>> “It’s really, really hard,” Krafcik said during a live-streamed tech conference. “You don’t know what you don’t know until you’re actually in there and trying to do things.”
Now, where was that Rodney Brooks interview? Ah, here it is:
>> Rob Reid: (...) Why do you think these people and others are overestimating the rate of development in this field?
>> Rodney Brooks: I think they're making a bunch of mistakes. I asked them when did the first car drive down a freeway for 10 miles at 50 miles an hour. They know that the Google cars did that in 2004 or 2005. It was actually done in Germany in 1987.
>> Rob Reid: Wow.
>> Rodney Brooks: When are we going to get the first car, hands off the steering wheel, feet off the pedals, drive coast to coast in the US? Yeah, well, it actually happened in 1995 with the Navlab Project from Carnegie Mellon University. My point is, everyone thinks, oh this is just a [inaudible 00:44:50], this is going to happen quickly. It's been around a long time to get to where we are. I have now demonstrated to them that their scale is wrong, their start point is wrong. It has taken a lot longer to get to where we are now.
So, to anyone who had any understanding of the technology it must have been obvious for a long, long time that "it's really, really hard" and that it wouldn't just take a few years after the time that Google announced the Google car. I struggle to believe that Krafcik is not one of those people, or that major automotive company CEOs are not.
Basically, those people have been bullshitting everyone and they're still bullshitting everyone, and they were probably not even interested in developing self-driving cars in the first place, it was all just some stupid marketing game supported by a very excitable tech press and a gullible public.
Rodney Brooks is misleading. He says things like, "It was actually done in Germany in 1987." but neglects to mention that the road had no other cars on it.[1] He also claims that the first autonomous coast to coast drive happened in 1995, but actually the project was autonomously controlling steering, not gas or brakes, and 150 miles of the trip were driven by humans.[2]
Modern autonomous vehicles are much more impressive. They were successfully navigating urban environments 12 years ago.[3] Waymo's cars have driven over 10 million miles and disengagement rate is once every 11,000 miles.[4] We're at the point where no major breakthroughs are needed, just incremental improvements. That's what's different from earlier eras of autonomous vehicles.
> In the 1980s, a vision-guided Mercedes-Benz robotic van, designed by Ernst Dickmanns and his team at the Bundeswehr University Munich in Munich, Germany, achieved a speed of 39 miles per hour (63 km/h) on streets without traffic.
Think about what that means. Waymo has been doing this for many years, drives in basically ideal conditions (Phoenix rather than Philadelphia), and still disengages at a rate that amounts to once a year for a typical personal vehicle. That’s not enough for “real self driving” because at that disengagement rate the human must be actively engaged the whole time. Human drivers go about 500,000 miles between crashes. (And that’s not 500,000 miles driving through Phoenix. That includes miles driven through places like DC where freeways have no acceleration lanes. That includes drunk drivers and teen drivers. You can’t control the other people on the road, but if you don’t yourself drive distracted, drunk, speed, etc., I’d bet you can expect to go at least a million miles between crashes.) Disengagement rates would have to improve by a factor of 50 to allow a human to not be paying attention at all times while achieving an acceptable level of safety.
A disengagement doesn't necessarily mean that the car would have crashed. There are amusing disengagement stories such as a cyclist doing a track stand, causing the car to get stuck.[1] Many disengagements are false positives. Think of how often you've had to do the equivalent to human drivers by telling them to slow down or watch out. For me it's certainly more often than every 11,000 miles.
Given that humans aren't great drivers, you'd think that after 10 million miles Waymo would be at fault for some crashes. But only one of Waymo's crashes was even partially their fault. One of their cars was moving at 2mph to get around some sandbags in the road and hit a muni bus that was trying to squeeze by at 15mph.[2] Waymo has since tweaked their software to account for aggressive bus drivers. That's over 10 million miles and only one collision that was even partially their fault. That sounds pretty safe to me.
And regarding weather: Though their pilot program is in Phoenix, Waymo doesn't just drive in places with nice weather. They've been testing in Michigan for the past 2 winters.
