyone that is upvoting it can read it b/c they subscribe to the news site, and maybe your comment shows your existing bias about your thoughts on other readers of this discussion forum?
I'm pretty sure it has more to do with the HN algo where some keywords rank higher than others. "Uber" "Billion" "Self-Driving" are hot topics by themselves and this one is all of them in one.
In terms of keyword ranking, from what I've observed the only think taking into account things such as keywords with respect to ranking is the readers voting and flagging.
I would frame it as "in discussion forums people upvote articles because they spark interesting discussions, even if the article is uninteresting or only available to few"
> Critics question why CEO Dara Khosrowshahi hasn’t held the team accountable.
Because Uber's insane valuation is largely predicated on them being able to pivot out of expensive human "driver-partners" into cheap and compliant robots, and any sort of public acknowledgement that this is not going to happen would tank their stock.
There is really nothing to back that claim. There are plenty of other companies in similar sectors (ridesharing, transportation, food delivery) in the US and beyond with similar valuations and no self driving ambitions or technology. Uber's self driving research has been seen from day 1 as an expensive hobby, nothing more.
A company which can achieve level 5 automation and has the capability to roll it out worldwide is worth a hell of a lot more than $60 billion.
I think the broadest interpretation is that autonomous driving was one of a few irons Uber has had in the fire to achieve profitability. The other irons include Uber Eats, Jump, and lately, grocery delivery. The miracle hasn't happened yet!
Okay, so in the extreme case Uber's self driving division is estimated to be worth ~$7 billion? That proves my point more than it refutes it. Their stock has fluctuated more than that this past month.
That $7 bn valuation came only a year after the disastrous 2018 crash which forced them to shut down the entire program for months, with months of of lurid news stories highlighting failure after failure. Probably a low point, actually.
The developing narrative seems to be that self-driving was a longshot that could have paid off hugely, had it worked out, but it's been plagued with problems and it just seems very unlikely to pay off now. But still not zero, since no one else has shipped anything.
Investors probably valued it like (0.7% chance of success * 1 trillion upside = 7 billion).
I'm not sure that self-driving cars would make the difference to Uber's profits that everyone assumes. Uber would probably have to own all the vehicles and pay all the costs associated with owning a huge fleet. Has anyone actually done the math on how much money that saves over paying drivers?
Clearly, we should aim for a less ambitious goal: ultra-compact self driving vehicles on dedicated and physically separated lanes, where cars cannot be encountered unless it's their fault, similar to bike and tram lines.
This could increase city trafic capacity by an order of magnitude in congested central zones and suplement public transport in suburban, dispersed areas that cannot be properly served by buses.
And it could be done today, with simple algorithms: stay in your lane, coordinate with other vehicles and the trafic lights, and when anything that looks like an obstacle is in front, brake.
My father's a civil engineer, and has told me they've been trying to do this since the 70s. The original plans were to put a magnetic strip beneath one lane of our freeways that could allow simple lane-keeping and some basic communication to keep the cars properly spaced, then raise the speed limit up 100+ mph for those lanes.
The problem is, once you ask anything of government infrastructure, it may take forever. I could maybe see it eventually happening if these companies lobby heavily for toll lanes, where autonomous zero-passenger vehicles pay the bulk of the fees.
I don't see how setting up an entire new parallel road network all over the world is "less ambitious". Some of the best funded cities in this country aren't even able to lay a few miles of fiber for broadband internet.
Cities usually go as far as having dedicated lanes for buses on a few main thoroughfares. That is a far cry from having a self driving car not encounter any human driver during the drive from my home to my office or the grocery store, for example.
The goal is not to never encounter a car, but that the encounter is mediated with very robust and proven technology that is compatible with both human and current level AI, like a V2X enabled trafic light or a steel bollard. A car can still hit the pod if it disobeys the red light, but the driver would be culpable and the incident itself would be similar to a car hitting, say, a bike - not the fault of the bike.
