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I have a feeling our regulatory environment is going to be unfairly hostile towards AVs in the coming months and years. Of course we all want a safe and respons

I have a feeling our regulatory environment is going to be unfairly hostile towards AVs in the coming months and years. Of course we all want a safe and responsible rollout of this tech, but people too easily forget how ABSURDLY dangerous driving is already. Like with Tesla, every accident and injury caused by a Waymo vehicle is going recieve disproportionate media coverage and subsequent public backlash. I hope we can view these incidents in context. Admittedly, safety is just one speedbump-- social and economic disprution is a whole 'nother beast. Whatever happens it's an exciting time to be alive! AVs have the potential to bring more sustainable, safe, efficient, and affordable mobility and I can't wait to see how it all plays out.

bsaul 7y ago
AV would certainly be judged with less hostility if it hadn’t built itself on the assumption that neural networks were the solution to any problem too hard to model. It’s going to be extremely hard for AV manufacturer to explain that it’s impossible for them to guarantee that a certain abnormal autopilot behavior that caused an accident isn’t going to happen again.
- ehsankia 7y ago
  I'm not an expert myself, but I think you overestimate how much ML is used in these systems. From my understanding, it's mostly used in classifying objects, but the actual controls are not, and I would assume that the driving logic itself is written in a conservative way and a bad classification wouldn't cause an insane behavior.
  - yo-scot-99 7y ago
    The Telsa autonomy investor day (which applied to the cars not the people) spent most of their time explaining their NN chip, ghost riding to correct predictions etc. Definitely gave the impression that the network was doing a lot of the decision making.
    - xmprt 7y ago
      Gives me the impression that Tesla made a small innovation which they're trying to overblow to investors since buzzwords like machine learning are more interesting than actual progress. I'm not saying Tesla isn't making massive progress but that anything they say to the press should be taken with a grain of salt.
      - drcross 7y ago
        Why speculate? Watch the I vestor day video and see for yourself why it's not just hot air.
    - nostrademons 7y ago
      Of course, because NNs are hot with investors now and Tesla wants their money. Companies frequently misrepresent how their technology works to the public. Typically they'll do some small portion with the hot technology for buzzword compliance, and then build the rest of it with an actually sensible, boring, and tailored-to-the-problem technology stack, oftentimes with a lot of proprietary legwork done by their data scientists and engineers. This way they get the best of all worlds: investment dollars from gullible investors, PR from journalists that want to hop on the next big thing, a product that actually works, and misdirection so competitors hop on approaches that aren't going to work anyway.
      - TaylorAlexander 7y ago
        That doesn’t seem to be the case with Tesla. Their custom chip is almost entirely focused on being a neural network accelerator and they seem to be hugely reliant on neural networks. Notably Waymo is said to be less reliant on neural networks but Tesla definitely depends on them.
        ehsankia 7y ago
        That doesn't really prove much. The classification is the heavy part that needs acceleration. The algorithmic side would probably not need an accelerator, as it's basically a decision tree. My original point was that the decision tree should hopefully degrade gracefully as the prediction quality goes down, and not have any brand that leads to an insane behavior. Now obviously, the better your predictions, the better the driving will be, which is why you'd want NN accelerators.
  - mehrdadn 7y ago
    > I would assume [...] a bad classification wouldn't cause an insane behavior I want to assume this too, but what evidence is there that we can actually assume this?
    - ehsankia 7y ago
      Well if the system was as I described it, you can throw as many bad classifications as you want in the simulation environment, of varying severity, and see how the algorithmic side reacts.
  - foobiekr 7y ago
    I have talked to a number of different autonomous driving startups and every one of them was entirely basing their approach on NNs and explicitly avoiding explicitly-coded algorithmic approaches. It was crazy and frightening that these people are serious.
    - Jasper_ 7y ago
      The even scarier thing is that a lot of these startups are training their neural networks on game videos like GTA or cars they get off the Unity asset store. I seriously doubt any of the artists, graphics programmers, AI developers, etc. involved in these titles think their work is suitable for safety critical systems.
    - yo-scot-99 7y ago
      the positions for Vision/Perception at zoox all mention nn's: https://jobs.lever.co/zoox https://jobs.lever.co/zoox i bet even simple questions like "how does this scenario change decisions when the lighting / sensor rotation are altered" cannot be answered.
      - ericd 7y ago
        Changing lighting and rotation on sensor input is a pretty standard way to improve neural net performance (it's called Data Augmentation), so I'm pretty sure they could answer that.
    - mli168 7y ago
      Having actually worked in these companies, I can say the actuation and controls are still deterministic algorithms. Talking on some buzzword is one thing, but actual implementation is another. I would be surprise if any of these companies have largely NN based modules in their stack for controls and lower level planning.
    - Animats 7y ago
