Driverless cars are coming along just fine. Waymo is making steady progress. The sensors are getting better. The problem comes from all those "fake it til you make it" startups, Uber and Tesla being the worst. Both have killed people.
This is mostly about sensors and geometry. Machine learning has a role, but only in target identification. That's how Waymo does it. The fake it til you make it crowd had the fantasy that you just hook up some cameras to a machine learning system, train it, and you have self driving. Doesn't work. Machine learning is way too dumb.
You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning. That's just used to guess what they're going to do next. It's not used to decide if they're an obstacle. Obstacle detection and avoidance is all sensors and geometry.
Also, "self driving car", "electric car", and "transportation as a service" are all independent. All will be available, but not from the same companies.
I am curious why you believe this to be the case? Driverless cars have yet to even come close to being workable in adverse conditions, to my knowledge, please correct me if I am wrong.
> This is mostly about sensors and geometry.
And mostly about the limitations of sensors, and the limitation of available algorithms to overcome geometry. A algorithm a driverless car uses to overcome some geographical feature might expect something to be spherical, but in reality, it ends up being elliptical, only it is too late for the car to adjust, for example, or vice versa. There is literally hundreds of thousands of potential corner cases out there. The earth in itself is a good example: although many people try to do distance calculations with lat/long and some standard radius are usually off by n precision points because the earth isn't perfectly spherical, only approximately. Driverless cars have to be precise. A couple points off might spell the difference between safely driving in the lanes, and veering into a ditch, off a cliff, or into a median or obstacle.
Sensors will suffer some of the same problems (or different problems) as our biological sensors do. How will road signs, lines, and likewise be detected in adverse conditions? Snow? How will radar overcome natural geographical corner reflectors?
Driverless cars seem to becoming along just fine in perfect conditions.
Not trying to be defeatist, but I believe if we want true driverless technology, the infrastructure will have to support the vehicles for these edge cases that we cannot overcome. Or we can continue to be idealists. I for one wish we never gave up on trains -- they are the perfect "driverless" technology candidate.
I think interesting edge cases include:
'empty cardboard box or log?'
'Deer just crossed road, is there another one close behind?'
'Driving temporarily on the wrong side of the street due to construction or a downed tree limb'
'Police directing traffic'
'Driving on wrong side of road to avoid collision'
'One lane bridges'
'Busy parking garage with blind corners'
'City Bus driver forces themselves recklessly into your lane'
'Other driver in round about about to cut you off'
'Pulling out to cross a busy 4 line highway with no median or traffic signal'
Not to mention, any snow on the road is going to make it supremely hard for a computer to determine where their lane is, or even the road is.
Driverless cars have advantages over humans too. Faster reaction speed, constant 360 degree surveillance, lack of distraction, (theoretically) better control of brakes and steering to handle skids.
Waymo has demonstrated solutions for many of the edge cases you mention. This video is from 3 years ago:
https://youtu.be/tiwVMrTLUWg?t=530
Regarding snow, it maybe a difficult problem, but if cars can't see road markings, neither can humans, so how do they do it? Sometimes by following a car in front. Though far from real autonomy, my Tesla doesn't need to see road markings for autopilot to work, it will fall back to following the car in front.
And.. Why does Waymo have to solve this inclement weather problem now? Surely it would be better to demonstrate safety in good weather, then light rain, then heavy rain, then light snow? They can just refuse to operate in bad weather unless they are confident about it.
Weather and trips being not completely predictable, the car would have to be able to pull over and stop if there was weather the car wasn't certified to handle, and if the human was asleep in the back seat or whatever and took a long time to get ready to take over.
I think I've seen at least a prototype Waymo car (it was exhibited in the Computer History Museum) that was designed without the steering wheel and pedals for a human to use. That wouldn't work so well given that the car might pull over and be unable/unwilling to drive anymore. (Maybe you can put an expected upper limit on how long the weather will remain bad ... Nah, storms can last for days, by which point a human who didn't bring food and water could be in bad shape.) I guess you could rely on being able to call AAA. Though a bad blizzard might be exactly the case where AAA would have a hard time reaching you. The human being able to take over eventually seems like an important feature. I guess that is the way all the cars in the field (that I've seen) work.
Does anyone happen to know if self-driving cars are practicing "pull over and stop" maneuvers? For some reason I've never heard of it. I think it is the only potentially reliable fallback mechanism if the car encounters, say, weird terrain it knows it can't handle. (I don't think you can assume the human will be able to respond within n seconds.)
> I think I've seen at least a prototype Waymo car (it was exhibited in the Computer History Museum) that was designed without the steering wheel and pedals for a human to use. That wouldn't work so well given that the car might pull over and be unable/unwilling to drive anymore.
It'd be fine - you just need to have some backup option. A small joystick or two behind some panel, or screen control, or perhaps you control the car with a phone app. It's like having an emergency spare tire - you just need a minimal driving UI that can be used in case of emergencies but users otherwise don't need to see or deal with. It can be inconvenient and speed-limited, since you don't expect to use it much.
Though if there's decent connectivity an obvious intermediate option is remote operation. Some human who is really good at driving might take over for a bit, driving your car from the comfort of their own home or office if you're not comfortable doing so yourself using the backup control pad.
Other edge cases include: Amish buggies, rotaries in Boston, Syracuse's upside down traffic light (green is on top), etc. The possibilities are endless; how can you test them all? Humans are really good about adapting to novel situations on the fly, not so much computers.
I mean, you are right about humans as a species, but oh god, not as drivers. As a cyclist commuter, pass/get passed by a lot of cars and see a lot of irregular/irrational behavior. Everytime there is a change in the traffic rules along my route (detour, construction, closed lane, new signalling) you will get a pretty high rate of people who either ignore the change, panic and drive recklessly, or panic and come to a confused stop.
Maybe we need driverless cars that can show panic faces when they don't know what to do and be coached by a friendly citizen what to do? It would be super cute.
Agree. It's a fun game to think up edge cases that would challenge a self-driving car. On average these cars will far outperform human drivers. I see human drivers blow through stop signs every day completely unaware that they did so.
One approach would be to record 100-to-1000 trials of how human drivers navigate each particular edge case in vehicles instrumented for autonomous driving.
Sadly, no one seems to have figured out a way to economically motivate human drivers to do this.
Isn't this part of what Tesla has been doing though? At least they sell cars that simultaneously has:
- human drivers in demanding situations
- sensor and compute package planned for autonomous driving
From there it is mostly a question of
1. getting permissions to collect the data
2. finding some efficient way to store -> sift for interesting situations -> magic happens here -> lots of regression testing -> self driving car -> profit!
I think it comes down to being able to model the world around us, having a model for human behavior, animal behavior, etc. If we see a baby deer, we look for the mother deer.
It feels like we're also really good at creating multiple open-ended stimulations in the back of our mind about how things might play out, where they can easily be paused or fleshed out depending on which became more probable or if we want to learn something. It's kind of a running background process.
30,000 deaths per year suggest that humans fail at these edge cases all the time. Maybe ate their best a human outperforms a machine but as any person who drives if other drivers are at their best.
I think it's still close to the most likely cause of violent death for an American; Neck and neck with gun deaths, if you count the self-inflicted.
I mean yeah, compared to medieval statistics, it's great, but in comparison to the other non-medical ways to die you face as a 21st century American? automotive fatalities are quite high, and the problem deserves a lot of focus.
(I mean, I agree that reducing miles driven is also a good goal. I'm just saying, making safer cars is a lot easier than talking people into allowing higher density construction and cities built around transit and walking rather than around cars)
Or, judging by traffic's constant deaths ... Their don't.
Anyone who's seen a Waymo car drive around the valley knows they're much safer than human drivers. They're annoyingly good, because for instance they just never miss a bike and are careful around them, and if you can't tell why it's a bit annoying.
But I've always come away from such incidents with a feeling of "I should have seen that". I've yet to see them screw up even once.
And yet you can't drive from SF to San Jose without seeing a human driver screw up.
> And yet you can't drive from SF to San Jose without seeing a human driver screw up.
I don't think anyone is debating that in perfect conditions the computer cars can sometimes out perform the worst drivers.
If your concern is terrible drivers killing themselves and others, what you should be arguing for is much stricter standards for obtaining a driver's license. Probably removing 'full coverage' insurance and only allowing liability would go a long way as well. Can't keep wrecking your vehicle if nobody's buying you a new one.
>If your concern is terrible drivers killing themselves and others, what you should be arguing for is much stricter standards for obtaining a driver's license.
Or for keeping a drivers license.
>Probably removing 'full coverage' insurance and only allowing liability would go a long way as well. Can't keep wrecking your vehicle if nobody's buying you a new one.
I disagree... a used car is pretty cheap. Cheaper than full coverage, if you have a bad record.
I think this should be attacked by increasing the minimum liability coverage. right now, in California, you can drive with homeopathic levels of liability insurance... $35K isn't going to cover very much hospital time/time off work if you hit someone who has a good job. The minimum liability coverage should be 2-3 orders of magnitude higher.
Of course, for either of these things to be politically possible, we first need a society where it's reasonable to get from A to B without a car. An idea that is fought against daily even in relatively dense places like where I am now.
Furthermore self-driving cars are at this point ONLY driving through areas with a lot of pedestrians. You'd expect them, therefore, to have much higher accident fatalities than normal vehicles. Why ? They're always around pedestrians. Instead, in the first years of operation, they're safer than humans.
Even with Uber's less than stellar safety practices, and Tesla's ... well ... how do I put this politely ? [1] seems a good link. Let's just say Tesla owners could be more careful, especially since they signed a contract stating that they would be more careful (and youtube has much worse than that video). Given that that's how people use self-driving cars I would argue that's pretty damning for human driving skills.
Not sure what your point is. That graph shows about 10 deaths per billion VMT, which is exactly the number I stated. It is a completely unfounded assertion that they are safer than humans.
You forgot ‘A woman in an electric wheelchair chasing a duck with a broom’ and ‘people playing frogger on roads’.
And Waymo self driving car didn’t seem to have a problem with that.
Things like snow aren’t necessarily a problem in the beginning because you can start by selling a self driving car that doesn’t work in the snow. There’s still a market for it.
I think we need to keep our expectations realistic. Most of those would challenge a significant portion of human drivers (and the scenarios suggested by sibling commenters are even more likely to cause a human to crash), and it's perfectly acceptable for a human driver to say "X crazy thing happened causing me to crash. What the fk?"
Except us humans drive in the middle of the street in residential areas often below the posted speed limit just for this reason. And if we live on this street, we can better anticipate the conditions.
I've seen this multiple times as a situation that people can deal with instinctively but computers won't. However people need to be trained to handle this situation; it is explicitly mentioned in the driver's handbook.† So I don't see this as a "win" for people over computers.
> Not to mention, any snow on the road is going to make it supremely hard for a computer to determine where their lane is, or even the road is.
HD mapping allows cars to know precisely where they are on the road even if they cannot see the lane markings below. In fact, georeferenced HD maps can pinpoint the car's location in the world down to less than 10cm of absolute precision (as opposed to relative precision)
These are tough issues, but they're probably not all relevant in the suburban Phoenix area where Waymo is getting started. Maybe it rolls out one city at a time for many years and that's okay?
I would add some more edge cases - driving a street in Delhi or Bangkok. Or navigating small Italian town where streets layout had been designed circa 12th century.
The infrastructure driverless vehicles rely on is their own internal maps, which have lanes and signage marked out. Being able to visually detect these things is important, but it is a measure for added redundancy.
Great strides have been made in using machine learning to filter out obscurants such as snow. Perception for autonomous vehicles is effectively a solved problem.
The biggest technical challenges are related to planning. So say you're approaching an intersection. There is a pedestrian about to cross, a cyclist in front of you and another vehicle waiting to turn left across your path. As a human, you understand that if you behave one way, it will cause the pedestrian, the cyclist and the other car to respond a certain way, but if you respond to the situation another way, it will cause all three to respond differently.
Our ability to game out scenarios like this is intuitive, but for AI to predict how it's behavior as an agent will influence the behaviour of other agents on the road is a daunting undertaking, particularly when taking into account the full scope of scenarios that need to be mastered before an autonomous can reliably safely navigate anywhere.
> Great strides have been made in using machine learning to filter out obscurants such as snow. Perception for autonomous vehicles is effectively a solved problem.
Great strides is not 'perfected' and I don't think perception for autonomous vehicles is a solved problem whatsoever. What is a driverless car to do if it slides out of position on the road and is now facing the wrong direction? Does it have the ability to know whether it needs to call for help, can safely maneuver, it's occupants are in immediate danger and should exit the vehicle (or not exit the vehicle)?
The two key aspects of an autonomous OS are perception and planning. Being able to "see" well enough during a flurry is a perception problem. Knowing whether to maneuver out of it or call for help after spinning out is a planning problem. There are many planning problems left to address and master before autonomous vehicles are ready for widespread adoption. Some planning problems are unique to specific intersections, and dedicated software has to be written just for that intersection, like the intersection of Market and Castro, in SF, for instance.
Can they perceive where on the road they should be located when the road is totally covered in snow and you can't see the pavement, let alone the line markets, possibly only tire tracks, if that?
Yes. An autonomous vehicle with lidar and maps can locate itself using any landmark, or series of landmarks it can see, it isn't limited to lane markings.
Just think, the remains of the last self-driving car will help the next self-driving car avoid the trap. But only if Google carefully catalogs it and no one moves the wreckage.
You can't reliably know the distance from pavement to any of those things unless you plan on indexing every physical object along every roadway.
I think the most likely scenario is self driving cars won't drive in those conditions, hopefully those conditions don't develop while you're on the roadways or you'll be parked somewhere cold.
They do index everything, the maps they rely on are lidar generated 3D point cloud fields that make a model of everything around the road, and are frequently updated.
The goal isn't perfection. The goal is to be as good as humans.
Eg: An autonomous vehicle driving through snow backed by millions of miles of experience driving in snow is better than someone from the tropics driving through snow for the first time.
> Perception for autonomous vehicles is effectively a solved problem.
The problem is that you can't separate "perception" from "cognition". A human could drive a car reasonably well via a webcam feed, so does a webcam count as "solved perception"?
"Perception" in the context of autonomous agents means a mapping from sensors to a model of the world; how effectively can the agent establish a reliable model given its sensor readings?
What GP means by perception being a solved problem is that existing sensors and algorithms produce high quality and reliable models in a wide range of environment conditions.
A webcam is a sensor device, the human observing the webcam feed most likely cannot construct a good model of the car and its surrounds, as they can't do things like shoulder checking or looking in the rear view mirror, which a good driver does frequently to maintain a model of where other cars are.
But then "reasonably well" for a human driving a car remotely via webcam feed is likely to be a far lower standard than we're holding self-driving cars to.
As a human, you understand that if you behave one way, it will cause the pedestrian, the cyclist and the other car to respond a certain way, but if you respond to the situation another way, it will cause all three to respond differently.
