I doubt there's ever going to be a big bang moment where self driving just works everywhere. Instead it's going to be a slow rollout of self driving taxi's in increasingly different environments.
Of course. We're still there with the horses -> cars transition. There are still plenty of places that horses can get to but cars can't.
And similarly: the transition will also go in the other direction. We'll start making roads and navigation easier for self-driving cars and prioritize the destinations we care about the most. At the tail end of the transition, there will still be areas with ridiculous intersections and confusing rules that only humans can do. We just won't care about them as much by then because everything we do care about is reachable by self-driving cars.
I think it's actually going to be the other way around. We'll build infrastructure exclusive to AVs where the rules are too complicated for humans, but allow AV traffic to move more efficiently. For example, an AV shouldn't need to stop and wait at a red light if there's no traffic to wait for.
To be fair, you also don't have to stop at a traffic light if there's no traffic to wait for if you don't want to. Just drive across the bridge to Oakland to see it in action.
Roads are already easy to drive. We already have signs on roads directing people to the most prioritized destinations. And now we have navigation apps that can even provide turn-by-turn and lane-by-lane directions. The issue is that most people simply ignore traffic rules when it is convenient to do so.
We didn't redesign roads and navigation for taxis or rideshares, and we're not going to do that for self-driving cars either.
We absolutely do redesign roads when the existing design becomes suboptimal as indicated by an increased number of accidents or driver complaints. And we do sometimes have lanes specifically for buses / taxis, too.
We already do this stuff, and we won't need to rebuild 99% of roads. It's the "less than 1%" that are already tricky for normal humans that might need a rework. Or self-driving cars will just take suboptimal routes, if those roads / intersections aren't the only ways to important destinations.
Where I live in Seattle, they have rolled out significantly more 5-30 minute loading only zones on former street parking to deal with the uptick in rideshares and food/parcel deliveries, because the alternative is a bunch of illegal double parking.
At 2 trips per day for 300M Americans over 7 days, that would put the rideshare takeover at ~4.2Bn. If we extrapolated based on the referenced graph and exponential growth, that would put the takeover at 2029 :)
Its safe to assume that the limiting factors will soon become sourcing of components of the perception and control stacks.
Yeah, I wonder how much money they're pouring into lidar production. Particularly considering that they've partnered with Hyundai, Stellantis, Mercedes-Benz Group AG, Jaguar Land Rover, and Volvo.
I'm not going to get excited until this can drive in Boston/Cambridge. If it can navigate that nightmare (and not kill any cyclists) I'll be impressed with what self-driving cars can do. Bonus points if they can work in snow when sightlines are obscured.
They have been navigating the SF Tenderloin for over a year. Entire streets are a crosswalk. Most biologic drivers would barely function there. But I do wonder how lidar/visual integration works in snow.
I don't know. Boston and New York may have a culture of taking whatever right of way you think you can get away with. The West Coast historically at least was more known for enforcing jaywalking though given the current state of SF I'm not sure that's still true. Boston/Cambridge also has a huge influx of students every year, many of which are pretty clueless about navigating an urban environment safely.
Depends on the location. I don't like driving in SF especially but there are some areas of Boston that are pretty crazy if you're not used to them and don't intuitively know when to get over into some lane and aren't used to driving pretty aggressively at times.
It's worth keeping in mind that autonomous vehicles find different things challenging than humans do. Weird road shapes and knowing how to route into some lane is pretty straightforward with map data. It's the "normal" parts of driving like predicting other road users that are more difficult.
Totally fair. Things I might find challenging as a human unfamiliar with a given location (though GPS tends to help a lot) are probably different from an autonomous vehicle dealing with a lot of borderline crazy behavior by other cars, cyclists, and pedestrians darting out into traffic. A person also can just process so many inputs at once so you get into situations that are challenging in part because so much is going on.
Absolutely. Every country, state, city, county can enact their own regulations as they see fit. This is Uber rollout on steroids, imo. There are some many hurdles to making this happen even if the tech exists.
In places that have real winters, there are going to be significant blocks of time where self-driving will never work unless real synthetic intelligence is reached.