      Yes, it's scary. We had an entry in the DARPA Grand Challenge in 2005. It was too slow, but it didn't crash. We profiled the road ahead with a LIDAR, so we had an elevation map of what was ahead. This is essential for off-road driving, and it's the gold standard for on-road driving. But there's a range limit. Not from the LIDAR itself. From the geometry. If the sensor is 2m from the ground, and you're looking 30m out, the angle is so shallow you can barely sense elevation. You can't see potholes. Anything that looks like a bump hides a lot of road behind it. The Stanford team's answer to this was to use machine learning to compare the near road texture, which they could profile, with the far road texture, which they couldn't. If the near road was flat, and the far road looked like the near road, they could out-drive their profiling range. If it didn't match, slowing down brought the stopping distance down to profiling range, and they could work through difficult terrain. The 2005 Grand Challenge didn't have much difficult off-road terrain. No rock-crawling or cratered roads. The 2004 course was harder, and nobody got past mile 7. So most of the time, fast mode was usable. Google/Waymo started from the Stanford approach, trying hard to profile the immediate surroundings. Their machine learning efforts were focused on identifying other road users - moving objects, not fixed ones. Their earlier videos make this clear. Google/Waymo built a cute little bubble car with a top speed of about 25MPH and a LIDAR on top. At that speed, you can profile the terrain all the way out to your stopping distance, so you have solid detection of fixed obstacles. That was something that had a good chance of working well. They decided not to manufacture it, probably because it would cost far too much. Machine learning isn't that accurate. You can get to 90% on many problems. Getting to 99% is very tough, and getting to 99.9% is usually out of reach. The killer apps for machine learning are in low-accuracy businesses like ad targeting. Or in areas where humans have accuracy in the 80%-90% range. Here lies the problem. Humans are very good at obstacle avoidance. Much better than 99%. Machine learning isn't as good as this problem needs. There's another side to the problem - the false alarm rate. If you build a system which insists on a valid ground profile, a piece of crumpled cardboard on the road will result in slowing down until the sensors can look down on the cardboard and see past it to solid pavement. You get a jerky ride from a conservative system. That's why Uber disabled automatic braking and killed a pedestrian. That's why Tesla's system fails to react to fixed obstacles it could potentially detect. Waymo has struggled with this. Customer evaluation of driving quality seems to be based on good lane-keeping and low jerk. These are things that trouble poor human drivers. Self-driving has different strengths and weaknesses. This is what leads to systems which seem to be doing great, right up until they crash. What self-driving seems to need right now is a rock-solid way of detecting the lack of obstacles ahead. All we have so far is LIDAR. Radar is still too coarse and has trouble distinguishing ground return from obstacles. Even LIDAR is rather coarse-grained. Stereo vision doesn't seem to be hugely successful at this. We need that before self-driving vehicles can be trusted not to run into obvious obstacles. If you have to recognize what the obstacle is before determining that it's an obstacle, it's not going to work. There are a whole series of secondary problems, from left turns to double-parked cars. But those are not the ones that kill people. It's the basic "don't hit stuff" problem that is not adequately solved.
  - computerex 7y ago
    Tell that to the owners of Tesla vehicles that have been running into stationary fire trucks.
- Erlich_Bachman 7y ago
  Where are you even reading this assumption? Who, which company has said this? Sounds like something someone overheard somewhere, and not an actual assumption made by any of those companies. In reality Waymo, Tesla and others are using NNs where they fit, where they have been shown to produce the best results - and other methods everywhere else. Heck, even the ML courses teaching self-driving tech to students don't exclusively use NNs, but all sorts of ML models.
amelius 7y ago
But let's not measure AV safety against the average human driver, but against the most capable human driver.
- maxerickson 7y ago
  The rational approach would be to license them when it was likely they'd increase the overall average safety of drivers. That isn't just a question of the safety of the autonomous systems though, it also includes consideration of which drivers end up using them. Some drunks will use auto taxis, lots won't.
- brendanmc6 7y ago
  Interesting way to frame it, but I'm not sure if I agree... If the net benefit is less death and injury, shouldn't that be the obvious choice?
  - twblalock 7y ago
    No, because society has already accepted the status quo and needs to be convinced to change it. Technology can't gain acceptance by being just as good as the status quo -- it has to be better. Every time a self-driving car causes an accident in a situation where a human driver probably would not have (and sometimes in pretty obvious ways, like driving into a freeway divider), it will hurt acceptance of the new technology. Politicians will never miss an opportunity to grandstand against tech companies. People will be afraid to ride in autonomous vehicles.
    - pawelmurias 7y ago
      The status quo is that average drivers can get an license not only the top tier ones.
    - mactrey 7y ago
      The status quo is you either have to pay someone ~$10/hr to drive for you, or you have to focus and keep both hands on the wheel and actually drive yourself, and it's still pretty dangerous. Self-driving cars could improve on the status quo significantly without actually being less dangerous.
adrianmonk 7y ago
I think you're probably right but I don't expect it to change. It's human nature to be afraid of the unknown and unfamiliar. Even if you had a mountain of statistical evidence to show it's actually safer (which doesn't actually exist yet), it's new to people, so they're going to fear it.
sgustard 7y ago