Why does the self driving car have to restrict itself to extremely subtle human nonverbal communication? Just put a loudspeaker on the outside of the car and have it announce its intensions clearly, yielding to pedestrians/bicycles according to the laws of the land.
> yet to even come close to being workable in adverse conditions, to my knowledge, please correct me if I am wrong.
There's some video here for:
>“The Yandex.Taxi autonomous car safely navigated the streets of Moscow after a recent snowstorm managing interactions with traffic, pedestrians, parked vehicles and other road hazards on snowy and icy streets,” https://www.theverge.com/2018/2/16/17020096/self-driving-car...
Presumably it's not perfect but it seems to be coming along. Snow and ice covered Moscow is more adverse than what I usually drive.
> come close to being workable in adverse conditions
Given how people drive in the rain and snow in the Northeast, I would argue human drivers have not even come close to being workable in adverse conditions.
We drive in them anyway, despite often times magnitudes more risk of crashing, because we want to.
I see this fallacious argument made as a counterpoint time and time again and it is getting tiresome.
If you look at all the relative statistics, both IIHS and insurance, the drivers who practice safe driving techniques and do not drive distracted have something crazy like a 3-4 fold lower accident rate. Moreover, those drivers who have had an accident are much more likely to have another one. Have you ever met someone who has gone their entire life without an accident? They exist, I encourage you to speak to them about how they drive -- more often than not it isn't by...accident (sorry)
The other point I am making here -- the drivers who do account for reckless, endangering driving, or who are careless by some measure of frequency (not careless as a whole, but maybe they forgot to change to their winter tires and properly inflate them?) -- they tend to pay the price the most. Their insurance rates are higher, they get tickets and points, and eventually the worst ones aren't allowed to drive at all.
When the "worst" AI's that are responsible for some amount of crashes, who is going to pay the price? Whose license is going to get deducted? Whose insurance is going to go up? In the world of driverless ubiquity, who is going to be the check and balance? What self-selecting mechanisms are going to protect us? You think Waymo will give a shit?
There are other reasons this argument is fallacious, the most obvious one that driverless cars have not yet proven they are safer or can remain statistically significantly safer than safe human drivers. How do we know driverless cars cannot or won't be compromised? What if a foreign nation state deploys an attack that exploits a known weakness? What if a car company is infiltrated by a bad actor and uses bad training data? We were able to break into a country's nuclear reactor. Russians were able to break into our democracy. I imagine this would be a nice juicy target for a country that really doesn't like us. Ect. Ect. It is going to come with a whole host of it's own unique problems, so comparing them to current human driving problems (which have potential solutions that our government won't embark on -- different story for a different day) generally won't be fruitful.
>the drivers who practice safe driving techniques and do not drive distracted have something crazy like a 3-4 fold lower
That's quite the qualifier. Problem is I see at least 3 people with their eyes on their phone during every 30min commute to work ...so...
>When the "worst" AI's that are responsible for some amount of crashes, who is going to pay the price? Whose license is going to get deducted? Whose insurance is going to go up? In the world of driverless ubiquity, who is going to be the check and balance? What self-selecting mechanisms are going to protect us? You think Waymo will give a shit?
These are literally the least difficult issues around self driving cars.
> There are other reasons this argument is fallacious, the most obvious one that driverless cars have not yet proven they are safer or can remain statistically significantly safer than safe human drivers.
> These are literally the least difficult issues around self driving cars.
You are either young, or extremely naive (or both) if you don't think these are going to be challenging problems.
> so we should stop trying?
Not sure why you thought that this begged that question. What I am saying is we should stop making arguments that compare driverless car habits, problems, and safety to the current habits, problems, and safety of human drivers. They are generally bad arguments. They won't bear any fruit. Statistics aren't people. Trying to sell a generation on driverless cars on some unproven projection that "they will be X times safer!" will fall on deaf ears to drivers who have made it a lifetime of safe driving.
> if you don't think these are going to be challenging problems.
are they show stoppers? c'mon assessing risk is old as the hills. There's an entire profession that is devoted to assessing and pricing in risk. With regard to liability, the courts will decide. It'll be messy but it'll get sorted out in time.
>Trying to sell a generation on driverless cars on some unproven projection that "they will be X times safer!" will fall on deaf ears to drivers who have made it a lifetime of safe driving.
people will get over their fear in time. People feared cars when first introduced too.
"With all the anxiety around driverless cars lately, it’s worth remembering there was a time people worried about cars exactly because they had human drivers. In fact, it was the removal of the horses—the horseless carriage—that gave some people fits.
In the 1890s, the prospect of a person driving without the aid of a second intelligence was a real concern. A horse, or team of horses, acted as a crude form of cruise control and collision aversion.
In 1896 Alfred Sennett warned, “We should not overlook the fact that the driving of a horseless carriage calls for a larger amount of attention for he has not the advantage of the intelligence of the horse in shaping his path, and it is consequently incumbent upon him to be ever watchful of the course his vehicle is taking.”
Also, the lack of support for harder environment isn't because they're impossible, but rather because they are focusing on getting it perfect in normal environments before expanding. The person said they are "coming along fine", not that they are done.
Also, the lack of support for harder environment isn't because they're impossible, but rather because they are focusing on getting it perfect in normal environments before expanding.
I beg to differ.
I claim that adverse environments are very hard, even pathological problems and placid driving in well laid out suburban road with generally well behaved drivers are merely hard problems.
The thing is that an engineering team working on a problem like self-driving in adverse conditions is always going to be making some progress. The main question is whether they are going to make the kind of progress that justifies the hefty expenses involved.
anyone have any idea of how frequently horse-drawn carriages crashed in dense urban inner city environments 120 years ago normalized against the incidence of crashes for contemporary cars on the same streets at the same speeds?
Maybe this could form the basis for a kind Turing test for level 1-4 autonomous Vehicles.
Fundamentally, if a human can drive a car with nothing but two relatively poor eyes with a pretty small field of vision set in a single location inside the vehicle, an AI can be trained to drive using the same inputs - any more sensors are a bonus.
The other thing people forget is the bar isn't that high: self driving vehicles don't have to be perfect, they just have to be better than humans are. All of the "whatabout" edge cases people proffer as examples of areas an AI would have trouble with, people have trouble with too. The difference is that once an AI learns to solve that edge case, it doesn't have to relearn going forward.
No one thinks that you just hook up ML to a camera and you're done. Literally everyone working on this only uses ML for identification. When that Model X crashed into a highway divider, it was because the lines on the road were very faint and there was a fork in the line that actually wasn't the _real_ lane line. The car followed that by mistake, but only because of the misidentification of the lane line.
How are more sensors going to tell the difference between a plastic bag and a cat? How does lidar tell you which car is parked on the side of the road and which one is in your path? Relying on a dozen sensors seems like the crutch to me. Nothing about our current world has been designed for lidar and radar. It was designed for binocular vision. Sure, if your only goal is to not hit things at low speed in perfect weather, lidar is great. But you can't get much further than that.
If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world, which it could have then used to say "there is an object in the path I'm on, maybe I shouldn't plow into it." As opposed to relying on implicit and apparently unreliable cues like lane markers. That particular fatal crash seems like a sensors and geometry problem.
"Nothing about our current world has been designed for lidar and radar. It was designed for binocular vision."
Really? Was the world designed for binocular vision, or is it just three dimensional?
Having more sensors, especially when they have different failure modes seems like the only possible way to create a reliable system. LIDAR isn't super dense, but generally has accurate returns. Binocular vision sucks on untextured objects, like the side of a white truck in the fatal Model S collision. Why wouldn't you want the crutch of both types of measurement?
> If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world
No it wouldn't. The whole problem with avoiding stationary objects is that they are _everywhere_. Do you really think radar and vision didn't "see" the barrier? Should it have known that it was in it's path? For sure. But that has nothing to do with sensors. Stationary objects are in our paths constantly while we drive, but we tend not to hit them because they are usually only temporarily so. At 80 mph the difference between a parked car being in our path and not, at the stopping distance of over 300 feet, is only a degree or two of wheel turn. We have enough information. Acting on it appropriately every single second of operation is the problem.
> Really? Was the world designed for binocular vision...
Yes. That's why we have road signs, stripes on the road, reflectors, lights on cars, lights hung over the road which light up in different colors to indicate right of way, etc. LIDAR is useless with all of the most important signals on our roads.
Well, my optical sensors(i.e. eyes) provide me with enough information to discriminate a cat from a bag, so I suppose with enough processing we should be able to do the same with a control system. Cars have an added advantage that their vision systems could work in lower light and non-optical wavelengths. I don't see any fundamental issues with getting self-driving cars working. It may not happen in 5 years, but it will happen.
The tough part about this line of reasoning is you can't tease apart the discriminatory power of human knowledge from human vision. How good does our expert system need to be? How good do our sensors need to be? I'm not so sure this is an easy to question to resolve
Exactly. Children have decent hand-eye coordination as toddlers. By 3 or 4, they can drive toy cars; by 5 they're riding bikes. But it takes them another decade or more to have the knowledge and judgment needed to drive a car in traffic. And even then they're not great; teens have a crash rate something like 3x other drivers.
Because of immaturity, not cognitive or physical capability. Kids start racing go karts as young as five - and that's a far more difficult, requiring fast reflexes, precise car control, and situational awareness. It's a far more challenging task than an average commute.
Not really, racing carts is primarily about the ability to control the thing under very well defined conditions (read: much better than your average 3 lane highway with hundreds of other road users) with other road users with the exact same end goal.
Exactly. "Immaturity" includes a big lack of detailed domain knowledge and domain-specific judgment, which is one of the things I think is going to be very hard to teach to computers.
Depends on what you mean by "domain", I suppose. But driving is a very broad domain. One has to understand human custom, human psychology, and human ethics, for example. As well as the behavior of wildlife, some applied meteorology, and a fair bit of understanding of both law and police practice. To a computer, these might be unrelated domains, but they aren't if you put a computer behind the wheel.
Evolution achieves that in part by a callous disregard for individual lives. The intelligences that evolution has produced are built on an unimaginable pile of corpses. Even Uber doesn't seem quite as willing as mother nature to spend quite so many lives to achieve incremental improvements.
What do you mean "no one"? Press coverage of Waymo is full of references to engineers who are teaching cars and cars that are learning. The AI car is a big part of the hype.
Sure, as long as you have reasonably well-calibrated cameras and optics.
Back-of-the-envelope calculation: assuming 1920x1080 camera sensors with a 90-degree horizontal field of view, each pixel covers a visual angle of approximately 0.001 radians. If you have two cameras separated by 5 feet horizontally, and your measurements are accurate to within a pixel, then you can measure the distance to an object 500 feet away with roughly 10% accuracy. That's a reasonably conservative following distance at typical highway speeds.
And that's just from a single parallax measurement. By using other visual cues (e.g. apparent size of an object whose physical dimensions are known) and averaging measurements across multiple frames, you can get a more accurate measurement.
Ah, I meant for humans. As in, how much is depth-perception actually necessary for driving... Obviously, humans also use higher-level cues, which IMO are much more important.
Whoops, my bad for skimming the comments and overlooking the context of your question.
I found a page [1] that summarizes the level of visual acuity required to obtain a driver's license in each US state. It appears that all states will potentially issue a license to someone with vision in only one eye. Some states impose additional conditions, such as requiring a favorable report from an ophthalmologist, limiting the maximum speed, or restricting the driver to vehicles with outside rear-view mirrors (to compensate for the loss of peripheral vision on one side).
As evidenced by my username, I can say confidently that you are correct. The depth perception gained from two eyes is only good at very close ranges and doesn’t play a big factor in most driving situations.
>You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning. That's just used to guess what they're going to do next. It's not used to decide if they're an obstacle. Obstacle detection and avoidance is all sensors and geometry.
Honestly, getting them to work to this basic level is the "easy" part. Real world driving conditions in urban environments are suboptimal at best. You're not only going to need a system that can navigate around and not hit things. You need it to be able to dynamically route around road-construction, do clever things to find parking.
Roads in most places aren't that well standardized. It takes a lot of small judgement calls for a taxi to actually do its job. Uber and Lyft still have trouble dispatching people to pick you up at your actual door!
Roads are currently designed for human drivers. Roads designed for automated vehicles could use different signalling systems for intersections and road works, and even parking (it would help if unattended vehicles could be moved at will for tighter packing).
That would be great but in reality we're going to need self driving cars which are near enough perfect with the existing infrastructure to get some major traction before roads start getting designed for them.
>Roads are currently designed for human drivers. Roads designed for automated vehicles could use different signalling systems for intersections and road works, and even parking (it would help if unattended vehicles could be moved at will for tighter packing).
For the amount of money it would take to completely overhaul the country's entire transportation infrastructure to accommodate self-driving cars in this way, you could have built a phenomenal train and bus system with bike/scooter lanes everywhere.
Coming along fine, sure, but isn't the point about reality versus hype?
The guy who started iRobot, Rodney Brooks, doesn't believe we'll see a true driverless car operating throughout a city on normal roads until 2035 at the earliest: http://rodneybrooks.com/my-dated-predictions/
As software developers, we all know how big the difference between "a demo the boss is excited about" and "reliably working in production for all users" can be. Given how complex the domain is and how many edge cases it has, I can easily believe Brooks is right here.
I had a look at his predictions re: self-driving cars. He clearly invested quite a lot of thought went into these because he makes a lot of subtle distinctions. However, one of his predictions (probably the one that you're referring to) is this:
> A driverless "taxi" service in a major US city with arbitrary pick and drop off locations, even in a restricted geographical area.
> Not Earlier Than 2032
This is odd because isn't Waymo doing just that in Phoenix with a general release date of 2019? I checked the source because I wanted to verify that it says "a city" and not "any city".
I think his note clarifies it pretty well: "This is what Uber, Lyft, and conventional taxi services can do today."
What I've seen about Waymo (and maybe I've missed something) is very hazy. And it's not out yet. I'll be very surprised if they go from "operating in secret" to "completely competitive with Lyft" in one jump. My guess is that there will be significant limitations for whatever their first release is.
Waymo is available right now, and has been for almost a year, to normal non-employee citizens, in Phoenix, albeit behind a private invite system. And as mentioned above, it'll become an open beta by 2019. Also, most of the limitation at this point has to do with regulation, they'd be in many more places if not for that.
Do you have a proof for that? Waymo is actually the only car that explicitly does not allow teleoperating. They specifically made this decision to bypass the risk of being hacked and taken over.
The best a teleoperator can do is suggest a path to a car that is confused, and the car decides if the path is a good idea. We also don't know how often that's used. If it's rare enough, does it even matter? Does it not make it driverless if once in a while they need a little nudge?
That's like saying your car isn't a real car because 1% of the time you need to take it to the mechanic.
I think you're correct on the first part; "It does have humans in remote operations centers who can communicate with passengers and guide the car in complicated situations—like a cop sending cars the wrong way down a one-way street—but they never take actual control of the driving; it’s the car’s job to stay safe." https://www.wired.com/story/waymo-self-driving-car-service-p...