Way too much of this is developed in places that... don't have weather.
AV companies test in winter conditions. Waymo had NYC and Buffalo deployments years ago, and they do winter testing in Tahoe and Michigan. This winter they'll do the upper peninsula, Detroit and Tahoe again.
I'm not sure what you consider "real" weather, but those are all places I think qualify by any reasonable definition.
When you stomp on the brakes in a reasonably new car that's skidding on ice and it makes a loud thunking noise, what is that, and what's controlling that system?
It's been standard in cars for a long time. It's a really pretty simple system that ensures that your wheels aren't just completely stopped while you're braking hard on slick services. When the wheel's are completely stopped there's less friction than when they're still rolling near the speed of the road. Also when your wheels are locked steering is nearly impossible, but you do have directional control while they're still rolling.
Some of the systems are more advanced than others, but the basic version just compares the speed of the wheels to each other.
And this ay-bee-ess system is able to control the car and bring a car to a stop on snow and ice in way shorter a distance a human is able to, to the point that new drivers are taught to stomp on the brakes and let the computer control the brakes because it's able to do it better than an ordinary human; this system is controlled by computers? But then somehow driving on snow is going to be this total show stopper that is just utterly insurmountable gotcha for computers driving cars? Nevermind that crawl, walk,
and then run/go out in the snow is a totally reasonable way to deliver a product, and that even if it never works in the snow, there's enough of the global that doesn't get snow (no thanks to global warming) that it's still a worthwhile investment, even if only to prevent drunk drivers from choosing to driving drunk during the summer months.
Driving on snow is just an exercise in modeling friction in a computer and which way the car will go given available sensor input. Self driving cars don't innately have a concept of friction the same way a human with feet does, and they're able to drive on static asphalt, and also snow, with some training. Human drivers should practice driving in the snow in a parking lot to understand how the car slips and slides and grips operates under those conditions before taking to the road. (It's also fun!)
I'm sure it'll take a lo of doing to winterize the sensor packages and for the software to work well enough to be reliable when there's just snow on the ground that hasn't been plowed recently, nevermind when it's actively snowing. But personally I think it's a when and not if as to whether or not self driving taxis will ever hit New England. (No guess as to a specific timeframe though, lol.)
I can't suppress the strong feeling that they will, not by being technologically mature, but by easing a lot of regulations that are restraining them now.
Especially with Tesla's Ceo soon to be a member of the government.
Just like cars companies made jaywalking illegal or bought public transport companies to close them.
Is Tesla a serious competitor in this space? I know they've made a lot of noise about self-driving cars, but that all seems to be hype generated to sell more human-driven cars. Maybe I'm off base here. I don't really follow Tesla closely.
It depends on what you mean by competitor. afaik Mercedez sells a self-driven level 3 autonomous car where they even insure the driver/car, but it's pretty expensive. Tesla has the numbers, but not a single car that can do as much as the Mercedez. Tesla promises they can just push an update an everybody gets a self-driving car, but they've been saying that for... 7 years maybe?
From your link, the Cybercab is a concept with an unknown release date using technology wasn't even demo-able during the reveal. This seems more in line with my comment about generating hype rather than a convincing show of capability. Even if they do release it, which would be cool, wouldn't it be like a decade behind Waymo at that point?
It's still far from ready to release, but it is also improving very quickly - far from solely hype. They have the most impressive non-geolocked self-driving system as far as I'm aware.
It still won't be a big bang moment. There might be a moment you can go hands off on highways, and a moment you can go hands off in urban environments. But it's still going to be gradual overall.
My understanding is that Tesla's approach is to not require hyper-detailed maps. So far it doesn't work well enough, but if they do manage to get it working, then I think it will actually be a "boom, suddenly it works everywhere" moment. Waymo One, by contrast, requires extremely detailed maps of the service area, which is why they can only slowly roll it out place by place.
I've been a bit surprised that no one (well GM was mildly pushing in this direction at one point) has really gone after autonomous driving on selected highways within some weather parameters. I know urbanites get all worked up about robotaxis but a system that lets me chill for the next 100 miles of highway driving seems far more interesting if it's reliable/safe.