As for the density of such infrastructure, you don't need it on every street, just within a short walking distance to be practical, a few hundred meters maybe. Once you can reach the hail point, it can take you non-stop to any other in the area served, so something like 30 Km/h top speed can go a long way.
If you used battery electric cars would likely be a lot cheaper to build.
Speaking of electric, in Taiwan they have occasional dedicated paths for scooters. With the advent of battery power bicycles grade separated bike lanes seem more useful. Because battery power eliminates the hill problem.
They can route people from fixed point A to point B, and some locations along a predetermined rute from A to B. Personal rapid transit allows a Many to Many mapping, just like cars.
Yes, the auto-pilot is easy on rails (Morgantown built one in 1975), but rails are expensive, many to many rail networks are even more expensive, and grade separated rail networks are insanely expensive. The Morgantown system final price was 12 million 1975 dollars per mile.
So by using advanced self-driving concepts (but not yet full self-driving alongside human drivers), you can repurpose much of the existing road space for personal public transit, without creating completely new infrastructure.
What I've never understood is how you're going to get a car to understand a construction worker or cop doing hand signals without artificial general intelligence. Why even bother with the car until you've figured that out in the lab?
Hand signals are pretty standardised and obvious, and even the first Kinect (XBox accessory from 2010) can estimate people's skeletons sufficiently well to figure out construction worker hand signals. I would expect that you can solve this pretty well even without any ML at all.
Even if you can identify the hand signal, and identify that a construction worker is giving them (establishing authority that the car should follow this signal), the signal contains a lot of implied information.
If the worker indicates you to go into the opposing lane, how long should the car remain there? How do you tell the construction part is done and you should return to normal self-driving logic? Sometimes there are cones, but sometimes not. American workers do often have Slow / Stop signs, giving a clear indication of when to move at least.
If you are going down a street slowly, and someone is wearing a hi-vis vest for their own safety, and they point at something, is your car going to follow that pedestrian's instructions?
A simple solution around that problem might be for these companies to form a consortium to develop and distribute (for free) autonomous car friendly signalling equipment to municipalities.
This article is behind a subscribe wall, which isn't very conductive to sharing. But upon reading, it seems to be that the technology is just not capable of performing the task. The assumption that deep learning is sufficient to be able to drive a car may be a faulty one.
Deep learning alone has long since been considered a faulty approach (see ALVINN), since it could produce a car that can sort of drive, but nobody knows how, and when a road rule changes you have to retrain it from scratch.
That's not what I got from the two paragraphs it's possible to read. It suggest Uber "is destined to lose the high-stakes race to its rivals, which have demonstrated a lot more headway" which sounds like it is doable, just not by them
Waymo seems to be doing much better than Uber, so it can't be just about what's possible. Waymo are also doing much more than just deep learning. For example a deep learning algorithm might be good for predicting possible paths of tracked pedestrians, but figuring out whether you will intersect any of those paths is better solved by a different non-learning algorithm.
Waymo almost predates the current deep learning fad.
While I'm sure they have deep learning somewhere in the stack, the core of their algorithm appears to be based on more traditional techniques, with kalman filters being the core.
> Didn't they lose a lawsuit against Waymo, which meant they had to build a lot of tech from scratch and, to add insult to injury, keep Waymo informed of the details?
That’s really interesting. Does anyone have a link to where this was stated?
Apologies, I deleted that last part of my comment after I tried to search for this and failed to find evidence. I'm not sure if I'm remembering wrong or if this detail was in some obscure article somewhere.
I interviewed at Uber a few year ago, pre-IPO (bullet dodged!). Their pitch, from a senior VP, was all about self-driving, even though I wasn't even looking at a self-driving role. But at the time, it struck me as a complete farce that this company that made its success by replacing cab drivers, was trying to convince me that it's actual success would come from them cracking a problem they hadn't cracked, which no one had cracked, which was not even close to being proven feasible.