Precisely, not Level 5. They are hiring for their remote operations through Adecco: https://www.adeccousa.com/jobs/self-driving-vehicle-operator... . This is a job where you sit in front of the display(s) with steering wheel in your hand and foot on the pedal. Remote driving - pure and simple. Not very scalable.
Yes, they are operating in secret right now, and are extremely hazy about what "operating" means. And they have said they'll be in open beta by 2019. But it wouldn't be the first time that a software project is late.
Google has promissed "release dates" as early as 2017 in the past. They have managed to keep exactly zero of those. Not only have they pushed back their deadlines again and again, but the scope of their promisses has also been reduced steadily. Let's wait and see what they can actually make work reliably next year.
> You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning.
What you wrote makes a lot of sense to me. However, I would also hope that in a matured self-driving environment, traffic lights would be mapped ahead of time. It's always possible that a traffic light shows up in an unexpected place, but in my mental image of the future, this raises a flag for system management to modify the map of permanent objects.
There is a chance that a powered non-permanent traffic light is found somewhere, a dude walking along the side of the street with a stoplight on his back, and connected batteries. In that case, the police need calling. In machine learning, there are just so many corner cases where best to not try to fully interpret, just call out "dude, look at this thing!"
> There is a chance that a powered non-permanent traffic light is found somewhere, a dude walking along the side of the street with a stoplight on his back
Temporary traffic lights are extremely common, at least here in Australia. They are used in the case of roadworks or other short-term disruptions that requires traffic flowing in both directions to share a single lane, in conditions not suited to manual traffic control (i.e. overnight, weekends, long-term works on rural roads).
Ideally you would have a radio transmitter on the traffic light that broadcasts its location, metadata, and state information. You could still have a database, but it would be much more redundant to have live information.
It's relatively common for road maintenance crews in rural areas to install temporary signal lights during major projects. For example when they close one lane on part of a two lane road so traffic can only move in one direction at a time while the drivers going the other direction have to wait a few minutes.
Geometry inferred from range sensors can certainly provide an additional useful source of information, but it's far from clear that the right approach to controlling a self-driving vehicle is mostly to solve a geometry problem. For example, even if a range sensor can provide a perfect estimate of the location and geometry of pedestrian, how do you predict whether the pedestrian will dart out into the road or stop because they see a car coming. Human drivers have learned from years of (mostly) visual experience observing human behaviors to make reliable predictions about such things. Perhaps machines can too.
Since evolution didn't provide us with our personal lidars, human drivers are an existence proof that it is possible to learn reliable driving performance from vision alone. Which isn't to say that machine learning based on vision alone is already close to human-level or competency or that human-level competency is sufficient for a automated driving system or that sophisticated sensors don't make the problem a bit easier. But I don't know how you can be so confident that vision alone (or primarily) won't be route that eventually succeeds.
How could it do that? The safety statistics quoted by Tesla is "fatalities per mile of Autopilot-enabled vehicle", compared to "fatalities per mile for the average car on the road". It's by no means an accurate comparison, in fact they're inflating their relative safety versus other cars by more than an order of magnitude.
Tangential to your point, do you think it's fair to compare AI driven cars to "average" drivers? I think it's more reasonable to compare them to "average [worst_category_of_driver]." For example, how does the Tesla car compare to teen drivers? If it's better than a meaningfully sized category of human drivers, it's probably ready for the road. Being on the real road is where the best data will be collected.
This seems backwards to me. Shouldn’t we be comparing the performance self-driving cars to the performance of competent human drivers? The variance in human driving ability is quite high, which suggests (to me) that self-driving cars will become better than a significant fraction of human drivers well before they become (what I would consider) safe. I personally don’t want to see any more below-average drivers on the road. It’s true that there’s a constant influx of inexperienced human drivers, many of whom (in my opinion) shouldn’t have been granted licenses, but that’s a separate problem. (I’m talking about the US. I’ve read that licensing requirements are more stringent elsewhere, but here in the states we give out driver’s licenses like candy.)
I think you're confusing the end goal with the path towards that goal. Ultimately, yes, we will want to compare AI driven cars against the best human drivers. But right nwo we're trying to determine if AI driven cars should even be allowed on the road.
The underlying assumption I'm making is that AI driving improvement is accelerated by being on the real road. If that's true, then we want the cars on the road as soon as reasonable possible. Because I would gladly trade hundreds or even thousands of AI driver caused deaths in the short run if I am reasonably convinced that it will prevent the tens of thousands of human driver caused deaths every year. And I am convinced of that. I also acknowledge I'm in the pool of people who might be killed by the AI driver. Just as we let teen drivers on the road with the expectation they will improve over several years, so should we accept a similar risk from AI drivers. The return is far better for the "inexperienced" AI driver because the AIs will continually improve forever, but as you noted we get a new batch of bad human drivers every day.
That’s a fair point. From a utilitarian perspective, I think you’re probably right. Unfortunately, the public will not follow this dispassionate line of reasoning if AI drivers start killing people in “large” numbers, even if there’s strong evidence to support its soundness. It might therefore be best to be just a little less aggressive than would otherwise be optimal, to avoid a public backlash that could—despite being irrational—delay the arrival of competent AI drivers.
The point is that we allow teen drivers on the road with the expectation and understanding that they will improve over several years. Why would we not expect to have to make the same concession for AI?
Because they are companies that sell a product to consumers, who expect that this will keep them safe on the road. We need to hold them to a much higher standard than a teenager.
I suspect that the corporate entities involved have such deep pockets and/or so many lawyers and lobbyists that won't work.
Instead, how about:
All new autonomous vehicle configurations (let's call that the algos + sensors + vehicle) have to take some kind of actual driving test, just like us humans do.
Maybe the public could even help design a good test? "Not driving at speed into a stationary fire truck which is parked on the highway right in front of you" would be one element I'd want to see tested.
If an autonomous vehicle is involved in an accident, and the algo/sensors/vehicle are found to be (partially) at fault the configuration earns penalty points.
If that configuration earns enough penalty points over a period of time, the entire configuration loses its certification, plus a fine, plus a mandatory re-test.
This method appears to work reasonably well in dealing with us not-always-perfect human drivers, and ought to concentrate the minds of the designers/developers/managers behind autonomous vehicles.
How did you conclude this? There are other similarly-priced but more-numerous models of car where literally nobody has ever died after crashing one. Controlling for price (as a proxy for the wealth of the occupants) Tesla has a poor safety record.
I was in a statistics class where the Professor was teaching likelihood, then asked if there are cases when we don't want to maximize the likelihood ratio. The answer is when you want to put a limitation on false positive (or negative) detection.
You wouldn't vet a system that is susceptible to high false negatives and likely to kill people- no matter how good the accuracy is.
Humans die on average every 80 million miles driven ( not sure the metric for highway miles only ), but prove that Tesla can beat that metric and you can assume lives are being saved.
In addition to the confounding variables others have mentioned, I think the most important factor is when autopilot is enabled. If you don't (or can't) use autopilot at night, in inclement weather, or in construction zones, then you'll get into more accidents when not using autopilot -- even if it's a significantly worse driver than you are.
not so fast. youneed to compare tesla death per mile withother high end sedan death per mile. comparing a population of all cars include a lot of less secure cars, like city cars, old cars and cars that haven't enjoyed the same level of maintenance a driver with high income can afford.
iow tesla needs to beat the average 2014+ 3 series death per mile.
You also need to account for the regions where Teslas are most popular, the demographic of people who are purchasing Teslas, cars with similar safety features, and many other factors. Comparing the very tiny slice of the market which drives Teslas against every other car+driver on the road is almost meaningless.
Arguably, but it's hard to demonstrate the negative. At best, we can compare Tesla accident rates to those of other vehicles in the same class (luxury sedans). I'm sure you're right, but proving you're right against the naysayers is a different problem.
Sir, you have nailed it. No serious robotics project deployed to date does anything more than Good Sensors + Good Geometry. And I do not think a revolution is required, just good old time.
At some point the right balance of sensor quality and manufacturing processes will converge to be an affordable solution to highway driving. (broad daylight, then dusk, then maybe rain, etc etc).
If history is any guide (airlines anyone?) This will come along piecemeal, and the CEOs being forced to make ridiculous promises to appease shareholder anxiety will be given nice scapegoat packages along the way.
All will be available, all from the same company.
EDIT: Waymo laughed at "route-based advertising" when I mentioned, but ZF supports this idea. Route-based advertising or route advertising is an advertising model where your vehicle diverts to make you see a particular place and/or get you to visit a particular shop. For example, it may make you see McDonalds to get you to buy BigMac.
My machine learning professor used to say that people tend to sensationalize self-driving car fatalities, without realizing that if every car on the road was self-driving, deaths would go close to zero.
I think the hard part of the problem is the infrastructure. Everyone wants to fix the cars, but they'll leave the hard part to the government- which is the development of autonomous-ready infrastructure.
I think we need to distinguish between assistive technologies, ADAS, self driving, autonomous, and driverless. They don't mean the same thing but are all interchanged.
For your professor, yes assistive technology like lane keeping assist and collision avoidance will save lives, but are no reason to go driverless.
I'm still taken aback by how quickly government (federal, state) allowed testing of driverless cars on public roads. Feels like a cold calculation made on behalf of citizens to say "some people probably need to die in order to bring this to market quickly, and that's ok with us in these areas."
The existence of cars and airplanes (even horses) is a similar trade-off. Some people have to die for us to even have them.
Ultimately the faster we bring driverless cars to fruition, the fewer people will die, simply because it's inevitable that they will quickly exceed the safety of humans.
Then we will have turned automobile safety into an engineering problem. It was partially that before, we could package the victim better to improve their survivability, but now we can modify the driver ... every driver.
> The fake it til you make it crowd had the fantasy that you just hook up some cameras to a machine learning system, train it, and you have self driving.
There are about 7 billion instances of those learning systems though.
Will this be replicated with machines in the next 10 years? I have no clue.
There's absolutely no equivalence between a CNN created today with deep learning, compared to the Neural Network in a human brain.
The problem with the human brain is one of inattention. CNNs / Artificial Neural Networks can remain at attention 100% of the time due to their artificial / machine nature.
But CNNs, despite being at 100% attention the entire time, still have issues determining if that splotch on the screen is the sky or an 18-wheeler.
Artificial Neural Networks / Convolutional Neural Networks have a very long way to go before they reach human equivalence. In contrast, sensor systems or LIDAR brute-forces the problem. LIDAR can see things human's can't see, and advanced sensors can tell you (at least, in clear conditions) the location and velocity of virtually every object around the car.
Fake-it till you make it camera-only driverless cars are clearly hype that relies upon a fundamental misunderstanding. Just because CNNs are kinda-sorta like the visual cortex of the human brain doesn't really mean that it works like one.
CNNs have really cool visual learning properties. But I've yet to see one 100% successfully tell you background vs foreground in pictures like a human brain can do. Even in clear weather conditions, the CNN can confuse a truck for the sky and still run full speed into an 18-wheeler.
I explicitly wrote my comment because @Animats said "machine learning system", not "CNN", which I know definitely not enough about to comment on.
Surely the field of "machine learning" includes things which are not even invented yet, the same way maths comprises of theorems not yet discovered.
I was just saying that I think one could "just hook up some cameras to a machine learning system, train it, and you have self driving", maybe not today though.
I dunno. I think "auto-optimization" best describes the process.
Even calling it "learning" is kinda overselling itself. There really are only two camps of "Learning": auto-optimization (against a trained dataset), and auto-categorization (aka self-training).
Its auto-optimization: the algorithm self-corrects itself to try and look more like the training-set's "ground truth". Or auto-categorization, as the algorithm looks for patterns and tries to draw its own categories.
"Learning" implies model finding. Which... strangely enough... I'd argue that 3-SAT solvers are more "learning" based, at least with colloquial use of the word. Those things really do craft new theories and test them through the process of elimination / resolution / etc. etc. "Neural Networks" explicitly DON'T do this however.
The 100% attention thing I why I have tremendous faith that computers will be out-driving humans in short order. Even really good human drivers have a limited perspective and focus. And even the best human drivers are subject to emotional state.
Yeah, humans suck at attention. But until we can program computers to tell me what is a foreground moving object, what is a shadow, and what is the background... you literally can't solve the "Should the car apply the brakes right now" problem.
Just go through this recent paper I found on DDG.gg and see the amount of effort it takes to parse foreground / background data that a self-driving car needs.
You gotta figure out if there's a still-object on the road. And whether or not its a shadow (shadows don't move after-all but its safe to drive over). Like, neural networks can't do that stuff 100% reliably yet. And it may never happen.
Or some researcher next year might come out and discover a method to parse background / foreground / shadows out of pictures. But then there are a whole host of OTHER issues involved.
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I think self-driving technology has potential. But you need more than just neural networks hooked up to cameras. I really like Waymo's direction with advanced super-human sensors. Avoid the shadow / background / foreground problem entirely and just have LIDAR give you the precise coordinates of all objects within 100-feet of the car.
IMO, if self-driving technology ever happens, it will be because of advances in advanced LIDAR or other kinds of sensors. Stuff that can avoid the research-problems that the "Deep Learning" community hasn't been able to solve for the last 50 years.
That's why I think the future lies with a mix of (possibly layered) sensing and decision-making technologies. LIDAR + cameras + downloaded maps + machine learning + whatever.
The "until we can program computers to..." is a when question, not an if question. There's nothing about driving, in any situation, that doesn't fall in the face of "assuming infinite computing power and infinitely good sensors". Driving isn't a creative act, it's a responsive one.
I think that's reasonable, although our time estimates for when this problem solved may disagree.
My main issue is that a large number of people seem to think that cameras + machine learning are enough to solve this problem. And while I'm not an expert at machine learning, what I know about it makes me a pessimist. There's just too many unsolved problems in the machine-learning community to apply machine learning to the car-driving problem.
Machine learning probably can solve weird cases people don't expect. IIRC, CNNs are better at recognizing blurred or garbled text than humans these days. So CNNs can read speed limit signs, road signs, and other texts and and at least process that.
Even figuring out if its a speed limit sign, an address, or a route-number probably can be solved by CNNs. But higher level reasoning (is that spraypaint messing up the signpost?? Which was common in some of the areas I drove through) seems like an unsolved problem.
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Anyway, Machine Learning + Cameras are IMO, at best... a partial solution to some of the problems. Anyone who thinks that cameras + radar + machine learning is sufficient is probably just a TSLA long who wants to believe in the success of their stock. Otherwise, I think most people are reasonable and recognize the importance of experimenting with a ton of different methodologies to solve this problem.
Humans suck at these classification tasks things too, though, if you set your expectations high. Is it a cat or a bag, or a weird shadow? Doesn't matter, I ran it over before I could figure it out and react. Or maybe it turned out to be a boulder? Now I'm one of 35,000 traffic fatalities this year in this country.
Computer vision has been improving rapidly in the last 10 years, I think it's too soon to rule out the viability of a camera-based solution entirely. Though I do hope improved lidar technology can improve on humans.