Tesla FSD already works everywhere, even on unpaved roads. It just doesn’t work as well as Waymo.
Waymo works very well, just not in as many places as Tesla.
You might bet on Waymo because they have a fully working product already, but I’m betting on Tesla because of the vast amount of training data they are collecting. There’s a bitter lesson here.
> the vast amount of training data they are collecting
They keep pushing this point. And they do appear to be collecting an absolute firehose of data from the millions of vehicles they have on the road. By comparison, Waymo collects a lot less data from many fewer vehicles.
Which leads to some tough questions about Tesla's tech. If they have (conservatively) 10x the training data that Waymo has, why can't their product perform as well as Waymo? Do they need 100x? 1,000x? 10,000x?
Assuming they were at parity with Waymo today, this would suggest that their AI is only at best 10% as effective as Waymo's, and possibly more like 1% or 0.1% or whatever. But since they can't achieve parity, it's not even possible to bound it.
It's entirely possible that their current stack cannot solve the problem of autonomous driving any more than the expert systems of the 60s could do speech translation.
I haven't heard a compelling argument as to why a system that is at best 10% as effective would ever be expected to be the leader.
Data isn’t as useful here as in other domains, since when you change the car’s behavior even a tiny bit, a lot of the timeseries is invalidated. It’s not evergreen, and it can be quite subjective what it means to “pass” a scenario that one previously failed.
Also, Tesla collects data from its fleet, but that data’s fidelity is likely quite limited compared to other companies, because of bandwidth if nothing else. Waymo can easily store every lidar point cloud of every frame of driving.
FSD and Waymo are completely different products. FSD isn't even autonomous, as the user manual reminds you:
Always remember that Full Self-Driving (Supervised) (also known as Autosteer on City Streets) does not make Model Y autonomous and requires a fully attentive driver who is ready to take immediate action at all times.
I hope for the best for Tesla, but they are many years behind Waymo. The world definitely needs a second working self-driving system! Right now comparing Tesla and Waymo is nonsensical. Once you can sit in the backseat of a Tesla while it drives there might be some worthy comparisons to be made.
My definition of "works" includes the fact that a self-driving car will never drive into a parked fire truck, or many other things i've seen tesla FSD do.
Well and because they actually have real self driving cars without a safety driver. Tesla doesn't have that and only has demoed it in very specific scenarios.
I own a Tesla, though I don't own FSD, but this year, Tesla has given all cars a trial of FSD on two occasions. It works remarkably well. I backed out of my driveway, then enabled FSD and it drove all the way across Portland to a friend's place with zero intervention. It was about a 15 mile, 30 minute drive.
It navigated neighborhood roads without markings and tons of cars parked on the curb. It got onto the freeway and navigated, including changing lanes to overtake slow traffic. Once I got to their place, I was able to tell it to automatically parallel park on the curb.
As far as I'm concerned, Tesla has fulfilled their promise of full self driving. The "supervised" requirement is basically just being used as a legal loophole to avoid liability if it fails.
> The "supervised" requirement is basically just being used as a legal loophole to avoid liability if it fails.
"If it fails" - so it is supervised for a reason then. It makes sense because FSD has an intervention rate in the low double digits according to community trackers like https://teslafsdtracker.com.
I don't understand the "bitter lesson" reference here. The bitter lesson is that general methods of computation are more effective. How is one of the two not using general methods?
My understanding is that Waymo is applying specialized centimeter-scale mapping and lidar to achieve superior results.
In contrast, Tesla is using dumb cameras and just dumping boatloads of data into their model. It’s a more general solution. Maybe the reference doesn’t fit perfectly - the model architecture is likely similar under the hood - but there’s some analogy there.
Just saying they have better results because of mapping and lidar is incredibly reductive. They have an extremely sophisticated AI/ML stack and simulators.
One challenge for Tesla and Waymo has been the piecemeal permitting process. Even though California gave Waymo a statewide permit they have still needed to work through various cities/counties for permits. I imagine one goal of Musk's is to make that all go away sometime next year. I'm not making a comment on whether I agree that is a good idea. Just speculating.