Somehow they felt that they would simply "be the world's transportation" (their stated goal) based on a completely unproven technology.
I hope someone can share the full article, but a Reddit post at least had some excerpts:
> Numerous ATG employees have privately said that nobody else at the company appeared to pay a price for the blatant mistakes that preceded the deadly collision and the fact that the units management ignored clear warning signs. For instance, a manager directly warned Meyhofer and other leaders before the collision that the unit's robotaxi prototypes were dangerous-one of them had swerved onto a Pittsburgh sidewalk and continued driving — and that the company did not terminate human backup drivers even if they repeatedly screwed up.
> In mid-2018, several months after the collision, a departing senior manager of ATG sent Khosrowshahi a 35-slide presentation outlining problems in the unit, according to a copy of the presentation that circulated across the company at the time and that The Information viewed. The document alleged that months after the collision the unit still had "inadequate" safety and testing procedures and a propensity for "theater" — celebrating what the team had designed "when we didn't yet have substance" in the form of a working prototype.
> This manager also told Khosrowshahi that the unit's software engineering team was populated by "university researchers" — a reference to the CMU lab where many Uber engineers, including Meyhofer, came from who didn't have much experience in commercializing technology for the real world.
> The former manager declined to discuss the presentation or their experience at the company with The Information. Uber has significantly upgraded its safety practices in recent years, according to Meyhofer and other employees.
> In the same time period, Uber's vehicles had also been having what the company refers to as a bad experience — such as a sudden jerk or a potentially dangerous movement — every one-third of a mile on average. The company's leaders had hoped the figure would fall to just one bad experience every 10 miles by fall last year, said a person with direct knowledge of the goal. One person who worked on the effort told The Information they felt the prototypes were better than the data indicated.
> Uber couldn't even get the prototype to drive a one-mile stretch between the unit's two Pittsburgh offices, with the goal of shuttling employees back and forth. Software leaders said they gave up trying because automating the route for internal use wouldn't help Uber develop software that it could apply to a broader array of routes. But other managers said the failure sent a message that Uber just couldn't pull it off.
> For his part, Meyhofer said road testing helped the unit's broader mission, including giving the team ideas on how to improve the way it configures the car's laser sensors. "Every time we do any kind of development, it shows us a lot of things we can do that will get us even better results" in the next test, he said.
> Meanwhile, the company is focusing on developing new autonomous driving software to replace the version now in its prototypes, which includes code academic researchers wrote about a decade ago. The new software, rNA, is nearly ready for testing on public roads. Meyhofer and other current and former employees said INA-which took longer to develop than originally anticipated-was a necessary upgrade to allow the company to incorporate new machine learning-related techniques that help vehicles better understand the world around them.
Self-driving tech should be focused on driver enhancement and not replacement. This is an incremental evolution area until all the 100 edge cases are 100%.
The self-driving enhancements they could give to existing Uber drivers to help them stay safe over long driving periods would be huge. Drive that flywheel (easier driving leads to more drivers, cheaper trips, more riders, etc.).
Let drivers multitask under safe scenarios in under 10mph traffic jams, open areas, queues, etc.
Build up those enhancements and you have a formidable, cheaper driver fleet that people would use perhaps v. buying a car.
I wouldn't mind paying something like $2 to read the single article, but $40 for a subscription that I have to cancel is just asking for too much, for a site that I will likely never come back to.
>I feel as though paywalled links should be heavily downweighted as most of the discussion will uninformed.
Incredibly frustrating to read comments like this. We can't rely on ad funded and corporate funded journalism forever. Downweighting actual attempts to fund real journalism is completely misguided.
This argument doesn't make sense. The purpose of this site is to discuss articles and other things. A prerequisite to discussing an article is to read more than its title. Sure, "real journalism" is good to have, but given that posts like this are allowed, what fraction of commenters in threads like this will sign up and support non-corporate journalism, and what fraction will clutter up the thread with uninformed comments?