A disengagement generally measures when a human test driver had to take control. It’s not just telling a human driver to watch out—it’s taking the wheel from them. They wouldn’t necessarily lead to a crash, but there is a pretty good chance they would. If even 10% of disengagement’s would’ve led to a collision, you’re still not close to a good human driver.
One crash in 10 million miles isn’t as great as it sounds. First, it’s a meaningless number because a human is intervening every 11,000 miles. It’s not a true measurement of what a purely autonomous collision rate would be. Second, humans crash once in every 500,000 miles, and that’s under the full gamut of circumstances (drunk drivers, unfamiliar roads, teenagers, etc). Waymo is running with trained drivers on thoroughly mapped test areas in a place with easy traffic and weather. You’d expect humans doing nothing but running the same routes over and over in that carefully geofenced area to do better than one collision per 500,000 miles. (Especially with someone looking over their shoulder, like the self driving car is doing!)
>> A disengagement doesn't necessarily mean that the car would have crashed.
Conversely, lack of disengagement doesn't mean that the car is driving safely. There is simply no way to know how close to an accident a car came, without the human driver having to take control.
Like I say above, disengagements don't really tell us anything about the car's real world driving ability. They're just a silly proxy mandated by bureaucracy, and only a very weak measure of real progress.
Yes, of course there has been progress since the '80s and '90s. Things would be really bad otherwise.
>> Modern autonomous vehicles are much more impressive.
It really depends on what you consider impressive. The DARPA Grand Challenge involved one road loop with stunt drivers instead of real traffic. These are still strictly controlled, laboratory conditions that tell us nothing about the ability of robot cars to operate in the real world.
Waymo's disengagement rates don't really say anything, either. Perhaps Waymo is now driving its cars in easier conditions after noticing that they tended to disengage too often. What we know for sure is that Waymo doesn't have autonomous cars -as noone else does. If they did, they'd be out on the streets without safety drivers and counting autonomous miles, not miles without disengagement.
According to the post you link, reporting rate of disengagement is required, but the fact that Waymo chooses to advertise theirs as a measure of improvement of their cars tells me that they have no real results to show and instead choose to tout a meaningless proxy just to make people believe that they are further ahead on the road to autonomy than they really are.
> the fact that Waymo chooses to advertise theirs as a measure of improvement of their cars tells me that they have no real results to show
It tells me that's the weakest number they can possibly report. If I were Google and I knew I had the strongest ML teams in the world by miles, the strongest internal results by miles, I would say as little as possible for as long as possible. Get as far ahead as possible.
I think the Alphabet board learned their lesson on announcing early. They still shut down products, of course, so does Intel, Facebook, and every other company. And I think they're learning their lessons about sales (Cloud's hiring 10k sales people) and customer support (I'm sure they're painfully aware of the issues).
Btw, this is from the same source as your link no 1. above ("Prof. Schmidhuber's highlights of robot car history"):
>> 1995: UniBW Munich's fast Mercedes robot does 1000 autonomous miles on the highway - in traffic - no GPS!
>> Dickmanns' famous S-class car autonomously drives 1678 km on public Autobahns from Munich to Denmark and back, up to 158 km without human intervention, at up to 180 km/h, automatically passing other cars
A most impressive result that is easily the equal of modern results- but in 1995. That puts your claim that "incremental improvements" are all that's needed, in perspective. Major breakthroughs are needed.
The 1995 result was nowhere close to what we have today. 158km was the maximum distance between disengagements. Waymo's average distance between disengagements is over 100x that, and they're going on more than just highways.
>> 158km was the maximum distance between disengagements.
That was 158km doing 180 km/h on an authobahn with no upper speed limit and with unrestricted traffic.
Anyway, like I say in my other comment Waymo's disengagements mean nothing because, unlike Dickmann's authobahn experiment, there is noone there watching the performance of their cars, other than Waymo employees. As far as anyone can tell, their impressive disengagement record is the result of their cars being driven in the mildest, friendliest conditions possible. It certainly seems that way, taking into account where they drive their cars - in sunny, peaceful Phoenix AZ, and then again, only on roads they've actually mapped.