If training data is such an edge for Tesla, how is it that Waymo works so much better than FSD with only 1/1000th the data?
I also don't see any evidence that Waymo can't work anywhere. They recently expanded to Austin, and it seems that it immediately drives better than FSD.
I'm betting on Tesla not for the technology, but because President Quid Pro Bro is probably going to issue an Executive Order that turns every Tesla company into a federally blessed monopoly.
Indeed, it was not very long ago that FSD would happily take a straight line through a roundabout, lanes or "skirts" be damned, essentially treating it as a standard intersection.
It looks similar to a cable/fiber rollout where they have to onboard each region individually. I know they are currently doing this in the Atlanta metro.
Like cable/fiber, once they have good models of the business and what it costs to roll out, they have the freedom to accelerate and do regions in parallel. If the business works, I would expect them to scale the pace of rollout.
This is the root of the misunderstanding, I think. You’re begging the question.
More data does not necessarily mean better data. You can collect many more individual driver experiences, but if they do not have sufficient resolution in the necessary dimensions, they may never provide “better data.” Similarly, even if the magic data is hidden somewhere in there, if the model cannot practically extract the insight because of their sizes/disorganization vs the computational/storage capacity, this too would mean they are not better data.
Of course you can make the argument that some of the sensors are unnecessary, but when one fleet has had millions of vehicles for years and isn’t working, and one started with dozens, has recently grown to one thousand vehicles, and is working, the evidence is not in support of the argument.
Waymo was able to do this with less miles. How much data does Tesla really need at this point? Assume you have all the data in the world that you could ever possibly want. How much of that can you really compress into a car for real FSD?
Tesla was supposed to have what they needed when they released the Model 3. Then they had to upgrade the cameras and CPU which meant they had to re train. Then they re-wrote, so again retrain. Now it's new cameras and compute again. Cycle repeats.
How over-fitted are their models to the cameras? I'd expect a layered architecture where a sensor layer does object-recognition and classification and then hands over this representation of the world to a higher-level planning model. You should have to retrain the whole stack for camera revisions - hell that's how it would work across car models with their different camera angles.
There are some "where" issues with Tesla too. I have an intersection where it consistently can't tell that its view is obstructed. It'll just yolo into the intersection then pause (after pulling out into the lane) when it realizes that it wasn't actually able to see. Its consistent behavior, and seems to be a flaw with obstruction detection.
I might argue that every traffic light is sort of a where too. Mystery meat yellow light handling is scarily bad.
Waymo vs Tesla definitely smells like bitter lesson to me yes, 100%. With Waymo being on the bitter side, to be clear. Future will tell if the intuition is right on this one
FWIW, Waymo has more cameras than a Tesla. Both companies are removing sensors over time. In some ways removing sensors is easier to prove out with real-life data than adding them. I think it is going to be fascinating to see how it plays out.
Tesla added back the radar and improved the cameras in HW4. My guess is that ultimately they'll converge to a similarly capable sensor/compute suite with Tesla improving theirs and Waymo paring down.
Well, one thing is that many of us rarely take taxis. (Aside from reserved private cars to the airport now and then.) I'm unconvinced that self-driving changes the equation enough for most of us. I do have a trip coming up that 50% cheaper Uber might lead me to not rent a car but that's rare.
Car ownership is pretty high in a lot of places. It's still pretty much central urban--lower ownership, harder to re-find a parking spot--vs. everywhere else. Taxis may be more common in some places but there are still a lot of privately owned cars and taking taxis or having drivers is really not the norm in most places.
Training data is trivial to collect. Betting on Tesla because they have more training data than Waymo is like betting on Roscosmos because they have more employees than SpaceX.
Tesla FSD will never catch up to Waymo until they switch to LIDAR and have human assistance when the vehicle gets into complicated scenarios such as emergency vehicles blocking the road and redirecting traffic.
Uhm, we already have FSDs, both the USA and China, just not the Tesla FSD. China is running auto taxis in a few limited areas with full setups that rely on LIDAR, and I hear they are pretty good.