The argument doesn't make sense to you because you assume every other person on the site isn't willing to pay for news. However, there is a 3rd option: you could just not participate. There is nothing in the HN rules that dictate you must participate in everything posted here.
By HN design, if such sites aren't useful to the HN community, they wouldn't be regularly upvoted. However counter to that, every week you see an article from wsj.com, theinformation.com or bloomberg.com hit the front page, precisely because despite having paywalls they continue to produce good content. Given the amount of engineers sucking six figure salaries on this site, I'd say a good percentage of them who might value actual news may pay for a subscription, which is why these sites continue to be posted here. I wouldn't want to see wsj.com downweighted below buzzfeed.com just because buzzfeed is free.
The ones who choose to complain, rather than just abstaining, are the problem. They could simply decide to not participate and HN wouldn't be any worse off. However the complaining that news organizations must (1) offer all news for free (2) don't use ad networks and (3) not be mouthpieces corporate PR is not going to accomplish anything.
News publishers worldwide are setting subscription prices too high for any one reader to support all of them, because that wasn't practical in the age of print. But it's the only way for a publisher to be compatible with a worldwide news aggregation and discussion audience.
Self-driving tech should be focused on driver enhancement and big replacement. This is an incremental evolution area.
The self-driving enhancements they could give to existing Uber drivers to help them stay safe over long driving periods would be huge. Drive that flywheel.
Let drivers multitask under safe scenarios in under 10mph traffic jams, open areas.
Build up those enhancements and you have a formidable, cheaper driver fleet that people would use v. buying a car.
Boil the ocean and you’ll be useful merely for your learnings to others.
There's just no way self-driving cars can meet the challenge with today's technology. These days the tests they are doing involve burying a wire in the road that the car can ride upon, which to me seems like covert recognition that computer vision and sensor data feeding AI is not equipped to handle the rigors of road travel quite yet.
The theoretical arguments about how self-driving cars are better than human drivers remain theoretical.
Did actual business goals ever align with the aspirational marketing though? I find it hard to believe that the actual people building it didn't know that real widespread autonomous driving was more than a pipe dream in the foreseeable future. They still managed to suck up piles of investor cash, maybe that was the real goal?
They rushed headlong into this, knowingly stealing IP from Google in the process, because their business model is currently unsustainable with human labor and this is the only way to make it work. It's unsurprising that they're struggling.
A moonshot isn't something that you need to figure out how to achieve, it's something you already know you can do as long as you dedicate a lot of operational and material resources to it.
There's more real money (hint: lobbying money) backing electric cars right now than there is backing autonomy since everyone in the industry knows it's at least 5 years before we get borderline level 4/99.99% reliable level 3 driving and a good 30 years before we get the 8+ nines that are needed to truly go to level 5 autonomy; most local laws are already well equipped to handle people using level 4 autonomy, so it isn't a priority thing to address.
Edit: I realize that level 4 doesn't ask you to take over, so I've edited my comments to reflect that.
I'm talking about four nines in terms of reliability (not crashes) and on level 3, where the car still has all the regular driving controls - so if there is a problem or the system has high uncertainty about certain road situations it can force/return control to the driver and have them navigate the unknown situation. I'm also probably being too optimistic predicting four nines in 5 years, it'll probably be 10 years or more for people to be able to reliably take their hands off the wheel for extended periods of time on interstates.
Edit: I realize that level 4 doesn't ask you to take over, so I've edited my comments to reflect that.
the issue is that randomly requiring non-professional drivers to take over during a trip is an underestimated danger. people get accustomed to it working 99% of the time and get lazy - then the 1% it fails and the driver is asleep or distracted or watching a movie and becomes a major safety issue.
ex all the horror stories of distracted Tesla drivers using autopilot like full autonomous driving today.
Furthermore, if you stipulate hand-offs will sometimes be needed, you now can't use the car for many of the use cases that proponents want because you need a competent adult driver to take over.