> view these incidents in context I view them in the context "software can kill people, and can do so at scale." Same way I view the recent Boeing 737 incidents.
- dbbk 7y ago
  Human drivers already kill people at scale. Enormous scale. Far greater than that of the incidents of self-driving cars. Ultimately it will come down to, who is safer?
  - mamon 7y ago
    Machine learning models for AVs are uploaded to whole fleet of vehicles, potentially causing thousands of identical accidents. No two humans have identical brains, so every human-caused accident is unique. In other words: human errors do not scale at all, fortunately.
    - mr_toad 7y ago
      > In other words: human errors do not scale at all, fortunately. Worldwide there were over 1.3 million road deaths in 2016. That’s a pretty big scale. Technology, even when deliberately employed to cause death, has rarely managed to cause such carnage.
    - dbbk 7y ago
      I see your point, although I would argue that you could say the same thing about human factors like intoxication. Say there's a big drinking holiday, human-driven deaths go up due to people drink driving. Self-driving cars are immune to that factor.
tim333 7y ago
The regulatory environment has been fairly easy going so far including allowing Tesla's autopilot although it's not terribly safe and Florida has passed a law allowing completely unmanned vehicles. I think regulators recognise that encouraging development now will probably save lives down the line. The bigger problem still seems making vehicles that work well rather than getting them past regulations.
parentheses 7y ago
I can confidently say this hope will not be met. > I hope we can view these incidents in context. The desire to hold some entity legally responsible for any accidents seems to be the key problem. That problem is really about punishing the responsible party. If someone dies because of an irresponsible driver, the outcomes of the case are always some sort combination of punishments: fines, incarceration, suspensions, etc. Proposed Solution: Legislation can easily be passed that provides clear guidelines about how these errors of judgement in computing systems can be punished. For example: In situations of death, $X is paid to the victim's family, $Y is paid to the federal government, the company's automated vehicle manufacture license is suspended until federal review, etc. Then, its a simple matter of getting humans to sign to agree that they will accept these terms.
- luckydata 7y ago
  There is already a pretty good framework that can be used: airline regulation.
  - otakucode 7y ago
    Companies which produce aircraft must hire licensed engineers to do the design and implementation work. AVs are almost all software. Licensed software engineers do not exist. While there are regulations and standards for every other form of engineering, there is nothing for software. And courts have recognized this. They have stated that companies can not be found criminally negligent regardless of their practices because there are no standards which they are failing to adhere to.
    - anticensor 7y ago
      May making MISRA guidelines an international standard, namely International Standard for Programming Practices in Safety-Critical Environments, solve this?
- judge2020 7y ago
  > The desire to hold some entity legally responsible for any accidents seems to be the key problem. Kind of off-topic, but do these minivans have insurance policies? Or is there some Alphabet subsidiary that allows them to act as insurance for themselves? If they do basically insure themselves, they will already be paying out insurance whenever their AI fails to follow/obey laws, so the only issue with placing blame is in the public/media's eye.
skywhopper 7y ago
It’s not about safety. These things don’t actually work yet. They can’t make left turns across traffic, they can’t change lanes in heavy traffic, they can’t handle anything but pristine perfectly mapped roads in good weather during daylight. Any non-standard street feature or road usage is an insurmountable roadblock (literally) to them. Promising that they will save lives and disrupt the economy (how you turn robot taxis into a profitable business hasn’t been explained convincingly for that matter) is a hollow delusion until they can actually navigate from point to point in less than perfect conditions without causing traffic backups or making the passengers carsick.
ant6n 7y ago
Not sure how massively increasing VMT will make mobility more sustainable. It`s more likely to do the opposite.
harry8 7y ago
This is going to be just about the only industry without heavy regulatory capture? Why?
z3t4 7y ago
There should be a zero vision. eg. no deaths.
- egl2019 7y ago
  Better give up eating vegetables, too: people die working on farms.
  - WiseWeasel 7y ago
    That’ll be fixed once autonomous farming takes over.
    - mapcars 7y ago
      Then.. farmers will die from not having a job?
  - userbinator 7y ago
    Better give up living too; people die by being alive... oh wait.
nathanvanfleet 7y ago
Not sure what you mean, there are all sorts of providers who have been actively on roads for the past few years. Including some giving rides to passengers like Lyft in Las Vegas. There was definitely some controversy last year when there were some crashes and even a death from autonomous vehicles being tested.
quatquat 7y ago
They have the potential, but I think that in practice we are at minimum decades away from having self-driving cars that are as safe as human drivers on average in general conditions.
nothis 7y ago
Since I don't think anyone on hackernews thinks much different, I feel like defending the other side of this: Yes, in theory self-driving cars can be safer than human drivers. But the tech simply isn't mature. It just isn't. Early tech always has hiccups, not the ones that are calculated into the risk but the ones no one expects. So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal. Let's start this, but it's okay to start slow.
- King-Aaron 7y ago
  > So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal Are you talking about bugs in artificial intelligence, or bugs in regular 'ol human intelligence? Because that statement rings true for both, lol.