Humans are way, way better than current CNNs on this field. We can talk about cats, shadows, and boulders when CNN-based methods stops crashing into concrete barriers, parked fire-trucks, and 18-wheelers making a left turn.
I don't want to dismiss the work of Deep Learning / Machine Learning specialists. I just want to point out that the problem is incredibly difficult. It is very far away from being a solved problem.
> Traffic-Aware Cruise Control cannot detect all objects and may not brake/decelerate for stationary vehicles, especially in situations when you are driving over 50 mph (80 km/h) and a vehicle you are following moves out of your driving path and a stationary vehicle or object is in front of you instead
This is a known issue, a known pattern and has happened multiple times this year. Its repeatable. CNNs today are not working in this case, and fixing it will require a research effort of mammoth proportions.
You're talking about what the tech does. I'm talking about what it can do, with reasonable-sounding non-magical improvements to tech. Just because there are limitations now does not mean those limitations will still exist in ten years.
Look at other people's videos of driving through that section of road around the same time - the pedestrian would have been clearly visible and the car and safety driver should both have easily seen them and stopped. If you read about the preliminary NTSB report [1], it's clear that the car had six seconds of warning and 1.3s of certainty of impact, yet did nothing to avoid it, not even alerting the safety driver. The pedestrian may have been foolish, but the car could easily have avoided killing them.
From Sterling Anderson, former director of Autopilot who oversaw the implementation of HW2:
>Perception is a game of statistics.Crudely speaking, if we have three independent modalities with epsilon miss-detection-rates and we combine them we can achieve an epsilon³ rate in perception. In practice, relatively orthogonal failure modes won’t achieve that level of benefit, however, an error every million miles can get boosted to an error every billion miles. It is extremely difficult to achieve this level of accuracy with a single modality alone.
>Different sensor modalities have different strengths and weaknesses; thus, incorporating multiple modalities drives orders of magnitude improvements in the reliability of the system. Cameras suffer from difficulty in low-light and high dynamic range scenarios; radars suffer from limited resolution and artifacts due to multi-path and doppler ambiguity; lidars “see” obscurants.
He is basically just saying that the errors need to be independent, so you can get that with different capture mechanisms. I think that is wrong. For example, small, fast and poorly reflective will have similar detection performance for lidar and cameras. I think that the real problem is getting consistent statistical estimators and fusing them at a useful update rate. Has anyone seen the lidar from the uber crash? It would be interesting to see if a person could "tell" that the poor pedestrian wasn't an artifact quickly from lidar alone.
The radar, Lidar and cameras on the Uber that struck Elaine Herzberg all detected her, it wasn't a sensor failure that led to her death, it was a software failure, the autonomous OS tuned to not respond to positives below a certain threshold.
First, thanks for sharing this! Second - based on the language used I can’t tell if he is saying Tesla’s camera and Radar approach will work, or that it won’t. The only thing that I pulled out was that if we increase the types of sensors we get better results because they have different strengths and weakenesses.
Sterling does believe cameras may someday be good enough, but I'm personally of the belief that Lidar will get cheap before vision gets good, and as such there's no good reason to not have the extra redundancy.
I’ll take the “over” on that bet any day of the week. It might not be 20 years, but it’ll be a friggin’ while.
There are scenarios it’s possible to encounter on the road that humans don’t even necessarily know how to handle immediately. In proper, brutal, real-world testing, one very quickly enters the realm of problems that you’d need full-fledged general AI to reason through.
Most self-driving efforts do not consider malicious actors and instead aim for sufficient caution to avoid danger. Malicious actors can never be entirely accounted for, as a driver on a narrow road can turn into your path in moments and you can't avoid the impact.
As an existence proof, people drive through fog every day. We prove that it's possible to take binocular visual data and convert that into a series of control signals that will propel a car through fog. Sure sometimes accidents happen, but every day thousands upon thousands of people safely navigate fog in e.g. San Francisco or London. I see no reason machines shouldn't be able to perform at least as well one day.
Just as a point of reference here - I'm not taking sides in this debate, I vividly remember reading about the 1999 Toronto 87 car pile up.
Fog on a straight road caused an 87 car pile up after a trailer jackknifed. The point in the article I remember at the time was a mother recounting watching her 14-year old daughter burn to death. Mom got out, but the daughter had been pinned by her leg.
The quote from the time was ""Mama Sheila, please don't let me die. I'm only 14," Marceya McLamore begged."
I suppose my point is that neither human or machine are good enough yet. and not to treat this as an abstract academic topic, it's real people.
I think olivewell's comment in this subthread is what dooms the idea of camera-only self driving for a really long time horizon: you basically need general AI for it.
I work in machine learning in a different area (healthcare) so my perspective may be incomplete, but what I see in ML/AI is that models are really good at memorizing, not so good at understanding. What I mean by that is that a human navigates the world by knowing what a car is, what fog is, what a person is, what a plastic bag is, all sort of things. Object detection can get much of the way there, whether it can get enough of the way there is an open question, but ok we'll grant that. Whether AI/ML can actually make the step from knowing what the object is to knowing how that object interacts with all the other objects in the world is another.
In other words identifying an object is just step one, understanding what that object means in context is the next absolutely required step, and it's way harder. We have a leg up as humans so we can rely on visual alone, but machines almost certainly will need other sensors that report additional information because they don't "get" context in the same way. And I'd say it's an open question whether even with those sensors, they'll be able to get there. I hope so, but the game is far from won.
Machines will be (and already are) held to a much higher standard than human drivers— there are a lot of reasons for this, ranging from the emotional to the pragmatic.
Just because thousands of people roll the dice every day driving in unsafe conditions does not mean that we should tolerate machines doing so.
One note is that perhaps people roll the dice because they want to feel some control and forward momentum. But if you're sitting in the car, being autonomously driven somewhere will you be so impatient?
I assume the car will give you an ETA, so you'll check the clock and go back to your book/social media. I'm okay with "slower, but smoother".
I think a lot of people in this field did see this coming. I knew a few people in this space about a year ago and I pretty much hear: "realistically, 15 years out at the earliest."
I really really hate the concept of a driverless car. It's an incredibly difficult problem space; and for the same cost, America could build up municipal rail and bus infrastructure to where they were in the 1940s/1950s. We need more cities like Seattle with its rail expansion and fewer New York City where the infrastructure is finally getting money so it doesn't fall apart.
There are already so many tax breaks going into driverless companies. If Alphabet or Here want to do this on their own, go for it; but governments around the world should stop giving tax breaks and municipal incentives for this technology.
I can see it being more useful in Europe, where so much of the country is connected and it'd help sold the last leg problem. But in most of America we need to get back to the point where cars are no longer a necessity, not just for those who can afford to live in the city, but all the people who are barely making it who's lives fall apart if something on their car breaks.
> But in most of America we need to get back to the point where cars are no longer a necessity
While I completely agree with you, the cultural barriers to this are petty much a non-starter in much of the country. I love not owning a car and being able to rely on mass transit where I live (Austin, TX), but Texas is so culturally opposed to anything like this.
A lot of people think that mass transit is for the poor, and the car represents independence and freedom. Go where you want, when you want (but you're gonna be bumper-to-bumper most of the way there.)
I hate that mentality, but driverless cars represent the "have your cake and eat it too" solution. It more closely aligns with the culture of driving here in the US, while also claiming numerous commercial and infrastructure benefits.
>A lot of people think that mass transit is for the poor
That's because it is. I had to take the metro in Montréal to get to work this week, hadn't taken it in months because I usually bike, it's such a shitty experience. It smells bad, it's hot, it's filled with tired people that don't feel like going to work (you feel it in the air), beggars harass you, it's slow (it can take 3x as much time as riding a bike to get where you want to) and it's operating past maximum capacity during rush hour. I haven't even gotten started on when service is interrupted and you show up over an hour late to work or class. Anybody who can afford a bit more for reliability and comfort will spend it without looking back.
I can't speak for Montreal, but there are countless counterexamples of cities in wealthy countries (not as wealthy as the US) where metro users are drawn from more or less every income level. Turns out you can actually make riding a metro into a good experience with a bit of effort.
New York, Chicago, Tokyo, Taipei, London, Berlin, Munich come immediately to mind.
And as sibling commenters have pointed out, in some places even smaller cities and towns have excellent public transit networks that pretty much everyone uses (maybe not always, but when convenient). Freiburg, Germany is one example I've seen.
Don't know if I'd go so far as to say riding the subway in NYC is "good" experience, but I'll certainly agree that it's one shared by people across the socioeconomic spectrum.
Taipei... yes, absolutely. That was a great experience and easy to use.
NYC... altright, better than 15 years ago but still not great at all. Not as good as Germany or DC.
Tokyo... lol, no! While clean and efficient, it’s a joke that you have different rail stations owned by different companies, different cards that may work on each other but probably not. The ticket machines are almost all cash only. And instructions in other languages might have well used Google translate. Tokyo was one of the more difficult public transport systems I’ve used and I’ve been around the world a bit.
Suica cards work practically everywhere. You can poke a button to use english, usually clearly labeled. You need cash everywhere in Japan so not sure why that surprised you. My experience with Tokyo metro was pretty good. I've never seen a metro as well-organized despite 15 private rail companies splitting the system. The only problem is the operating hours, the last train rush is insane some nights.
The English button does work great... But doesn't tell you a DAMN THING about which line to transfer to get to some location just how much it costs. And when you need to transfer green to blue, good luck, because you better know that this one blue arrow pointing left means you need to go upstairs, cross the street, go into an entirely different station and then go down two flights of stairs with basically no more directions in English.
I was surprised that the machines only took cash, but it was annoying as hell that we were 10yen short and the nearest ATM was 2 blocks away under the street then back up again.
The rush for the 11-11:30pm trains are nuts. I've never seen so many black suits filled by unsmiling faces than the last train out near Tsukiji.
Did you just claim DC public transit is good? Wow. Coherent bus lines are few and far between. Light rail is non-existent. And the Metro is falling apart at the seems... Prone to excessive delays. Entire lines are brought down for extended periods to perform decades of deferred maintenance. There's no ring routes - to get from Dulles to Rockville, you have to go all the way downtown and back out again. The system was built without consideration for express lines. And neither of the DC airports are on the same line as Union Station.
A ring route from Bethesda to Largo is under construction and it's called the Purple Line. Metrorail could be better and has it's own shortcomings but it is one of the best in the US and far from nonexistent.
I said light rail (trams, streetcars) is non-existent. There is a test line in South DC, but nothing that’s actually useful for commuting or getting across the city.
My wife tried to use Metro for her Reston->downtown commute. It was a disaster - rail delays made it completely untenable. Then she tried the bus. It was more consistent, but overcrowded. She ended up driving 4/5 days because it was faster, cheaper, and more consistent.
It's easy to buy a card, and get on the right track. Your day to day minutia is of little concern to people that just need to get on and get somewhere.
> The ticket machines are almost all cash only. And instructions in other languages might have well used Google translate.
That's probably only hold true for (Western) tourists. And I don't think it is fair to compare on that. Tokyo (and Japan in general) rail system can be really intimidating but that's just because its sheer size, but once you know your way around it, it's gotta be among the best rail system in the world.
My wife & I live in San Francisco. SF Muni fares are a flat $2.50.
So for the two of us, a Muni trip is
- total cost: $5
- usually takes 30-60 min to get wherever we want to go in the city.
- we need to to figure out the optimal route, schedule, and entry & exit stops.
- we need to make sure we will arrive at the stop on-time.
- we need to walk 5-10 min to closest stop on either end
This process is familiar to anyone who's taken public transportation. In general, I think it's a great system. Muni network coverage is pretty good in SF.
However... a low-cost Uber or Lyfts pool ride for two is
- total cost: $5-12 (same serice area as Muni)
- duration: 15-45 min
- we don't have to plan the route or schedule
- we don't have to worry about going to a remote pick-up stop on-time
- we get dropped off directly at our destination
So, in the best case scenario, a lyft line ride is the same cost as Muni but so so much better in terms of value to us. Even when it is 2x as expensive, for us, the extra $5 is totally worth it. I know that's not true for everyone, but I personally am amazed that the cost of using the cheapest ride share option is often only 1x-2x the cost of using the billion-dollar municipal public transportation system.
Of course, here in SF ride share vehicles are definitely not allowed to use the special public-transportation-only lanes of some of the major roads, which remain reserved for the exclusive use of Muni buses and taxis to improve their transit times.
The muni system is one of the worst functional bus system that I have ever encountered.
Sure there are worse systems that don’t have any coverage (El Paso for example) but they are not functioning so I don’t count those.
Problems with muni include:
- To many stops (like every two blocks).
- Hardly any dedicated bus lanes, bus gets stuck
in traffic too many times.
- Slow and un-intuitive routes.
- Small and overcrowded busses.
- No transfer to BART or ferries.
I recently came across a muni map from the mid 80s and it was almost identical to an up to date one. That might give an idea of how stagnant the system is.
The few good things I find about the muni system is that it has good coverage, frequent busses[1] and is cheap.
[1]: Sometimes too frequent, I sometimes see the 14 being stuck in congestion of other 14s
This is cherry-picking. It always makes more sense to take a car service when multiple people start and end at the same places and can easily coordinate (e.g. a married couple). But this tells us nothing about the average outcome. The _average_ car contains only 1 person.
Does anyone have back-of-the-napkin estimates of total passenger throughput for central public transportation vs ride share transportation for any metropolitan area?
If public transit i.e. Muni serves 10x or 100x riders each day vs ride sharing than I see your point... I think.
Don't bother with napkins. The data is open. TNC trips average about 150k / weekday [1], BART carries about 415k trips / weekday [2], and Muni carries about 750k [3]. Thus, public transportation carries about 8x more people, with the caveat that not all BART journeys start or end in SF.
On the other hand, 99% of vehicle trips in SF are either private cars or TNCs.
Neither of these was my point, though. My point was that comparing cost between a per-trip price and a per-person price will always favor the former when there are multiple people. But most trips don't involve multiple people, which is why such an analysis is besides the point.
If we’re comparing a bus or train to a Lyft or Uber carpool or line of some sort, wouldn’t you expect it to be more cost effective to drive people around in buses rather than cars, even if the app coordinates things so that there are two people in the car? It sounds like buses are not very cost effective.
I think what’s actually happening is Uber drivers are paid peanuts and provide and maintain their own vehicles. There’s a technology innovation (eg the efficiency of knowing if and where someone needs a ride) coupled with a labor innovation in paying drivers less than minimum wage.
Huh. This is interesting. The "Learn More About TNCs" button on the page you linked to leads to some more facts, including:
> "On a typical weekday, TNCs make more than 170,000 vehicle trips within San Francisco, approximately 12 times the number of taxi trips, representing 15% of all intra-San Francisco vehicle trips." - https://www.sfcta.org/tncstoday
So: 1,333,333 intra-San Francisco vehicle trips each day, including Transportation Network Companies (TNCs), and from your other links, 1,165,000 MUNI+BART trips per day, for a total of 2,498,333 rides per day
The population of the city during business hours is ~1,100,000... Oh of course, most people make round trips so it makes sense for the total number of rides to be >2x the city population.