And, yes, people imagine scenarios like remote drivers taking over. That seems a very difficult problem--especially if the situation is such that the autopilot is confused.
It's not that black and white. The unnerving thing is that self-driving cars have completely different failure modes than drunk humans: instead of falling asleep and drifting into the next lane, they do (to humans) absurd things like mistake the side of a tractor-trailer for empty space and merge into it.
I firmly believe that the literature produced which shows self-driving cars are safe or even safer, and there is scads of it now, is mainly down to the program's ability to make sure a safe following distance is observed leading to greater reaction time for braking. I know a lot of driving tests have been done in simulators which show the AI can be safer but I agree with your statement.
I also have very little confidence in the AI's ability to stop at road construction, make its way over temporary embankments and diversions placed for construction, navigating in inclement weather or adverse traction situations like a muddy drive, etc. I suppose the real goal here is for Wal-Mart and Amazon to move freight on the Interstates to begin with but I don't even see that happening any time soon. Your average Wal-Mart loading bay and parking areas are likely much more than any current AI can handle anyhow. How does the AI know the person in the mart cart isn't going to just jut out in front at the last second? Can't exactly make eye contact.
Personally, I don't think so. If anything we might need less machine learning.
It's mostly a problem of sensor fusion. Once your self driving car has a good view and solid understanding of the surrounding environment, the actual driving algorithm is reasonable simple. All you really need is really solid software engineering to implement it with minimal bugs.
The problem is getting that understanding. You can't have objects pop in and out of existence. You can't have computer vision misclassifying objects or just not seeing them.
It might just require better sensors, or more types of sensors. Or we might need to work on interpreting the data and understanding the actual situation.
I believe so. There are way too many variables when it comes to driving. I honestly don't think it's possible to solve the problem without huge advances in general purpose AI that can do its own goal setting ... and then I just imagine Marvin from Hitchhiker's Guide...
"...one of the most advanced robots in the galaxy that can do billions of computations a second and you ask me to do the most mundane tasks... go open the door Marvin. Go pilot the ship Marvin. Go fix the reactor Marvin ... Go drive my Tesla Marvin ... I think you ought to know I'm feeling very depressed..."
So replace roads with tubes containing a fixed track that prevents animals, weather, and people from interfering. Then add tube outlets to areas that are frequented by most travelers. You could even put these tubes underground to save space, and instead of large individual cars you could optimize the vehicles for many passengers in a small amount of space.
I am not surprised. This is a competition between Tesla and Google, technology companies. I never saw Uber, a services company, as being part of this race.
One company builds a ride hailing app while the other builds one of the premier, high-performance EVs in the world with significant levels of driver assistance, over the air updates, and world-class onboard perception that industry incumbents readily admit is "years" ahead of their own development.
How exactly would you characterize the comparison?
Uber is more of a tech company in that their entire value is based on internet connectivity (while Tesla could take a 99% market cap hit and still put together metal on an assembly line), but Uber is less impressive since it's just an app and an API connecting drivers to people and sometimes throwing a restaurant in the mix.
People forget these days that technology (i.e. “tech companies”) does not equate to the internet, which is a just small subset. Technology is defined as “the application of scientific knowledge for practical purposes, especially in industry.”
maxlamb captured my sentiment exactly... tech is not synonymous with "internet connectivity".
Modern vehicles (ICE or EV) are vastly more sophisticated than "putting together metal on an assembly line" -- they're modern marvels of all the physical sciences: chemistry, thermodynamics, materials science, electronics, mechanics, aerodynamics, wireless connectivity, reliability, safety, real-time controls, computer vision, sensing, and on & on & on. Vehicles are vastly more "technological" than most mobile phone apps, especially one like Uber.
Pure software companies may (rightfully) fetch higher valuations, but that's simply due to the nature of their economics: higher margins, pricing power (oligopoly?), and negligible incremental unit costs.