Put these two things together and it's obvious that Dickmann's experiments were run in as close to real-world conditions as possible, whereas Waymo is consistently keeping its cars in closed, controlled, simple environments that tell us nothing about their capability in the real world.
But they're still using easy environments. Not sure a German motorway without speed limits is easier to navigate than what Waymo faces.
I doubt that maximizing the miles between disengagements should be our goal. The goal should be for the car to face the worst conditions imaginable (snow, ice, dirt roads, other drivers ignoring traffic) and somehow manage to survive in those situations.
A German motorway without traffic is very easy to navigate, but a typical day to day situation involves several kinds of cars driving at different speed limits and engaging in various maneuvers like overtaking, exiting, merging, switching lanes. There's also traffic jams or heavy traffic situations.
If one wants to drive dynamically, one has to overtake and switch lanes quite a lot, which makes this challenging. If one is content with driving like a snail they can stick to the first lane, which is pretty simple and could be managed even by a so-called self-driving car.
The usual roads are probably very easy, they have wide markings. The problem there arises with repair works which mess up the markings and lane width in all possible ways. During summer they are very frequent, and I bet they were the cause of human interventions in those old experiments.
No problem, disengage there. The problem seems to br no safe way to disengage.
Tesla crashes kill people because of this. (Ding ding, you have 1 second before impact.) Waymo probably wants to nail city driving first, because it's much lower speed, safer.
A limited access road is absolutely easier to navigate than a city. Once you can stay in one lane with sufficient following distance, you're done. The problem space is tiny.
If you have a lane. A gravel road with two way traffic (not that uncommon in rural areas) only works because drivers communicate their intentions (esp if one needs to wait at a point where the road is wider). They don't work by fixed rules.
Or nothing is needed other than cranking up the safety factor. Let me read a book while driving and if anything is out of the truly ordinary start to slow down. Much better than what Tesla does (keep velocity and signal the human godspeed, what could go wrong!?)
I don't think his point is that autonomous vehicles haven't made any progress, rather the rate of progress has been pretty slow if you adjust the start point to the 80's/90's rather than the last 10 years or so that the public usually thinks of. Of course, the rate of progress isn't necessarily linear, especially given the rapid advancement in machine learning, so there's no reason at all to assume any further progress here on out will take just as long. Even so, I don't know if it has been demonstrated adequately if AV's perform just as well (if not better) than humans, given the vast, vast variety of unideal situations human drivers have been subjected to over the past century.
Your point reminds me a bit of Theranos, and how they were able to coast on a completely fraudulent but awe-inspiring idea.
It might not be related, but whenever I read stories this, I'm reminded of the ways that tech is marketed in the world. It's impossible for the public to understand whether or not a certain technology is feasible, practical, or even possible, but marketing teams get an unbelievable amount of leeway when marketing products and services. And they get to do it without really telling you what data is collected and how it's used, etc., etc.
The power asymmetry between what tech companies are allowed to say versus the limited technical understanding of the public is brutal, and not getting any better.
Perhaps not the general public, but everyone in the clinical lab industry knew that there was no way that Theranos could achieve accurate results with a tiny blood sample. A single drop of blood extracted from just under the skin is not representative of the blood in the patient's circulatory system and contains too many contaminants. This is fairly straightforward biology and has been know for many years.
True. Still, Theranos happened and flew fir quite a while. The problem here is the smaller the population of people able to judge new tech (which is generally speaking getting smaller everyday tech becomes more specialized and advanced) the longer it takes for reality to catch up with the money.
Which also means that it is ny impossible to distinguish between a growth company with a solid product and one that is just trying to out run reality.
But I read on these very forums, by prominent posters, that the only reason we were skeptical of Theranos was that we didn't want to see a young woman succeed! What happened?
Having bold dreams are important too. Trying hard and failing is a perfectly useful data point. Pretty sure there would have been many naysayers 20 years ago, when presented with what is today's mobile technology.