The reason I brought this up was to wonder how insane (just a little? or totally impossible?!) it would be if 100% of public transportation was serviced by "TNCs" in the city.
> "On an average weekday, more than 5,700 TNC vehicles operate on San Francisco streets during the peak period"[sfcta.org/tncstoday]
So if TNCs provide ~30 trips a day, and all 1,165,000 MUNI+BART passengers switched to TNCs, there would have to be an additional ~40k TNC vehicles in the city :).
Maybe it would work if they were really, really small.
Mass transit will always be viewed as the lesser option where it is the lesser option.
In cities that were designed or entirely remade to support the automobile, the automobile works better than everything else. This is almost a tautology, but it's remarkable how often it's overlooked in this discussion. If cities were re-designed around transit (with more density, smaller roads, and more space for alternative transportation modes), then transit would work better and cars would be worse. †
In summary, yes, obviously cars work better in cities designed for cars! But cities that work well for cars aren't a natural feature of the universe. It took a lot of work to get them to look like that.
† An important implication of this is that transit will never overtake the automobile in low-density, sprawl-heavy cities. Transit use is high where the transit infrastructure is good and driving is painful. Both things have to be true. ††
And the tension here is direct. Sprawl-heavy areas can't support good transit infrastructure and high-density, pedestrian-friendly areas are awful to drive in. A choice for one is a vote against the other.
†† This is why arguments about the superiority of cars based on revealed preference are usually spurious. If you put a light rail system in a town built for cars, then people will keep using the thing the town was built for. But those people are revealing their preference for cars in an environment built for cars. Where the built environment is different, people behave differently.
My experience in my multiple Montreal soujourns has been so different that I consider the Metro to be a jewel. I admit that some stations are grungier than others (once I had to duck an errant basketball at Cote-des-Neiges) but that was once out of around 100 trips. I do agree that the air conditioning is marginal.
It largely depends on the country or even city. Me and my gf went to Switzerland by car a couple of years ago (we live in Eastern Europe) and I’d had expected that we’d visit different parts of the country by car. What happened once we got there is that we “forgot” the car in the hotel’s parking lot for a week and we did all our travel by train, it was wonderful. Even traveling inside the city itself (we were based in Lausanne) was a very nice thing, I’ve started building a soft spot in my heart for the city’s trolley-buses (electric public transport rocks, btw, always has, alwsys will).
American living in Switzerland. From what I understand, access to public transportation seems to be considered a basic human right here. No one is expected to have to buy and upkeep car maintenance.
While the electrification of the mass transit systems is super nice, unfortunately it came about because of the World Wars. Switzerland was hit really hard, and no one wanted to trade their precious coal away (Switzerland had no coal mines). Thus out of sheer necessity they began electrifying all the trains. So unfortunately there's not replicable policies other countries can use to achieve what Switzerland has achieved in terms of electrification, so it'd take some creativity.
A lot of people think ... the car represents independence and freedom. Go where you want, when you want.
Well that's because it's actually true for a lot of people. Sure, there's no freedom in commuting between SF and south bay by car, or navigating the most dense downtown environments. But I definitely use my car on a daily basis for things that would be impossible or incredibly time consuming by transit. And yes, many of the transit patrons around here would probably prefer a car if they could afford it. Most places are not like NYC where the subway is often the most effective option regardless of wealth.
I don't think it's really feasible for more spread out suburban environments to implement effective mass transit. The anti-car idealists often seem to forget that there are a lot of people living outside of dense city centers.
Hmmm, weird idea here, but maybe that's the answer then?
If self driving cars are terrible at coping with the chaos humans grit their teeth and deal with, maybe software for engineering cooperative bumper-to-bumper traffic jams involving clogs of slow-moving self driving cars, that reduce the road speeds to constant 20 MPH (the /constant/ part being important), and eliminate chaotic lane changing to near zero for the group, is one way to bootstrap self driving cars.
In other words, low-performance self driving cars might work fine, and since people can lounge about, and disengage from the guidance and navigation tasks, why not go slower?
Then, add swarming to the mix, such that cars going to the same place, all travel slowly in a single group.
It's against the law to obstruct traffic, or violate minimum speed requirements, so certain laws would need to change. For example, zero emission vehicles can idle indefinitely, and software-controlled vehicles can interface with an external control network, approved to operate in such ways, with points of contact at operations centers for resolving problems, technical or otherwise.
So change laws to permit idle electric vehicles (in more places and controlled, desginated places, not just anywhere), and permit large slow moving groups to occupy certain corridors, at certain times, when jammed traffic is a known quantity, that driverless systems aren't the cause of. Driverless networks can cut into a slice of the jam, and possibly improve outcomes for members only at first, and eventually boost efficiency within the jammed system by augmenting flow through expert participation.
I'd like to join in on the bikeshedding mass transit into solar-powered self-driving car-apartments that can always drive anywhere with no congestion for free, need no maintenance, and aren't controlled by a monolithic entity with an abysmal reputation for profit over users.
Mass transit is expensive, boring, and thankless. How many bus companies have ever applied to YC?
I live in the countryside but work in the city. This is in the US, so there is no bus I could take for my daily commute, though I've lived in countries where a similar arrangement would have a bus route within walking/biking distance.
The thing is, if there were a bus, it would have to stop to pick up / drop off passengers along the way, which would make it so much slower than driving that it really would be for the poor. I've been on such buses as a kid. Even when traffic is bad, bumper-to-bumper in a car (taking the fastest route) is going to be faster than bumper-to-bumper in a bus (taking a more circuitous route and stopping frequently along the way)
I think the only way buses will stop being for the poor, is when they stop become faster than more expensive alternatives. (Or at least nearly as fast and significantly cheaper.) If you can save a lot of time by spending a little bit of money, which would you choose? What if you could spend a lot of money but it wouldn't save you any (or much) time?
In cities where congestion is a major problem, dedicated bus lanes/roads can help balance the equation in favor of buses. Usually there aren't enough dedicated bus routes though. (I might point out that the people deciding how to balance bus/car traffic are not the people who ride the bus.)
I still think self-driving cars are far in the future, but I find them appealing because they would make "buses" more efficient. A lot of the cost of operating buses is paying the drivers. To maximize economies of scale, buses are large, which means they have to make a lot of stops to pick up and drop off passengers, which in turn makes them slow. Self-driving buses could be a lot smaller and wouldn't need to make as many stops. If they could tell that no one will be boarding or deboarding at a given stop, they could skip it entirely and take a shorter path instead. At some point, the lines between bus/ridesharing/taxi get pretty blurry.
The problem with buses isn't picking people up or stopping. It's just that without dedicated lanes or busways, they're not better than cars. Same traffic, + stops is a recipe for failure for people who can afford it. My bus takes a busway and skips huge traffic jams. I save 25 mins riding the bus and I don't pay to park.
> If they could tell that no one will be boarding or deboarding at a given stop, they could skip it entirely and take a shorter path instead.
Everytime selfdriving tech comes up people say things similar to this, this problem is 100% solvable now. Why are we waiting for self driving cars to solve this problem?
>A lot of people think that mass transit is for the poor, and the car represents independence and freedom. Go where you want, when you want (but you're gonna be bumper-to-bumper most of the way there.)
What the hell is going on in Austin?
Bumper-to-bumper traffic happens mostly at commute hours in commercial zones and during special events. It's very much not the norm for driving at other times. To wit, I live in San Francisco, one of the densest and least car-friendly cities in the U.S., but the last time I returned from a road trip, I traversed the whole city corner-to-corner -- from crossing the Bay Bridge to arriving at my home near the zoo -- in less than fifteen minutes. Why? Because it was midnight! Cars provide unparalleled mobility for irregular trips outside of peak commuting times, even in the largest cities.
I wholeheartedly support deprioritizing car infrastructure and working towards a norm where most people do not drive to work, but I nonetheless believe that car ownership provides a lot of independence and ought to be accessible to the modal citizen, at least outside of the very dense coastal cities (SF/LA/NY). Cars work really well for irregular trips outside of rush hour. They work terribly when large amounts of people need to go to the same place at once.
I suspect that driverless cars will end up somewhere on the spectrum between buses and human-operated cars. They're extremely cautious and will be a lot slower than human-operated.
>Go where you want, when you want (but you're gonna be bumper-to-bumper most of the way there.)
I can count on 1 hand (ok, maybe both hands) the number of times I've been in bumper-to-bumper traffic in my life. One of those was in Austin. There's lots of places to go that aren't big cities.
I think it's pretty clear that Waymo & maybe Cruise are the leaders in this space. If you take a look at the quota from Waymo "it will be “longer than you think” for self-driving vehicles to be everywhere." - the key part is "everywhere".
Maybe it will take 15 years for it to be everywhere, but I'm still fully expecting a deployment in Phoenix this year or next.
I'm not really clear what tax break you're complaining about, AFAIK there is no extra tax break for Waymo.
Calling for better US gov infrastructure still doesn't solve this problem for them. Nor will American or Chinese tech companies. In the meantime I'll take driverless electric cars who are actually making progress pls.
Instead of fantasizing about the day modern nation states are marginally functional at delivering services, like they were half a century ago. Basically everything they touch, especially under the false guise of 'private' partnerships ends up a decade late and 2-4x the cost (in billions). And often delivering only half of what was originally planned.
The less we gamble on such a trainwreck the better IMO. Unless, of course, something changes. But every year and every election it seems to get worse.
You act as if self driving cars are independent of infrastructure. These cars need roads. And if these cars are your solution to mass transit, far more will be on the road, requiring more upkeep. Roads are huge money sinks.
You seem to think self driving cars are magnificent devices that just glide over roads and don't need bridges or tunnels. For some reason, we never include these costs with cars when compared to mass transit. That is simply unfair.
I'm not against self driving cars by any means. But people misrepresent them all the time.
I didn't make such a suggestion at all, I was referring to major transit projects and related projects. Seems like you're changing the subject anyway, so I'd rather not continue.
Perhaps you should explain how, of course I can't force you to continue. Simply say you no longer wish to discuss - no need to be insecure about the debate by needlessly adding a "convenient" excuse to exit.
This is the part that drives me crazy - America HAD electric railroads all over the place. Or at least Illinois (my homestate) did. You can look up 'Illinois InterUrban' and see maps of rails connecting every rural city.
Many of the carriages were used as scrap metal for WWII, and once cars took off the demand wasn't there to rehabilitate them. But it would be so much cheaper to build out than even just replacing the signals in NYC would be. All the right of ways are still there, many of them turned into bike trails (which is great, but I'd rather have a $5 ride to the next town over)
The carriages back in the day were pretty slow, maybe 20mph, so I get why cars won, but rebuilding this infrastructure with modern equipment would be a really nice situation, and if gas was 10$/gal we would probably see the demand, but as long as gas is cheap we lack the ability to plan ahead...
Unfortunately Illinois borrowed from future generations and horribly mismanaged the economy. Now they're struggling just to avoid bankruptcy, let alone building out huge public transit projects.
Not to mention a multibillion dollar, unnecessary tunnel linking O'Hare with downtown which will almost certainly cost multiples higher than Elon Musk and Rahm Emanuel claim. We'd rather spend money on vaporware than build something that would actually help.
>Not to mention a multibillion dollar, unnecessary tunnel linking O'Hare with downtown which will almost certainly cost multiples higher than Elon Musk and Rahm Emanuel claim. We'd rather spend money on vaporware than build something that would actually help.
That project is privately funded. The Block 37 station was the expensive vaporware.
Freight traffic dominates the utilization of the rail network in the US and is prioritized over other traffic. Freight trains travel slowly.
This is why US passenger train service is so poor compared to Europe.
> The picture for freight is different. According to Panorama 2009 , 46 percent of EU-27 freight goes by highway while only 10 percent goes by rail, while in the U.S. 43 percent goes by rail and only 30 percent by road. (In both cases, nearly all of the rest is waterways and pipelines.)
> So, it isn’t so much that Europe decided to move people by train rather than by automobile. It is more that Europe decided to use its railroads to move people while the United States decided to use them for freight. America moves almost six times as many ton-miles (or tonne-kilometers) of freight by rail as Europe, while both move about the same number of tonne-kilometers by road. While Europe moves about twice as many tkm of freight by waterway as the U.S., we move six times as much oil by pipeline. [6]
- area of Continental US: 3.12 million sq mi [1]
- area of Europe: 2.306 million sq mi [1]
- rail network length, US: 141,808 mi [2]
- rail network length, Europe: 157,667 mi [3]
- goods carried, US: 1.558 trillion lg tn mi/yr (long ton-miles per year) (world rank: 1st) (2015 estimate) [4]
- goods carried, "Europe": 0.32604 trillion lg tn mi/yr (long ton-miles per year)
I also wonder how much population density has to do with this. The distances that freight is moved over in the US seem far greater than in Europe. The same applies to people, rail travel is much more available/popular in the denser parts of the US, but for the west coast (for example) the useful stops are fairly far from each other, Seattle and Portland are relatively close at about 170 miles, but then its another 600 miles to Sacramento, or 680 to San Francisco. Even with (I wish) high speed rail, those are long journeys. Of course you can have long train journeys in Europe too, but there really aren't any sizable destinations between Portland and Sacramento (sorry Salem, Eugene, Redding).
I guess it feels like the distances involved in the US are more advantageous to freight, and in the EU are more advantageous to passengers
I'd argue the main difference is that the infrastructure in the US is private, while it's publicly owned in Europe. This allows some amount of subsidy towards the infrastructure, like is done for highways, allowing passenger trains to exist.
Since then railroads have to be completely self-supporting in the US, they focus on how they can achieve the highest productivity: giant, slow trains on shoddy track.
It also means the infrastructures are competing with one another, so there are redundant, shoddy, competing rail networks, rather than a network for slow and heavy freight trains, and a network for fast and light passenger trains.
City driving is a hard problem space, and all we'd achieve is cooler taxis.
The real game changer is instead driverless trucks.
Shipping is both a trillion dollar industry, and the problem space of "highway driving when it is sunny out" is much much easier than the consumer usecase, while still being extremely valuable.
I think you underestimate the impact of ubiquitous, free valet parking on urban design. We surround everything with parking to minimize walking distance to/from our vehicles, but you could organise things very differently if everyone was picked up and dropped off.
You could also park cars bumper-to-bumper, because you don't need trusted human drivers to move the cars boxing you in. Removing isles from the parking lot would nearly double the number of cars that could fit in a given space.
It's counter-intuative, but I think driverless cars may eventually make cities more walkable.
I knew a few people in this space about a year ago and I pretty much hear: "realistically, 15 years out at the earliest."
Driverless. Technology of the future. Always was. Always will be.
But seriously, how much would it take to mostly handle driving trucks on limited access highways between exurb mega-warehouses? By "mostly," I mean, be able to handle 98% of all situations, and be able to flag attention from a remote control human supervisor for the other 2%. I suspect we're pretty close.
> I pretty much hear: "realistically, 15 years out at the earliest."