  - AdieuToLogic 7y ago
    >> So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal > Are you talking about bugs in artificial intelligence, or bugs in regular 'ol human intelligence? > Because that statement rings true for both, lol. Your stated position gives far too much credit to algorithms and far too little to what every capable human driver can do.
    - cthaeh 7y ago
      U give far to much credit to human drivers. Capable human drivers as a subset of human drivers. A large subset to be sure,but nowhere near everyone. At least an av cant get drunk.
      - AdieuToLogic 7y ago
        > U give far to much credit to human drivers. The data available challenges this contention. According to here[0], one estimate is that there are approximately 18,000,000 people driving at any given time in the U.S. And according to here[1], there were 34,439 traffic fatalities in the U.S. for the calendar year of 2016. For the sake of discussion, let's assume that of the 18 million drivers in the U.S. on the road at any given time, there are at least two other drivers which are not on the road at that same time. Further, let's assume these are all of the U.S. drivers for the entire 2016 calendar year. This would put the estimated set of unique drivers at 54,000,000. A conservative estimate by any means. This makes the estimated probability of a human driver being involved in a traffic fatality for the 2016 calendar year to be 34439 : 54000000, or 0.00063776. According to here[2], the probability of being struck by lightning in the U.S. is approximately 1 : 280000, or 0.00000357. While the former is mathematically 200x more probable, the latter is statistically insignificant. > Capable human drivers as a subset of human drivers. Hence my qualification of "capable", included in order to obviate edge condition "whataboutism." > At least an av cant get drunk. But it can get defective updates, be unable to identify unknown conditions, suffer from misidentification of threats, and susceptible to cascading failures affecting all autonomous vehicles in the same situations. 0 - https://www.quora.com/How-many-drivers-are-on-the-road-at-any-given-time-in-the-US https://www.quora.com/How-many-drivers-are-on-the-road-at-an... 1 - https://safer-america.com/car-accident-statistics/#US https://safer-america.com/car-accident-statistics/#US 2 - http://www.lightningsafety.com/nlsi_pls/probability.html http://www.lightningsafety.com/nlsi_pls/probability.html
viburnum 7y ago
Robot cars don’t work, and as long as they share the streets with autonomous humans, they never will. But don’t give up hope, because maybe corporations can make it illegal to be outside unless you’re inside a robot car.
OrgNet 7y ago
The company implementing the autonomous vehicles still need to be held accountable no matter what... otherwise you could pay them to kill anyone...
jancsika 7y ago
> Like with Tesla, every accident and injury caused by a Waymo vehicle is going recieve disproportionate media coverage and subsequent public backlash. Explain the universe where humans are rational enough to give "proportionate" attention to tech as novel as self-driving cars, yet irrational enough to have preferred private car ownership over mass transit in the first place.
- conanbatt 7y ago
  Why irrational? Cabs are SO convenient, and public transportation has all kinds of issues world-wide. Buenos Aires, for example, has subsidized metro (about 0.50U$S per ticket) vs a non-subsidized uber (5U$S per ride~) and still the experience is so much better and convenient and reliable that 5U$S is really worth it. I think that the ride-hailing revolution is a classic case of great microeconomics.
  - robotresearcher 7y ago
    Uber rides are subsidized by investors.
    - conanbatt 7y ago
      Even better, rich people giving free money to drivers and riders world-wide is one the most fantastic charity project in the world.
- rayiner 7y ago
  Fun fact: the U.S. has among the shortest commute times in the entire OECD, because we rely more on point-to-point private car ownership and less on mass transit: https://www.oecd.org/els/family/LMF2_6_Time_spent_travelling_to_and_from_work.pdf https://www.oecd.org/els/family/LMF2_6_Time_spent_travelling...
justapassenger 7y ago
> ABSURDLY dangerous driving is already It's very dangerous in some places in the world. Majority of deaths are happening in places with poor infrastructure[1], that autonomous vehicles are very far away from being able to handle. For current state of AV, bar it has to meet and exceed are places with good infrastructure, fairly new cars and reasonably good driving culture, as those are first targets of rollout. For example, in Phoenix, AZ, about 250 people die per year from accidents[2], with about 9k miles driven per person[3] and metropolitan area having 4.7m people, to just match human levels AVs to have less than 1 fatality per 170 million miles driven. [1] https://en.wikipedia.org/wiki/List_of_countries_by_traffic-related_death_rate https://en.wikipedia.org/wiki/List_of_countries_by_traffic-r... [2] http://www.city-data.com/accidents/acc-Phoenix-Arizona.html http://www.city-data.com/accidents/acc-Phoenix-Arizona.html [3] https://arizonapirgedfund.org/sites/pirg/files/reports/FINAL%20Bikes%2C%20Trains%20%26%20Less%20Driving%207-14.pdf https://arizonapirgedfund.org/sites/pirg/files/reports/FINAL...
- userbinator 7y ago
  Majority of deaths are happening in places with poor infrastructure[1], that autonomous vehicles are very far away from being able to handle. In other words, it's still more like a better cruise control: it makes the easy part of driving easier, but doesn't help with the hard parts (and may make them even harder.)
erobbins 7y ago
Driving is not dangerous. Millions of people drive hundreds of millions of miles a day in the US, and the number of deaths is a statistical blip.
- kalenx 7y ago
  Then, by this reasoning, autonomous driving is not dangerous either.
  - erobbins 7y ago