It’s just my perception, but Tesla and Google both have track records of developing new technology IP to overcome their challenges. Uber’s record is not the same, they don’t have any hard to reproduce software or technology IP at the core of their business. Their strength is the brand that has quickly entrenched itself in many cities fighting public legislation to satisfy its goals.
Uber has yet to show a vehicle with any semblance of reliable autonomy. Tesla has billions of experience miles at Level 2 autonomy (Navigate on Autopilot is close to, but not quite, level 3 autonomy).
I personally believe that level 3 is completely useless. It requires the driver to be completely aware and ready to take over the driving with a second notice whenever the car gets in over it's head.
It seems like level 3 is more dangerous than a 100% manual car.
Even high-end level 2 seems dangerous.
Until we get self driving cars to level 4, were they don't require the driver to play attention, I don't think self driving cars should be on the road.
I think they mean the green bits there are the part where the car can be relied on to drive by itself (with the blue bits requiring constant attention).
Arguing about what to call it is boring. Is Tesla close to having a system that can drive without attention, decide it isn't sure what to do and safely request driver attention? Or does it just have the bit that can successfully navigate a lot of situations?
Having driven across the US almost 30k miles on Navigate On Autopilot in our Teslas, I’d argue the former (“Is Tesla close to having a system that can drive without attention, decide it isn't sure what to do and safely request driver attention?”). Attention is given, but intervention is rare, even in construction zones (only done when zones are inactive, not with workers present for obvious reasons). Interstate to interstate transitions, passing of slow vehicles without our intervention (“lane changes without confirmation” feature) is mostly flawless.
Edit: if I didn’t make it clear, Tesla vehicles safely hand over responsibility to the driver when path planning confidence has been lost. If you don’t take over, the vehicle comes to a stop with the hazards on. If you haven’t, I recommend taking a free test drive yourself to better understand the system constraints and UX.
If the system/software to safely hand over control isn't present in the vehicle, what does driving 30k miles demonstrate about how close they are to deploying it?
Much of the distinction between level 2 and level 3 is that the vehicle reliably hands over control. Successfully navigating situations doesn't provide much information about how close that capability might be.
Level 2 means the driver always has responsibility.
It's good that the Tesla system stops making inputs when it doesn't know what to do. That's different than the Tesla system having full control and safely notifying the occupant that they need to start driving.
It maybe competition between Tesla and Google, one day in far away future.
But so far, Tesla is dead last in self-driving cars. They some cool driver-aid systems, but their self-driving tech is still being written and rewritten, and didn't even begin any tests on the roads.
And yet there are tens (hundreds?) of thousands of drivers who use Tesla’s Autopilot every day, myself included, without incident and to great benefit.
All attempts at self-driving cars are a failure so far. There are no exceptions. If Uber is struggling, they're all struggling. I expect similar if not worse stories coming out for the rest of them.
It's kind of grim, but so far Uber and Tesla are the only ones to have killed people, and the Tesla case is more ambiguous. There's clearly big problems at Uber compared with the others, though I too think that the tech is further in the future than people were saying a couple years ago.
Waymo and Cruise are being much more careful. Consequently, they’re finding out that self-driving cars cannot be deployed yet without being dangerous to people. It’s not a surprise that Uber and Tesla have killed people.
The most shocking detail:
> Uber’s vehicles had also been having what the company refers to as a bad experience—such as a sudden jerk or a potentially dangerous movement—every one-third of a mile on average.
That's really bad. While there are no uniform standards for what a "bad experience" entails, my general sense is that Waymo and Cruise (widely considered first and second) are doing 10-100x better by that metric.
Another damning bit:
> Uber couldn’t even get the prototype to drive a one-mile stretch between the unit’s two Pittsburgh offices, with the goal of shuttling employees back and forth
I don't even know what to say to that. If you can't make your cars work reliably on a known, one-mile stretch of road, what have you been doing for so many years?
[Disclaimer: I work for Lyft, but not on the self-driving car program.]