And honestly any number is simply just 'pulled out of the ass' anyway. It's not as if they can see daylight on all the problems that need to be solved or predict various soft issues (the government only one example). So this is not that someone is building the atomic bomb and can realistically judge more or less the scope of the problems that need to be solved and then build in a bit of leeway.
Sure, the number is pulled out of the air in a way, but that's not what is important. People in the field know what is holding things back, and even if they don't don't see all the way to the end, they know enough about the journey to recognize that newcomers don't completely appreciate what they're up against, and rosy predictions about the proliferation of driverless cars is a reflection of that naivete.
"The idea that sharing rides is good has become almost axiomatic in transportation discussions. At conferences I have seen people declare that robocars are pointless if they are not shared -- ie. people who are not travelling together ride together in them. The positive of sharing is so axiomatic that public transit is seen almost as a good in and of itself, rather than a means towards real goals like energy efficiency, low cost, and higher road utilization.
It has has attained this status as revealed truth because it is indeed roughly true -- more people together in a vehicle done right will indeed use less energy per person and less road space. But the "done right" is very important as it is commonly done quite wrong.
As I have studied robocars, this has led me to the discovery that some of our old assumptions are wrong. In particular, more sharing is not always good, and the styles of sharing (including the vehicle sizes) of current public transportation are almost certainly not the optimum sizes, and that smaller vehicles are likely more optimal once we eliminate the need for drivers and move to a highly communicating world.
I believe there are strong arguments that while shared travel is beneficial, we actually have too much of it in most transit systems, and not enough in private cars. That the 'shared' future is one of van-sized group vehicles with a mixed fleet of more personal cars with 1-4 seats."
This seems like the inevitable conclusion: autonomous cars bring you from your house to your destination, unless you are traveling through a thoroughfare. In which case they will drop you at a tram (ideally drop you at the platform), the tram gets you through the bottleneck, and another private car will take you from the tram stop to your actual destination.
There’s no efficient way for busses to get people close to their door. It makes no sense. Mass transit should relieve congestion on major routes, it’s not an efficient solution to the last mile problem.
From an economic standpoint, investing in fast mass-transit (e.g. high speed rail) would probably result in a larger net positive than self driving cars. Why?
1. I would theorize that the economic benefits of transportation are directly proportional to how fast the service is, and how much people it can move. As an estimation, I'd say cars are limited to 60 mph while high speed rail would be limited to 200 mph.
2. With fixed-path mass transit, the problem of traffic is greatly simplified. Self driving cars may solve a labor issue but they won't solve the traffic problem: cars routing themselves selfishly will not result in the lowest travel time possible. You can argue that a central coordinator can exist to coordinate routes, but if there's an incentive for a person (not necessarily a driver) to deviate from their set path, why wouldn't they take it?
rail and bus infrastructure is never going to be feasible in the small town in Texas where I grew up, 1.5 hrs from Ft. Worth. Not to mention all the even smaller towns in that county and the counties around it.
How is one supposed to move 3 horses across the state using rail and buses?
What about my parents driving to surrounding lakes to kayak? Just cary that on a train that for some reason actually goes to these lakes in the middle of nowhere?
What about hauling larger personal watercraft? Just don't do that? Store it at the body of water you've chosen to exclusively use your boat/jetski on?
Rely on Amazon to handle the logistics of shipping hay for your livestock?
Maybe these are all just cultural things that need to disappear and be replaced by magical super-efficient factory farms or not replaced at all. But there are other ways of life than just living in an apartment and commuting to an office.
No offense, but this conversation is not for you or your family. The car is the second best thing that ever happened to rural life, after the tractor, and nothing is going to change that.
There’s no reason for rural America to act like these ideas are crazy, nor for urban America to act like these problems are universal. So often these two sides act in opposition to each other when they really have no conflict with each other - except perhaps that both side has a hard time relating to the other lifestyle.
FWIW those 62% live in "incorporated paces" or cites, which would include my town (as long as I'm understanding that correctly.) Down under "new incorporated places" it mentions Sandy Point, TX, population 200. It's crazy that even including little towns like that you're still only talking about 3.5% of the land.
I think it also speaks to how relatively solvable some of the urban problems are in the sense that we could be intentionally building new cities (not just attached suburbs) if we wanted to, and that would - if it worked - take some of the pressure off the places that are struggling right now.
For whatever reason America just stopped doing that after WW2. Maybe it’s time to start again?
The really meaty space of "cool impactful stuff we can do now" are all organizational problems, not engineering. How do you organize 10k people to build a new city, get them to agree upon a basic design and location, and then get them to actually go do it? There's nothing really stopping you.
Of course there are going to be wide swaths of the United States where passenger rail and bus service isn't going to make much of a dent for local transportation.
Regional transportation is an entirely different question. Is there a rail line running through the small town in Texas where you grew up? I bet there is, and I bet there is the remnants of a passenger station too. What would it mean to your small town if people could easily commute by rail to the bigger city 45 minutes away? I bet people would be more interested in living in that small town.
There is a rail line, but no passenger station. Realistically there would be 1 train per day max to the big city and you'd have to spend the night instead of making a day or half day trip. (I currently live in Durham and I can catch a morning train to Charlotte and back in the evening according to the schedule, as long as I can fit my business in between the arrival time of the morning train and the departure time of the evening train, and that is servicing two much larger populations.)
And that is just going to the nearest larger city... What if you want to go to a different city? Or a smaller town? Or a random place that doesn't have a bus station?
For a data point on this, I'm in the Waterloo region, about an hour's drive into Toronto when traffic is good, or 2-2.5 hours when it's not. The government regional rail (GO Transit) operates four commuter trains into the city on weekday mornings, and four back again in the evening.
Despite being slow and expensive, those trains are packed, day after day, with commuters who would rather live out of the city, and not spend 15-20 hours of their week sitting in traffic on the 401. They recently extended two of the trains with additional carriages to handle the capacity.
We've been clamouring for hourly bidirectional service for over a decade and it's only in recent years that the relevant authorities have finally gotten their act together to build out the necessary infrastructure to make it possible (twinning a bunch of track sections, building a bypass for US-bound freight, and electrification).
We're talking about commute and long-distance travel. In most scenarios, you don't carry that much luggage. You don't carry your horses and kayaks when you go to work or travel overseas.
> but all the people who are barely making it who's lives fall apart if something on their car breaks.
Maybe people need to take personal responsibility and not spend money as if the government will make things easier for them and solve all problems. I am not claiming this is possible for everyone there are truly people who need help. But the vast majority of people can try to live in a way that they can have personal transportation (which has been around how long now?) and is reasonably enough priced currently.
Separately back before autos wouldn't people have had the same issue with horses or with even machines that they needed to run their lives or their business? Isn't it part of being human to plan for breakdowns of various things that you need that you can plan around failure?
I suspect that if someone could deliver a fully autonomous car at say 2x the cost of a regular car, the next immediate problem would be massive autonomous traffic jams where you would still need mass transit to work back scaling costs on the transport networks.
At least now the 4 hours you spend in traffic every day can be useful — catch up on some sleep, check your email, train your car's AI by playing "I spy"...
That's at the heart of the problem. Once traffic time is lower 'cost', then people will likely immediately start spending that savings. A one hour acceptable commute becomes shifts to 4 hrs being acceptable, and you get maybe 4x more traffic into the same commerce centers.
> America could build up municipal rail and bus infrastructure to ....
I don’t think the killer market for driverless cars in America in the first place. Places like China that have all that (commuter rail, subway) but lack places for new roads and parking would benefit greatly from optimizing their limited road infrastructure. They already have people who are used to taking taxies everywhere, now make the ring roads automated only to triple their capacity.
Europe, Asia, can be benefit greatly from driverless cars because they have a different situation from America.
I love the idea because it would remove the need for me personally to own a car. Also it was supposed to happen in the scale of a few years, instead of the decades needed to build the heavy infrastructure projects you mentioned, but remains to be seen. Also, it could quicken the move to electric vehicles if uber/waymo etc fleet was all electric.
I think driverless has the potential to be both - we can have a bus system that runs dynamic routes based on the users that are going to ride it and runs closer to ideally efficient vs. a fixed route that is likely inefficient.
we can have a bus system that runs dynamic routes based on the users that are going to ride it and runs closer to ideally efficient vs. a fixed route that is likely inefficient
This doesn't seem to require driverless busses. I can see an argument of why self driving taxis would be helpful -- cost of labor is near zero -- but with busses, the cost of labor is amortized across passengers.
Driverless trains are not a problem to begin with. If you have a train and it carries hundreds of people [or trainload of cargo], it is economically irrelevant whether it has a human operator or not. So it is safer to have a human there just in case.
The tech for automated road trains is vastly closer than where self-driving cars are. If you feel this way about trains, then you should feel the same way about highway-specific automobile autonomy.
We also need to focus on the actual problem we're faced with. Cities are hitting limits to growth due to congestion and we can't build more roads. The state of tech right now is capable enough to solve that problem by increasing the throughput of the major arteries of LA / DC / etc.
"in most of America we need to get back to the point where cars are no longer a necessity" - ...because why? I am assuming in good faith you might say:
because a world in which a greater proportion of people travel via multi-passenger vehicles like the buses and trains of public transport networks is a better world because these transportation solutions are 1) more efficient per passenger (does this help w/ reducing carbon emissions?); 2) economically more accessible because passengers pay per trip instead of purchasing vehicle outright; 3) potentially less expensive to operate due to economies of scale (purchasing & maintaining a large fleet of vehicle vs a single vehicle) and higher equipment utilizationl; 4) perahaps encourage more social connection amongst passengers; 5) passengers do not have to focus on driving and can "recover" the time that would have been spent driving a car doing something else.
I ask because I think the endgame for self-driving car companies is not so much to sell cars (self-driving in this case) to individual consumers, but rather to to win the zero-sum-game of becoming the largest on-demand "elastic" self-driving vehicle transportation platform; i.e. 80% of the cars Ford makes in 2030 it reserves for its automated fleet, which it dispatches on a per-ride bases to subscribers/customers for a single trip, a day, a month, etc. The ultimate technological opportunity here is effectively "packet switching" for physical transport via the highway network.
While it's possible (and desirable, in my opinion) the fleet of vehicles enabling this automated transport network could be a composition of myriad different vehicles, from many different vendors, contributed dynamically by everyone from families (or groups of families) that own a single vehicle and rent it out when its not in use to the fleets of large companies like ups, hertz, ford, etc...
it seems more realistic that a few giant companies (Waymo, Uber) will be the ones that can scale up a working network fastest and cheapest by building, owning, and operating huge fleets of vehicles made up of just a few vehicle variants.
Anyway, imagine 60% of the cars on the roads today were capable of participating in an automated-vehicle-on-demand transportation network. This scenario seems like it has the same benefits I attributed to public transportation. What do you think - is it an equally desirable solution, or are there other particular benefits to a world with significantly more (conventional) public transportation / less cars that I failed to articulate?
> are there other particular benefits to a world with significantly more (conventional) public transportation / less cars that I failed to articulate?
- Substantially reduced traffic on surface streets (a bus or subway is MUCH more densely packed with humans than a road full of cars).
- Encourage more walking and overall fitness
- Improved safety for non-mechanized road and sidewalk users (reduced traffic will do more for pedestrian safety than automated traffic will, I promise).
- Less space required to be devoted to parking and streets, so better land utilization.
Ok, fair enough - for urban centers. Although to your first point, lets go farther and say that 50% of core city streets could be closed to traffic and repurposed for walking/biking pedestrians.
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So... this got really long. It was just supposed be a quick back-of-the-napkin sanity check estimate of the economics of some rural autonomous vehicle service scenarious and it got a little out of hand. If anyone else also finds this interesting, drop me a line or comment!
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Lets also consider the merits of these two transportation scenarios when depoloyed to serve regional/rural populations too. I don't think any of these benefits are significant for the other much less dense half of the US population (but by 2033 or something this fraction will fall to like 1/3 I've heard).
I grew up in Northern Michigan, where 99% of all daily trips were between 5-40 miles and required a personal car because there was no availability of taxis (too expensive per ride) or buses (because population density was too low to marshal enough passengers per bus route). In cities, where density is high and distances are low, buses/trains that batch passengers into one vehicle that's part of an interchange network works pretty well. But in rural areas where the opposite is true, passengers can't be batched together as easily, so buses don't work and an interchange takes too long to transit because of the distances.
A personal car is a necessity for most people living in rural areas because there is no other practical way to get to a job, store, movie, friends house, hospital etc when these locations may be 10-40 miles away. The time spent traveling to these places may be about the same as the commute time for a city-dweller, but rural residents have to do the driving themselves. Aha, so the critical question is: what, if any, features of personal transportation via on-demand self-driving-cars-as-a-service in rural areas might make it competitive with or more desirable than owning a personal car?
If costs per year are roughly equal, then I would love a self-driving car that I could work in. Or self-driving land-yacht office RV for 4-8 people.
Say a personal car costs $3000-6000/year in gas, maintenence, payments, etc. If a person travels 200 days a year and takes 2 trips a day, that's 400 trips a year. This is hard to estimate. To be conservative lets say self-driving-cars-as-a-service would be competitive if it allowed a customer to take 400-800 trips a year for the price of owning a car. That works out to $3.75-$7.5 per trip for the ex-owner of a cheap car, and $7.5-$15 per trip for the ex-owner of a mid-range car. I guess if these are electric self-driving cars, the fuel cost might be $0.50-$2 per day. Hmmmm. If the vehicle cost ~$50,000 and the profit per ride was $4, then it would take ~12,500 rides to break even. If a vehicle can get 10 average fares per day, 350 days a year, thats 700 fares per year.
So actually, the economics are not toally insane. At $4 profit per ride, it would take ~2 years to break even on a $50,000 vehicle assuming 10 rides a day that that take 1 hour, have a rider only one of those two ways, and only have 1 rider at a time. These vehicles might be operating at 20 hours a day though. Not sure they would last 2 years. So... what startups are working on self-driving Land Yacht Office co-working-commuting vehicles?
Now I see a significant portion of the fleet should be something that could pick up at least a few passengers along a route, otherwise there would need to be basically as many vehicles in the fleet as there are riders to support solo rides during commuting hours. $200,000 land yacht, 5 riders, $5/ride: 8000 trips to break even, 10 rides a day = ~2 years. But for a region of 40,000 riders, that might require 5000-8000 land yachts that cost $200,000; so $1-1.6 billion in vehicle costs. Aw man. What's ubers valuation? 70bn? And goog is 820bn? hmm.
Ah so here's the problem. Because of the distances involved in rural trips, it might take 15-60 minutes after requesting a ride for an automated fleet vehicle to travel to the pickup location. That might be ok for occasional travel, especially if trip times are 3+ hours, but it wouldn't be convenient for daily travel. So rural passengers would probably prefer owning their own car, or sharing an automated land-yacht with a couple local other folks, because they need it to be physically nearby most of the time to minimize the time-to-pickup.