    It's more dangerous, and I trust distributed systems (humans) more than a monolith (waymo). Sure, an individual human may from time to time screw up, but there aren't any defects present in every single person just waiting for the right edge case to appear.
    - jefftk 7y ago
      There definitely are! Consider blind spots / limited field of view, slow reflexes, and tendencies towards distracted driving. AVs certainly have bugs, and some may lead to accidents and even deaths, but each one will be examined in an enormous amount of detail to figure out what sort of edge case it was and prevent similar ones from happening.
- _delirium 7y ago
  It's a pretty big blip! About 2.2 million people a year are injured in automobile accidents in the U.S., and around 35,000 are killed. Granted, you're still much more likely to die of heart disease. But if we're going to care about any non-disease causes of death or injury at all, automobile accidents are near the top of the ones to worry about. It's a much bigger cause of both deaths and injuries than violent crime is, for example.
ab_c 7y ago
I feel this has been the case with e-scooters in SF. People being disproportionately angry at tech companies for making these devices available. And yet, before them, you'd see an army of social activists riding their bikes thru thru red lights and being general assholes.
computerex 7y ago
I don't necessarily disagree with you, but the comparison between Tesla and Waymo seems absurd. Tesla doesn't have the greatest track record when it comes to safety. Waymo has been moving very slowly and meticulously, and their tech is light-years ahead of Tesla.
rayiner 7y ago
> Of course we all want a safe and responsible rollout of this tech, but people too easily forget how ABSURDLY dangerous driving is already. I don't really understand how this meme gets so much traction. It just ignores the enormous number of miles driven by Americans every year. Last year, Americans drove 3.22 trillion miles. There were about 6 million accidents, or 500,000 miles between accidents. (Or about 37 years of driving at typical rates). Driving results in a death every 85 million miles traveled. Driving is actually very safe. Conversely, because it is so safe, it wouldn't take much to dramatically increase accident rates from driving.
- blub 7y ago
  I guess many of us have such an inflated sense of self-importance that we think we can save humans from themselves, without stopping to think who will save everyone from crappy software.
- michaelt 7y ago
  I don't really understand how this meme gets so much traction. The trick is to compare driving deaths to other things where we had a much bigger (or smaller) reaction relative to the number of lives lost. For example, tell someone "cars kill as many people as twelve September-11th attacks every year" and they might wonder where the trillion-dollar war on road deaths is. On the other hand, tell someone "heart disease kills 17 times as many people as cars every year" and you'll give them the opposite impression.
shirro 7y ago
Better driver assist technology could have the same benefits but it is not equally distributed due to cost. Automation is going to go from luxury vehicles to commercial vehicles and be funded by labor savings. Good luck affording even basic collision avoidance tech in a family car if you are an unemployed driver.
nradov 7y ago
Driving is actually quite safe, if you have a late model car with top safety ratings and never drive drunk or distracted.
- slavik81 7y ago
  Or tired. Or at night, especially on rural roads.
- glenneroo 7y ago
  As someone else mentioned, there were an estimated 1.3 million road deaths in 2016. The number of injuries is considerably higher. Do you consider that "quite safe"?
agildehaus 7y ago
It's important to remember that flying was ridiculously unsafe when it first appeared. Now they're the safest form of travel. Not to say that self-driving cars will be ridiculously unsafe when the first commercial service appears, but they share one thing with planes: increased safety is an engineering problem. Every incident that occurs with these vehicles will have tons of data and people looking over that data to fix the issue. Human brains can't be fixed, sensors and computer software can.
simion314 7y ago
>I hope we can view these incidents in context. The context is that Tesla hardware is not sufficiently powerful, so they do "optimizations" and ignore stationary objects. This is not a video game where we can trick the player with some clever hacks, if the hardware is not fast enough the solution is to use better hardware and I think is very normal to see in newspaper when "autopilot" hits a wall, it is a public service even if Tesla fans and shareholders don't like it and try to play with numbers to show some statistics to favor Tesla(AFAIK Tesla still keeps the safety numbers they were using to promote their cools stats a secret)
dalbasal 7y ago
Is that such a terrible thing? Sure, our perception of risk and regulatory responses are not statistically accurate. Commercial air travel is much safer than cars, yet regulatory resposnses to risk are stricter. Is that a bad thing? It creates a very safe mode of transport. Going driverless is a new mode, and an opportunity to create a safer future. Why not set a standard that is much higher than human operated cars? Also, a lot is unknown. We won't know what driveless' safety record is until it truly exists in the wild. The economic pressures to go driverless will be immense^. Meanwhile, a high safety standard could require a some counterpressure, and the starting point will set the stage for the future. ^two kinds. It could be a huge win for consumers, with taxis prices halving or better. It is alsi an opportunity to "put capital to work," in a (current) market that is starved for such. A robo-taxi fleet is just the kind of thing a massive fund can erm.. fund.
not_a_moth 7y ago
If you're a top 1% driver, defensive, experienced etc., then putting yourself in an AV means assuming greater risk. If you're in the latter group, you would be rightly horrified each time there's an AV accident. (the "on average across the population it will be safer" doesn't mean anything for drivers who are already well above average)