I don't think they're the same thing though. Touchscreen phones with high speed internet was an unsurprising goal, even if the pace of smartphone adoption has been fantastic.
Driverless cars... unless there have been some fundamental breakthroughs in AI tech that allows for such a fully unsupervised system, its hard to see how this can be a possibility.
Now, reducing the complexity far more... assisted driving tech is already pretty mainstream. Autonomous driving for predictable, long haul routes (inter-city trucks on US highways) is an exciting market too.
Everyone is wrong about long haul trucks, frankly. It will be easier to get fully autonomous cars than trucks. They're much longer and wider. They're at least twenty times heavier. They require much more room to maneuver, to start, and to stop. If they're involved in a crash, they cause a lot more damage.
Not to mention that there's nothing really predictable about a long route. Traffic, weather, construction, and every other variable is more likely to change over a longer route as well. It would be far better to focus on making autonomous cars first.
All those extra difficulties of long haul relative to cars are big challenges to humans because the scale is so far off from the baseline of our embodied intelligence, but not much of a difference to machines.
A human driver eyeballing a difficult curve will easily be half a meter or more off over the length the trailer. But for a machine it it does not really matter wether it plots a path for a Twizzy through the LIDAR point cloud or for a semi-trailer, as long as the model is accurate. Humans have all their relevant sensors at a single point, awkwardly mapped to vehicle dimensions with mirrors and guesswork, therefore human driving gets worse with increasing vehicle size. A driving machine however can take input from all over its body, its "skilll does not deteriorate with increase in vehicle size (arguably it might even improve because a bigger vehicle will have more computing and a wider range of sensors at the same fraction of total mass and cost). The bigger the rig the easier it becomes for robots to compete with humans.
It's not that trucks will have it first, per se. It's that trucks spend a much larger fraction of their time on freeways, so they can get a much bigger benefit from a system that only works there.
Specifically on freeways, the difference in difficulty is pretty minor. The lanes are wide and you don't need to accelerate very rapidly.
> It would be far better to focus on making autonomous cars first.
Mu. The same system's going to be on both types of vehicle.
In 1999 we had all the basic ingredients for a modern smartphone. The components were too slow, expensive, heavy, power hungry, and unreliable to allow for building a viable consumer product but no one really claimed that improvements were impossible.
My smarthphone has issues sometimes: no mobile data, or no GPS, or a Bluetooth-device fails to connect, or an outright crash. Not very often, perhaps once a month. Not too big a deal for a phone: I can simply can reboot it.
If an autonomous car has issues even 1/10 as frequently, I won't ever trust it to transport me.
Now, where was that Rodney Brooks interview? Ah, here it is:
https://cdn.arstechnica.net/wp-content/uploads/2018/06/2nd-P...
>> Rob Reid: (...) Why do you think these people and others are overestimating the rate of development in this field?
>> Rodney Brooks: I think they're making a bunch of mistakes. I asked them when did the first car drive down a freeway for 10 miles at 50 miles an hour. They know that the Google cars did that in 2004 or 2005. It was actually done in Germany in 1987.
>> Rob Reid: Wow.
>> Rodney Brooks: When are we going to get the first car, hands off the steering wheel, feet off the pedals, drive coast to coast in the US? Yeah, well, it actually happened in 1995 with the Navlab Project from Carnegie Mellon University. My point is, everyone thinks, oh this is just a [inaudible 00:44:50], this is going to happen quickly. It's been around a long time to get to where we are. I have now demonstrated to them that their scale is wrong, their start point is wrong. It has taken a lot longer to get to where we are now.
So, to anyone who had any understanding of the technology it must have been obvious for a long, long time that "it's really, really hard" and that it wouldn't just take a few years after the time that Google announced the Google car. I struggle to believe that Krafcik is not one of those people, or that major automotive company CEOs are not.
Basically, those people have been bullshitting everyone and they're still bullshitting everyone, and they were probably not even interested in developing self-driving cars in the first place, it was all just some stupid marketing game supported by a very excitable tech press and a gullible public.