In conclusion, InitialLastName's comment leads me to imagine a future in which the dense core of urban areas is served by high-capacity public transit, a significant portion of the central surface streets are closed and used for other purposes, with small-vehicle parking and pick-up/drop-off hubs are sprinkled throughout and around the city that link transport throughtout the wider region and state via privately owned vehicles (for daily commuters) and automated on-demand vehicle fleets (rolling offices) for the ocassional traveler.
Personally, I find it hard to do productive work on public transit, largely because transfers interrupt continuous work and the passenger compartments prioritize density over work surfaces. I think I would be ok paying 2x the fare of public transit for a trip that took 1.5x as long if the vehicle was outfitted with normal office furniture (desks) ~6 passengers. A relatively low-density vehicle for its size, scheduled a couple of hours in advance, providing a hub-to-door trip with no transfers. Ha. Yeah. Self-driving-land-yacht-office-as-a-service company?*
* we could validate it right now... SF <-> Palo Alto, 6 round trips per day per vehicle, 6 passengers per trip, $19 fare, $200,000 vehicle cost, $19/hr for driver, and lets ignore fuel costs. So say revenue of $600/day, that leads the vehicle break-even within a year. hmmmmmmmmmmm.
It's amazing the serious face some people keep "re-discovering" 100+ years old, derived from basic principles technology. The ultimate of this is the autonomous truck convoy: wouldn't it be amazing if we could just have trucks follow each other closely and save a ton on air drag?
Well, yeah, it exists, it's called a train, it's magnitudes longer than any "autonomous truck convoy" ever will be, and instead of the billion dollar AI machine learning big data system we have to keep them close together, we use a fricking mechanical linkage.
America’s economic bread and butter is innovation. We’re creating an entirely new market segment. That’s why new driverless cars are far more attractive than improving public transport infrastructure.
municipal rail is a money sink. currently across the nation there is over a hundred billion dollars of deferred maintenance on municipal rail; light and heavy. worse bus service tends to suffer because they try to force people to use rail by making bus service less attractive which in effect is just damages the concept of public transport.
no the real solution is get over this mythological idea that America is too car heavy. everywhere that people get freedom of travel they go their own transport. what automation will bring is freedom to those who cannot drive so we best better figure out how to get cars talk to each other and which areas will be reserved for automated driving only.
funny you mention Seattle, a city that blew over their recent rail budget by half a billion dollars [1]. plus is it also a city deferring maintenance to hide the costs of their folly.
It seems that way because the costs are centralized, but cars are as well, and it's disingenuous to compare this way.
If you look at how many people go in debt to own cars or the amount of credit on cars, you would see poor numbers there as well. Cars are incredible money sinks. There is a reason why Uber doesn't operate its own fleet.
If public transit billed by value it would easily be kept afloat. But the value proposition in most cities in America just isn't there, because they simply aren't dense enough. It's not a mythological idea. It's simple math.
> funny you mention Seattle, a city that blew over their recent rail budget by half a billion dollars [1]. plus is it also a city deferring maintenance to hide the costs of their folly.
Funny you mention things going over budget because nearly all infrastructure projects in this country do - yes, including roads. This is a problem with our government, not mass-transit solely.
In your very own article, the reasons stated for the price increase have nothing to do with mass transit inherently. They would be true of any infrastructure project.
By way of contrast the Millau Viaduct[2] cost approx. €400 million and the Øresund Bridge[3] cost approx €2.6 billion — and represents an order of magnitude more engineering challenge.
Civil engineering in the US just seems to cost a lot more than in other developed countries.
> everywhere that people get freedom of travel they go their own transport.
They have freedom to travel, but not freedom to live where they want. The United States has entirely banned dense housing in everywhere that people want to live, and this consequently makes transit impractical. Get rid of zoning restrictions on housing, and we'd be in a much different place.
In level of stupidity, the concept of self driving car in my opinion is second only to a flying car.
The second disregard, that well... there are airplanes.
The first, that driverless busses that creep at 30km/h and do emergency brake every every 10 minutes thanks to overattentive collision avoidance system also been around for decades.
We've had flying cars for decades. They're called helicopters. Unfortunately they're much too expensive for the masses. But I don't see why anyone would consider the concept stupid.
My point is that the popular image of flying cars with retractable wings and wheels turning into jet engines is ludicrous, and that yes, light personal airplanes and helicopters are there.
And the same parallel for driverless car, except for even when well executed it is kinda of arguable usefulness/value.
Are regular cars useful? A self-driving car is just as useful for someone who can't drive: minors, many seniors, many people with disabilities - or people who just don't have a driving licenses, like me.
For them, a 30km/h crawler with overattentive collision avoidance system may well be useful. This is not much different to how public transport drivers have to drive.
I expect them facing same issues like trams and trolleybuses - terribly bad experience in traffic.
You only see risky people aggressively trying to overtake and scratching their paint, while leaving the driver no opportunity to move an inch.
A self-driving car is a mobile monitoring station; every such behavior will be closely tracked, recorded and possibly shared with the authorities. I think those drivers will learn to stay away from them.
"Driverless car" is probably not the outcome for autonomous vehicles. At one end of the scale, cities will use road space vastly more efficiently with optimized vehicles for groups of riders, and at the other end of the scale, short-haul air travel will be challenged by door-to-door 150mph+ highway vehicles. None of these will look much like a personal car, and only the wealthy will consider owning one that will become rapidly obsolete and have a meagre duty cycle a sensible idea. For many people the answer will be a bicycle because the roads will become a safe place for cycling.
This assessment of the state of play is very uneven. For example, the assertion made by Meredith Broussard quoted in the article "It’s also not true that we must transition to self-driving cars because human-piloted ones are so lethal" is a truism. The article goes on to say "Countless innovations have made cars radically safer since the 1950s and continue to do so."
Yet vehicles remain as lethal as dread diseases, mostly down to the humans piloting them. Just cutting that number of deaths and injuries significantly would be a boon similar to eradicating malaria.
I expect the flourishing of autonomous vehicles to be sudden and unanticipated. Just as you can't tell unless you are looking for the decals or attuned to why back seats are suddenly more populated you might miss the fact there are two million ride share drivers in the US now. One day we will realize the wait for a bus is much shorter because busses are right-sized and more frequent and can surge where they are needed because drivers aren't a bottleneck and routes are dynamic.
"Our love affair with self-driving cars is a form of 'techno-chauvinism,' Prof. Broussard says. 'It's the idea that technology is always the highest and best solution, and is superior to the people-based solution.'"
We like the idea of technological solutions that don't require us to change our lifestyle or make hard choices. Driverless cars are appealing because they would allow us to largely maintain the status quo (as opposed to, say, reorienting toward public transportation). It's like an obese person who says, "I don't want to eat healthy and exercise. Why can't scientists just invent low-calorie versions of the food I like?"
Really? I don't like to fetch water from a lake every day to my house. Instead of using technology to bring water to my house, what lifestyle changes or hard choices should I rather make?
The bigger problem, IMHO, is the attitude that it's some kind of moral quandry if technology allows us to solve a problem without effort. For example, I've heard people really say that an obesity-preventing drug would be a bad thing because it would discourage exercise. This fetishization of hardship does a lot of harm, because in reality, the kind of progress we can make as a civilization essentially amounts to refocusing exertion on increasingly impactful things.
Other examples of this phenomenon:
Direct atmospheric carbon removal is bad. It encourages emissions!
Contraceptives are bad. They encourage sexual license! (I had to try to avoid the obvious joke here.)
Highways are bad! They encourage driving.
Word processors are bad. They discourage good penmanship!
Fertilizers and farm equipment are bad! They discourage small family farms!
GPS navigation is bad! It discourages map reading and mental direction finding!
Some of these examples look ridiculous to us now, but people really did think these things at some point. I see some opposition to autonomous vehicles falling into the same category.
We like the idea of technology improving our quality of life because as a civilization it's worked for us spectacularly so far. Driverless cars are appealing because they build on top of a transportation solution that already works, reducing the problems and externalities of it, without requiring us to completely overhaul the way we build cities and live which could take decades. When half of the world lives in remote or insecure areas, driving vs public transport is not a lazy lifestlye choice like eating poorly. Autonomous cars will also bring about a lot of new use cases which could improve public transport design, reach and usage, like driving you to a metro station which has no parking in the morning and picking you up in the afternoon.
And as a society we reject a lot of possible technology out of hand.
For example, we could have a device on cars that transmit basic information. Such as licence ID number, speed, location, pedal position etc. It would be ridiculously useful data for a whole host of different things. You could use it to bill parking, catch speeders, sequence traffic lights, and warn of hazards ahead. And maybe even help self driving cars make sense of the world.
From a technological point of view this is a no-brainer. But this is incompatible with the way that we think about cars and roads. Every car has to pretend to be isolated from every other car.
> From a technological point of view this is a no-brainer.
Yeah, it becomes a brainer, though, when you ask “how do you deal with malicious transmitters”, since the answer to that tends to involve developing the systems to monitor the same variables externally without trusting the transmitted values, and once you do that, what is he transmitted data for?
Using transmitted data for less safety-critical things like route intent for efficient holisitc route optimization, with a penalty system for misrepresentation might be useful, though.
I think that safety critical systems need to deal with bad data anyway. Adding an extra level of redundancy makes sense.
Maybe you could have a lower power transponder style technology in addition. This would just broadcast an ID after a fixed amount of time in response to a request. This could be compared against radar,visual, and broadcast information to actively verify data. And critically it could be independent of the rest of the cars systems. Obviously that is not a solution, but it does add another layer of redundancy
Redesigning cities to be less reliant on cars is pretty much a solved problem. It just needs a few decades of focused policies. Check out for example how the Netherlands became bike friendly by relentless improvement since the seventies.
Ebikes make most cities flat, and the Netherlands only relies on bikes for last mile transport. Medium and long-haul routes in the Netherlands have great transit options.
But human drivers kill a lot of people. It would be a shame if that's the best we can do. And some car tech improvements have saved lives, so it's not necessarily chauvinism it's just extrapolation.
As long as the U.S. personal-injury legal system remains in place (with strong support from media coverage of fatal crashes), it won't be enough for self-driving systems to have lower death rates/mile in aggregate. They will need to be better or equal to human performance in every subcategory of driving. That's really hard.
To wit: It's not enough to say "Our self-driving cars avoid 14,000 drunk-driving, texting and asleep-at-the-wheel fatalities," if it's also true that: "Our self-driving cars hit and kill 30 errant pedestrians a year that a human driver would have noticed."
I know that 14,000 > 30. But the specter of roadway martyrs being murdered by killing machines needs only a few examples to sustain itself.
It will very likely kill far fewer per mile driven than humans do. Unfortunately you're right -- it probably still will kill some. Even nonfatal accidents will be scrutinized heavily and leave a lasting impression of fear/loss of control.
I'd wager a relatively small percentage of drivers account for a relatively large percentage of deaths. Reckless driving, not driving as conditions permit, intoxicated drivers probably account for the vast majority of road fatalities, either directly or indirectly.
I don't believe a computer will ever be as good a driver as I am in my lifetime in terms of my personal safety, except for when I'm really old and possibly can't see well.
That's totally unproven, the technology doesn't even exist yet and we're still assuming we know what it will look like. In their current state self driving cars would kill far more people than humans if all cars used self driving 100% of the time, and no one knows if we will ever move past that.
Despite the imperfect technology, I'd bet that if we could somehow make all cars autonomous today (with current tech) and network them all together, it would drastically reduce both accidents and fatalities.
The vast majority of accidents by human drivers are caused by basic neglect, not tricky edge case situations. I think it's hard to really comprehend just how bad humans are at driving. It wouldn't take anything close to a perfect autonomous system to do better--just having "drivers" that actually pay attention to their surroundings all the time would be a massive improvement, even if there were occasional bugs and glitches.
> In their current state self driving cars would kill far more people than humans if all cars used self driving 100% of the time, and no one knows if we will ever move past that.
Really? No one knows if we will ever improve on self-driving cars than the current technology today? I'm going to stick my neck out and say "Yes, I know that will move past that."
>I wouldn’t say speech recognition is solved. It’s still quite error prone.
Sure it is, but it's doing a hell of a lot better than many critics thought ever possible.
>Self-driving cars need to be even better or people will die.
People will always die. Requiring with certainty that self-driving cars will never cause accidents is a purely emotional instinct with no regard for facts or well-being of people. The only thing that self driving cars need to demonstrate is statistically lower deaths or injuries caused per mile (or hour) of driving than the average human would cause. This would mean that adoption of technology would reduce total deaths if substituted for human drivers, which is what actually matters.
>Self-driving cars need to be even better or people will die.
He is right - the problem with your response to this statement is that it doesn't identify the _actual_ reason behind why they need to be better, and it's a problem identified by the article in question: When a human driver swerves randomly and kills someone, we know EXACTLY who is to blame, and something can be done. If a driverless car, or even a car with "driverless technology" that also has a driver in it (like the Tesla driver mentioned in the article) hits someone and god forbid kills them, we still have no idea who is to blame for that problem, because it practically becomes a marketing argument in some cases.
Before we can be okay with driverless cars, ESPECIALLY if we don't plan on them being 100% accident free, we need to solve a lot of ethical and legal battles that don't seem to be even on the minds of the people that tout this as the future, or a necessity.
Nobody will accept liability for actions outside of their control, and car manufacturers can not possibly afford to insure all cars they sell in perpetuity.
Insurance only works if the insuree bears the risk (and it has to be an actual risk with nonzero probability times cost, i'll leave why as an exercise to the reader) and in the case of car accidents, that risk is liability, which people have and computers don't. Can TSLA or Uber be charged and convicted of vehicular manslaughter?
Lower rate of accidents will just lower the market rate of insurance contracts.
> Nobody will accept liability for actions outside of their control,
Sure they will. People pay for insurance now, and the insurance companies will give you a discounted price for your self driving car insurance.
Why wouldn't I want to accept liability in exchange for a cheaper policy? I would win as well as the insurance company.
The benefit is clear. And this is an exchange that many many people would be willing to make if it meant that their insurance prices were cut in half. It's free money to the consumers.
You are treating this as if this is some new problem. Your car can already have the wheel fall off, due to no fault of your own, and you'll crash, and the insurance company will pay for it.
> Nobody will accept liability for actions outside of their control, and car manufacturers can not possibly afford to insure all cars they sell in perpetuity.
Car manufacturers already, in the US, bear strict liability for damages resulting from manufacturing defects in perpetuity, and bear the cost of that liability either by self-insurance or some form of liability insurance contract.
> Can TSLA or Uber be charged and convicted of vehicular manslaughter?
Irrelevant to the insurance issue, since criminal penalties are uninsurable; more relevant is can they be held civilly liable for wrongful death resulting from a defect in a vehicle they make, to which the answer is clearly “yes”.
If we look at humans as a counter, sure, apply all the stats you'd like, but I don't think we should do that when it comes to self driving cars.
if we simplify the driving risks, we have:
1. driver kills him/herself
2. driver kills person outside his/her car
* Humans and computers can make mistakes on both.