- taneq 7y ago
  True, assuming you're in top-1% condition. Even a usually top-1% driver is going to be far worse off if they're tired, or distracted, or had a fight with their partner that morning, etc.
- unionpivo 7y ago
  Problem is that about half of my friends think they are in that top 1% Besides we need solution that works for 80% of the people. there will always be some edge cases
jillesvangurp 7y ago
Peer pressure will counter initial regulatory hostility. Inevitably there are going to be some early adopter areas and a lot of people scrutinizing what is happening there. When some of those early adopter areas are are getting clear benefits, there's going to be a lot of pressure on neighboring areas to do imitate what their neighbors are doing. From there, it is just a matter of time. Eventually it will turn around and regulation will start making non autonomous driving harder to wield out the remaining accidents involving drunk/tired/incompetent/reckless/etc. drivers. Insurers will be a major factor here. They should start getting some pretty good insights in accident rates involving AVs vs. normal cars.
walrus1066 7y ago
In my view, accidents aren't the main issue, it's more the disruption caused if an AV, with no human driver, encounters the 'freezing robot problem' (I.e. When traffic lights not working, with policeman directing traffic) & gets stuck in a busy city centre, blocking traffic all around. I'm not aware of any fallback remote takeover mechanism that can be used to recover AV's on this situation. EDIT: I'm convinced, that until we majorly overhaul our road infrastructure to be more 'robot friendly', it's hard to see _fully_ autonomous AV's work in major cities I.e. electronic beacons on lane dividers, electronic signals on traffic lights, vastly stronger GPS network or replacement thereof, six nines level mobile network coverage at high bandwidth.
Traster 7y ago
Well we're really talking about two different things here: The first one is manufacturing a product, and the second is using the product. It's systemic risk. Airplane manufacturing is extremely highly regulated - the reason being that if there's a bug, then the bug is in every airplane. And when that bug appears there's often very little opportunity to mitigate it and the consequences are huge, it's the Manufacturer that's responsible, but the passengers (and bystanders) who pay the price. Similarly, the standard for safety in car manufacture is much higher than the standard of safety for becoming a driver. Partly because the problems for the former are systematic, and partly because the latter primarily poses a risk to themselves. There's self-regulation there. When Tesla tells everyone they have autopilot it isn't Elon Musk whose Tesla slams into a lane divider at 70mph, it's one of the customers he lied to, and it's likely not even one customer, it's a systematic issue where every driver in that situation will face danger.
otakucode 7y ago
>I hope we can view these incidents in context. That is extremely unlikely and borders on impossible. AVs have some profound things working against them. They share the problem airplanes have. Human beings are abysmal at risk estimation, and a very large factor of the estimation they do is whether they have personal control. It doesn't matter that planes are much safer than driving, the fact that people don't have direct control of the aircraft makes them feel unsafe to the point that some people are paralyzed by their fear of flying. The same will be true of AVs, and for the same (un)reasons. But I have my own doubts that it will even get far enough for that to pose a serious problem. We have a more general problem with technology in our society. It is nearly unanswerable to the law. Take the Toyota "unintended acceleration" scandal from a few years ago for example. Investigation of that issue determined firmware flaws were the cause, and led to the deaths of over a dozen people. The criminal court case against Toyota unearthed that while the automotive industry had coding practices that established 'required' and 'suggested' techniques, lists of around 100 practices. Toyota followed 4 of them. Firmware developers working for Toyota did not even have access to a bug tracker at all. They did not have access to static analysis tools. They had no role in determining scheduling. They were found 'not guilty' for criminal negligence. The reason given by the court was that because the problem involved software, criminal negligence was impossible. No standards exist governing software, and therefor no company can be held criminally responsible regardless of their practices. During the civil case, they were found guilty and responsible for the deaths, but before the jury could award damages, Toyota settled with the victims families. That legal precedent is terrifying. The first AV to market will inevitably be the one that cuts the most corners and is rushed the most in its development. When it kills someone, as is basically guaranteed to happen by simple statistics, the public will be paying more attention than they did to the Toyota case. And when the public at large hears that tech company executives are literally above the law, the outrage and consequences will likely be swift and severe. Sensing political opportunity, the legislators will descend and could very well end up dictating what language must be used, what coding standards must be followed, what tools must be used (you know the tool vendors will be lobbying hard), etc. The ACM (Association of Computing Machinery) has been discussing this issue for years, debating the potential merits and pitfalls of establishing a licensing system for software engineers. Thus far, the discussion always ends with 'companies would have to pay more for licensed developers and the cost of labor must be contained.' The looming pitfall of avoiding certification and licensing, however, is that government will step in and do it themselves which is virtually guaranteed to enact the greatest pain on the software industry.

bsaul 7y ago

AV would certainly be judged with less hostility if it hadn’t built itself on the assumption that neural networks were the solution to any problem too hard to model. It’s going to be extremely hard for AV manufacturer to explain that it’s impossible for them to guarantee that a certain abnormal autopilot behavior that caused an accident isn’t going to happen again.

ehsankia 7y ago
I'm not an expert myself, but I think you overestimate how much ML is used in these systems. From my understanding, it's mostly used in classifying objects, but the actual controls are not, and I would assume that the driving logic itself is written in a conservative way and a bad classification wouldn't cause an insane behavior.
- yo-scot-99 7y ago
  The Telsa autonomy investor day (which applied to the cars not the people) spent most of their time explaining their NN chip, ghost riding to correct predictions etc. Definitely gave the impression that the network was doing a lot of the decision making.
  - xmprt 7y ago
    Gives me the impression that Tesla made a small innovation which they're trying to overblow to investors since buzzwords like machine learning are more interesting than actual progress. I'm not saying Tesla isn't making massive progress but that anything they say to the press should be taken with a grain of salt.
    - drcross 7y ago
      Why speculate? Watch the I vestor day video and see for yourself why it's not just hot air.
  - nostrademons 7y ago
    Of course, because NNs are hot with investors now and Tesla wants their money. Companies frequently misrepresent how their technology works to the public. Typically they'll do some small portion with the hot technology for buzzword compliance, and then build the rest of it with an actually sensible, boring, and tailored-to-the-problem technology stack, oftentimes with a lot of proprietary legwork done by their data scientists and engineers. This way they get the best of all worlds: investment dollars from gullible investors, PR from journalists that want to hop on the next big thing, a product that actually works, and misdirection so competitors hop on approaches that aren't going to work anyway.
    - TaylorAlexander 7y ago
      That doesn’t seem to be the case with Tesla. Their custom chip is almost entirely focused on being a neural network accelerator and they seem to be hugely reliant on neural networks. Notably Waymo is said to be less reliant on neural networks but Tesla definitely depends on them.
      - ehsankia 7y ago
        That doesn't really prove much. The classification is the heavy part that needs acceleration. The algorithmic side would probably not need an accelerator, as it's basically a decision tree. My original point was that the decision tree should hopefully degrade gracefully as the prediction quality goes down, and not have any brand that leads to an insane behavior. Now obviously, the better your predictions, the better the driving will be, which is why you'd want NN accelerators.
- mehrdadn 7y ago
  > I would assume [...] a bad classification wouldn't cause an insane behavior I want to assume this too, but what evidence is there that we can actually assume this?
  - ehsankia 7y ago
    Well if the system was as I described it, you can throw as many bad classifications as you want in the simulation environment, of varying severity, and see how the algorithmic side reacts.
- foobiekr 7y ago
  I have talked to a number of different autonomous driving startups and every one of them was entirely basing their approach on NNs and explicitly avoiding explicitly-coded algorithmic approaches. It was crazy and frightening that these people are serious.
  - Jasper_ 7y ago
    The even scarier thing is that a lot of these startups are training their neural networks on game videos like GTA or cars they get off the Unity asset store. I seriously doubt any of the artists, graphics programmers, AI developers, etc. involved in these titles think their work is suitable for safety critical systems.
  - yo-scot-99 7y ago
    the positions for Vision/Perception at zoox all mention nn's: https://jobs.lever.co/zoox https://jobs.lever.co/zoox i bet even simple questions like "how does this scenario change decisions when the lighting / sensor rotation are altered" cannot be answered.
    - ericd 7y ago
      Changing lighting and rotation on sensor input is a pretty standard way to improve neural net performance (it's called Data Augmentation), so I'm pretty sure they could answer that.
  - mli168 7y ago
    Having actually worked in these companies, I can say the actuation and controls are still deterministic algorithms. Talking on some buzzword is one thing, but actual implementation is another. I would be surprise if any of these companies have largely NN based modules in their stack for controls and lower level planning.
  - Animats 7y ago
    Yes, it's scary. We had an entry in the DARPA Grand Challenge in 2005. It was too slow, but it didn't crash. We profiled the road ahead with a LIDAR, so we had an elevation map of what was ahead. This is essential for off-road driving, and it's the gold standard for on-road driving. But there's a range limit. Not from the LIDAR itself. From the geometry. If the sensor is 2m from the ground, and you're looking 30m out, the angle is so shallow you can barely sense elevation. You can't see potholes. Anything that looks like a bump hides a lot of road behind it. The Stanford team's answer to this was to use machine learning to compare the near road texture, which they could profile, with the far road texture, which they couldn't. If the near road was flat, and the far road looked like the near road, they could out-drive their profiling range. If it didn't match, slowing down brought the stopping distance down to profiling range, and they could work through difficult terrain. The 2005 Grand Challenge didn't have much difficult off-road terrain. No rock-crawling or cratered roads. The 2004 course was harder, and nobody got past mile 7. So most of the time, fast mode was usable. Google/Waymo started from the Stanford approach, trying hard to profile the immediate surroundings. Their machine learning efforts were focused on identifying other road users - moving objects, not fixed ones. Their earlier videos make this clear. Google/Waymo built a cute little bubble car with a top speed of about 25MPH and a LIDAR on top. At that speed, you can profile the terrain all the way out to your stopping distance, so you have solid detection of fixed obstacles. That was something that had a good chance of working well. They decided not to manufacture it, probably because it would cost far too much. Machine learning isn't that accurate. You can get to 90% on many problems. Getting to 99% is very tough, and getting to 99.9% is usually out of reach. The killer apps for machine learning are in low-accuracy businesses like ad targeting. Or in areas where humans have accuracy in the 80%-90% range. Here lies the problem. Humans are very good at obstacle avoidance. Much better than 99%. Machine learning isn't as good as this problem needs. There's another side to the problem - the false alarm rate. If you build a system which insists on a valid ground profile, a piece of crumpled cardboard on the road will result in slowing down until the sensors can look down on the cardboard and see past it to solid pavement. You get a jerky ride from a conservative system. That's why Uber disabled automatic braking and killed a pedestrian. That's why Tesla's system fails to react to fixed obstacles it could potentially detect. Waymo has struggled with this. Customer evaluation of driving quality seems to be based on good lane-keeping and low jerk. These are things that trouble poor human drivers. Self-driving has different strengths and weaknesses. This is what leads to systems which seem to be doing great, right up until they crash. What self-driving seems to need right now is a rock-solid way of detecting the lack of obstacles ahead. All we have so far is LIDAR. Radar is still too coarse and has trouble distinguishing ground return from obstacles. Even LIDAR is rather coarse-grained. Stereo vision doesn't seem to be hugely successful at this. We need that before self-driving vehicles can be trusted not to run into obvious obstacles. If you have to recognize what the obstacle is before determining that it's an obstacle, it's not going to work. There are a whole series of secondary problems, from left turns to double-parked cars. But those are not the ones that kill people. It's the basic "don't hit stuff" problem that is not adequately solved.
- computerex 7y ago
  Tell that to the owners of Tesla vehicles that have been running into stationary fire trucks.
Erlich_Bachman 7y ago
Where are you even reading this assumption? Who, which company has said this? Sounds like something someone overheard somewhere, and not an actual assumption made by any of those companies. In reality Waymo, Tesla and others are using NNs where they fit, where they have been shown to produce the best results - and other methods everywhere else. Heck, even the ML courses teaching self-driving tech to students don't exclusively use NNs, but all sorts of ML models.