But, my wife and I can teach our kid everything we have learned over the years, to prevent 1, and try to reduce 2. I consider ourselves better than average drivers, if I get my kid a self driving car that is not as good as us, I won't care that it drives better than my neighbor or someone in California.
And in a tragic scenario, it's one thing to say, my kid made a fatal mistake vs, some random QA didn't do a good job and now my family is minus 1
Everyone thinks they are good drivers, yet hundreds of thousands of people are dying every year because of these "good drivers." Not sure what makes you think that teaching your kid what you know will make them a better driver than software that will continue to be iterated on and improved based on millions and millions of miles of data (more data than you and your wife could ever pass along to your child). Also not sure why you think your own driving will be better than self-driving cars.
Exactly. People used to think computers will never beat humans in chess, clinging to all sorts of romantic notions such as that inherently human understanding was required for high-level play.
If you care about traffic safety and take steps to be a safer driver (minimize distractions, pay attention, don't drive while under the influence of drugs, including alcohol) then you are almost certainly not a significant part of the problem. The problem is other drivers, whom you have no control over, and who can ruin your life at any moment with sheer carelessness and with few consequences.
By that logic, we should be putting all the money we're putting into driverless cars into getting more people to travel by bus, rail and air, all of which are a much much better than marginal improvement in terms of deaths per person-mile.
You are absolutely correct. That would almost certainly reduce deaths, and I would support taxing myself more for more money to go towards safer public transportation to reduce traffic fatalities.
I will, at the same time, support self-driving car research.
I think Musk notwithstanding, folks who are actually developing ADAS technologies are not* really touting driverless capabilities – that's the ultimate goal but the genuine projects today are focused on HD mapping and image recognition from cameras to overcome the LiDAR price hurdle.
OEMs are very interested in startups working on those specific issues, but for various reasons these incremental steps aren't as widely reported so all we get left is the hype that self driving cars "are here" and things like Tesla Autopilot
The argument that autonomous tech will save lives is the most dangerous. This will take decades to be true.
The same companies who are pushing for that narrative, are also the first ones to blame the drivers when their tech goes wrong.
There’s so much data fudging to push for those narratives — they want the credit for lives saved, and at the same time don’t want the blame or liability for accidents caused.
Or maybe we hold driverless cars up to an unfair standard. Today, 3000 people die in the US every single day because of car accidents. Many, many more are injured or disabled.
Why would we expect driverless cars to reduce that to 0? Shouldn't it be good enough if they reduce it to 50%? 25%?
> Today, 3000 people die in the US every single day because of car accidents
Whoa... that's over 1 million people annually... you probably mean globally?
Depending on the year, it's somewhere between 30,000 - 40,000 annually[1][2][3], or in the worst-case, about 109 people daily in the US.
When you examine those numbers further, you'll see about 10,000-18,000 (depending on the year) are sadly still alcohol related[4]. We can and should fix this first and foremost.
With over 3.1 Trillion miles driven annually in the US, that's about 0.001 fatalities per 100,000 miles driven, or about 1 fatality per 80,000,000 miles driven. Driving is pretty safe - although I agree we can make it safer.
Unfair? Why should a technology touted as the future be half-measured to something as "50%", as just "good enough"?
When you have the human element at play, fault is easy to judge, as is blame easy to lay. When, say, a drunk driver is involved, it's clear what the problem is, and the state can fund enforcement against drunk driving and take other measures to reduce accidents. But with driverless cars, who does the victim and/or the victims family blame? What can the state and law enforcement do when there's nothing to prosecute besides some corporate entity (and possible laws that protect it) and a faulty algorithm or similar? The human element is no longer at play, and instead there's a car manufacture, protected by decades of lobbying, deciding what is safe enough to unleash on the populace. It's pure negligence to release driverless vehicles onto the roads simply because some statistics show it's "50% safer, thus safe enough".
Note that the 3000 daily deaths is worldwide, not just the US. The daily US total is about 100. I do agree that any improvement on those numbers with AI should be applauded.
Waymo have driven 8 million miles and had one minor accident that was the cars fault where it thought a bus would give way and a dent resulted.
I've driven about 200,000 miles and done considerably worse including two cars written off, though no injuries. I'd say Waymo seems safer than me. And judging from my insurance premiums which are low, I'd be safer than the average human driver.
Waymo alone is fine, but when you take into account fatalities caused by others like uber, right now I think self driving cars are worse than humans by a pretty large amount.
Driverless vehicles are "the new fusion power".
Always "about 10 years in the future".
>Driverless cars are coming along just fine.
Even if this were true it doesn't mean humans will be fine with them being deployed. We had working driverless trains 20+ years ago yet almost none are deployed today (AND we have plenty of human-caused fatal train crashes that might be a good reason to want driverless trains).
Except Waymo is being used by real people in Phoenix right now, albeit on an invite only system. They've said they'll go public by next year, and expand to other cities afterwards. Most of what is blocking them is regulation. I'd predict that by 2025, they will be in at least 10 major cities, regulation willing.
While I am still waiting for my Tesla Model 3 SR, I browse the Tesla forums and find it amusing (or maybe just sad) that Tesla is charging $5000+ for Full Self Driving (FSD). Owners are paying for the future possibility that the car will be "conducting trips with no action required by the person in the driver’s seat" [per Tesla Model 3 ordering page].
I think some Tesla owners are even expecting that their car will go self work for Uber over night, generating the user income. Other customers seem to be paying the fee, yet they are just leasing their car. Will these leasees ever see any significant FSD features?
This article gets it right that self-driving is way, way off. It will be interesting to see what and when Telsa delivers to its customers who prepaid for FSD. I think Tesla already settled a lawsuit with some owners over self-driving fees and associated delays.
Ha! I can just see the teenagers blocking the car, covering cameras with paint, and leaving an empty Tesla in the middle of a busy intersection for the cops to deal with. Pranks for the future generations are going to be really interesting.
I think it’s important to distinguish between a self driving car that can work in every scenario, and a self driving car that can take over part of the time. Personally, if someone could make a car that was extremely good at highway driving so it could sit in traffic for me and drive on the highway (basically if Tesla autopilot actually worked and was 99.9999% safe) that would be AMAZING. that’s good enough for me. I don’t need a car that can self drive in the snow.
The people who argue that driverless cars can't match humans have a real double standard going. They talk about all the conditions like snow and edge cases that driverless cars can't handle now.
But they have nothing to say about all the real conditions that everyday make human-driven cars unsafe, like lack of sleep, alcohol or illegal drugs, youthful showing off, road rage, texting, arguing with a passenger, old age, poor vision, and so on.
Remember, the problem is not to make driverless cars perfect, it is to make them as good as humans, and that is much easier.
Also, let's remember, the transition to driverless cars will not come all at once, with all vehicles handling all conditions. Instead we will gets lot of partial, easier cases, like a truck that drives only along a well-mapped route, or people using it only when weather conditions are reasonably good, and so on. As the AI and sensors improve, new uses will be added, until eventually we get it to be universal, or nearly so.
And finally there is the likelihood of infrastructure improvements to make it easier.
So want we are going to have is not suddenly one day driverless cars take over, rather a gradual increase in their use.
Generalized self driving cars seems like such a hard problem, laced with a huge amount of hard to handle edge cases and a huge amount of hard to enumerate possible scenarios.
I think it will still happen, but they need to simplify the problem. The way to simplify it is to create automated driving lanes, similar to the current HOV lanes, that have standardized markers that are easy for computers to read, and then eventually extend it to automated driving routes.
That will take some amount of buy-in by the government to install, but I have faith in our well paid lobbyists.
Afaik, highways in non-severe weather are already pretty much solved, so I’m not sure that special lanes would make much difference, except perhaps during snow storms.
The edge cases seem to be mostly around city driving, rural back roads, and bad weather.
> highways in non-severe weather are already pretty much solved
And yet all the automated driving driver fatalities have been on the highway, with the Mountain View crash in particular having been caused by weathered / confusing road markings.
I wouldn't consider that solved at all.
But to the larger point, self driving lanes would only be a first step. Eventually it would develop into a standard set of markings and signage for automated driving friendly roads so that you could safely have self driving cars in things like snow storms.
There's no need to limit it to highways only, although there I think there is some benefit in the near term to segregating automated driving cars from human driving ones.
Just like teaching humans to drive. Yes, sure, you have to show them how to do it on the highway/BAB, driving safely at 130+ km/h, but it's really not hard (over long distances things you can't really teach make it difficult). City driving on the other hand takes time to master; here easily 80 % of the driver education is done in cities (0-50 km/h).
Practically all the edge cases, all the difficult situations and complex maneuvers are done in cities. Outside cities driving is very simple and safe (if you stick to the limits).
Automotive industries never had problems with attracting taxpayer’s money. Graduating the car from break-clutch-engine machine to airliner level of complexity vehicle is a perfect money sink.
I'm still skeptical that this will happen anytime soon outside of selected small zones. I may be wrong, but I feel like the US or wherever these get deployed need a major infrastructure update to be better or more consistent. Even with the most advanced automated driving system imaginable you will still have poor and inconsistent infrastructure everywhere.
Seems like a good interim solution is to build infrastructure for designated "driverless" lanes. I assume there's a good reason why this isn't being pursued though?
If you factored algebraic expressions in high school, and you agree that the "re" prefix generally can be added to a verb, then it's already part of your lexicon.
The process of code refactoring, especially extracting common code into a method, is very similar to the process of simplifying algebraic expressions. So it's not just a grammar argument; the two words really do represent related concepts.
The web link to google often doesn’t work to find the non paywall version anymore. I’d be happier having a setting in my HN profile that ghosted these publications.
I can't read this paywall article, but here are some similar counterpoints to hype, starting in 2016. They are from people actually working on self-driving technology or executives/investors close to it. (I'm interested in any earlier "expectation setting", having heard a lot of this at Google.)
March 2016:
Chris Urmson: How quickly can we get this into people's hands? If you read the papers, you see maybe it's three years, maybe it's thirty years. And I am here to tell you that honestly, it's a bit of both.
Those who think fully self-driving vehicles will be ubiquitous on city streets months from now or even in a few years are not well connected to the state of the art or committed to the safe deployment of the technology. For those of us who have been working on the technology for a long time, we’re going to tell you the issue is still really hard, as the systems are as complex as ever.
I wish cities would create zones specifically designed around facilitating autonomous car operation. For example, there's zero reason to allow random private cars in Manhattan south of 96th street. In a small, dense area like this, it should be possible to optimize around the limits of current autonomous car software.
I think the car manufacturers will, in the end, win out with the continued, steady progress of smarter and more capable driver assistance systems. Cruise control gave way to super cruise with lane keeping, warnings when your back bumper was approaching something gave way to features that stop the car for you before you hit something.
Eventually, the car will be less dependent on the human's attention, as the safety features will make the human's attention less important (while not telling the human their attention is less important), until it's good enough to take over for the human.
I think a lot of the issue is that dream and expectation that "hey, I can just watch a movie, I don't really need to pay attention" is crazy, and will continue to be for many years to come. We need to stop marketing that future.
I was just having this discussion last night as it happens. We sat at an impasse as everyone was quite inebriated and didn't have any real empirical evidence to back any of our claims up. I was rather curious if the rate of deaths caused by human drivers would continue to dwarf those caused by edge cases of deployed self-driving cars if we scaled up the number of self-driving vehicles.
Presently human drivers cause an awful number of deaths with cars. However even despite the edge cases of machine learning, which can be adapted for relatively quickly, would drunk drivers still kill more people every year even if we replaced all of the cars with robot ones? We've been trying for decades to minimize the damage caused by drunk drivers but policies don't seem to have much of an effect. Compared to the massive amount of data we could collect from robot cars in order to optimize them and adapt them... it seems like we'd be faster at making them safer than preventing humans from making poor decisions.
I think in the case of piloting a slow-moving bullet around crowds of humans... I'd trust technology more in this case. It did wonders for the aviation industry and while cars are more complicated to pilot in many cases I don't see how we can make current human-piloted cars safer vs. optimizing robot piloted cars. We've been trying the former for decades with diminishing success.
> didn't have any real empirical evidence to back any of our claims up.
NHTSA publishes the FARS every year. It is their database of every known roadway fatality in the United States. It's free to the public. It's well worth study. Here's an example: Texas has more fatalities than California. Not per-capita, but in total. California has 10m more people living there than Texas. This is not a uniform problem.
> Presently human drivers cause an awful number of deaths with cars.
Yes, a majority of accidents only involve a single vehicle. It is often the case that a driver exceeds their ability or roadway conditions and kills only themselves.
> would drunk drivers still kill more people every year even if we replaced all of the cars with robot ones?
Replaced them with cars that have no manual control option. Given everything we've learned about automation, this is a bad idea given our current infrastructure. So, it's highly unlikely that they will have much of an impact for this group.
> it seems like we'd be faster at making them safer than preventing humans from making poor decisions.
This ignores the nearly 100 years of saftey history that we already have. We have already reduced roadway fatalities by a staggering amount and have created a regulatory framework that has successfully created higher saftey margins for all drivers.
We already drive Trillions of miles every year in the US and we only have 36k fatalities. Further: 6k of those are pedestrians and 8k of those are motorcycles. 7k are young men under 24 and 7k were drivers under the influence. There are not a lot of "easy gains" left out there where it's obvious that self-driving cars will have a major impact.
> I think in the case of piloting a slow-moving bullet around crowds of humans
Which is one thing. However, we're talking about piloting thousands of slow-moving bullets around crowds of humans _and_ each-other. There will not be a single manufacturer of technology, nor will there be a single auto-pilot system.
Plus we haven't experienced any automation failures yet that have caused us to establish best-practices around this system. For example, should the autonomous system have full 100% authority over the cars controls? It may be useful in an accident that the car can use full authority to avoid an accident. It may be disastrous in a situation where the car has bad data from it's sensors. So, should we limit control authority to reduce the opportunity for failure here and also leave some margins for a human to override the machine? Will drivers actually understand the complicated and subtle difference?
What happens when we need to roll out regulatory changes to autopilot functions? Do we do that all at once? How do we force drivers to do these updates? How do we keep drivers safe now that we've changed a major operational mode of their vehicle? We expect airline pilots to engage in simulations and continual training to ensure that they are on top of these changes, what are we going to do in vehicles?
> It did wonders for the aviation industry
It wasn't without it's own set of challenges[0]. Upshot of the video is, switching to a lower level of automation is now recommended practice in many situations because it's actually safer.
This is mostly about sensors and geometry. Machine learning has a role, but only in target identification. That's how Waymo does it. The fake it til you make it crowd had the fantasy that you just hook up some cameras to a machine learning system, train it, and you have self driving. Doesn't work. Machine learning is way too dumb.
You can maybe identify "traffic light", "car", "pedestrian", and "deer" with machine learning. That's just used to guess what they're going to do next. It's not used to decide if they're an obstacle. Obstacle detection and avoidance is all sensors and geometry.
Also, "self driving car", "electric car", and "transportation as a service" are all independent. All will be available, but not from the same companies.