amelius 7y ago

But let's not measure AV safety against the average human driver, but against the most capable human driver.

maxerickson 7y ago
The rational approach would be to license them when it was likely they'd increase the overall average safety of drivers. That isn't just a question of the safety of the autonomous systems though, it also includes consideration of which drivers end up using them. Some drunks will use auto taxis, lots won't.
brendanmc6 7y ago
Interesting way to frame it, but I'm not sure if I agree... If the net benefit is less death and injury, shouldn't that be the obvious choice?
- twblalock 7y ago
  No, because society has already accepted the status quo and needs to be convinced to change it. Technology can't gain acceptance by being just as good as the status quo -- it has to be better. Every time a self-driving car causes an accident in a situation where a human driver probably would not have (and sometimes in pretty obvious ways, like driving into a freeway divider), it will hurt acceptance of the new technology. Politicians will never miss an opportunity to grandstand against tech companies. People will be afraid to ride in autonomous vehicles.
  - pawelmurias 7y ago
    The status quo is that average drivers can get an license not only the top tier ones.
  - mactrey 7y ago
    The status quo is you either have to pay someone ~$10/hr to drive for you, or you have to focus and keep both hands on the wheel and actually drive yourself, and it's still pretty dangerous. Self-driving cars could improve on the status quo significantly without actually being less dangerous.

adrianmonk 7y ago

I think you're probably right but I don't expect it to change. It's human nature to be afraid of the unknown and unfamiliar. Even if you had a mountain of statistical evidence to show it's actually safer (which doesn't actually exist yet), it's new to people, so they're going to fear it.

sgustard 7y ago

> view these incidents in context I view them in the context "software can kill people, and can do so at scale." Same way I view the recent Boeing 737 incidents.

dbbk 7y ago
Human drivers already kill people at scale. Enormous scale. Far greater than that of the incidents of self-driving cars. Ultimately it will come down to, who is safer?
- mamon 7y ago
  Machine learning models for AVs are uploaded to whole fleet of vehicles, potentially causing thousands of identical accidents. No two humans have identical brains, so every human-caused accident is unique. In other words: human errors do not scale at all, fortunately.
  - mr_toad 7y ago
    > In other words: human errors do not scale at all, fortunately. Worldwide there were over 1.3 million road deaths in 2016. That’s a pretty big scale. Technology, even when deliberately employed to cause death, has rarely managed to cause such carnage.
  - dbbk 7y ago
    I see your point, although I would argue that you could say the same thing about human factors like intoxication. Say there's a big drinking holiday, human-driven deaths go up due to people drink driving. Self-driving cars are immune to that factor.

tim333 7y ago

The regulatory environment has been fairly easy going so far including allowing Tesla's autopilot although it's not terribly safe and Florida has passed a law allowing completely unmanned vehicles. I think regulators recognise that encouraging development now will probably save lives down the line. The bigger problem still seems making vehicles that work well rather than getting them past regulations.

parentheses 7y ago

I can confidently say this hope will not be met. > I hope we can view these incidents in context. The desire to hold some entity legally responsible for any accidents seems to be the key problem. That problem is really about punishing the responsible party. If someone dies because of an irresponsible driver, the outcomes of the case are always some sort combination of punishments: fines, incarceration, suspensions, etc. Proposed Solution: Legislation can easily be passed that provides clear guidelines about how these errors of judgement in computing systems can be punished. For example: In situations of death, $X is paid to the victim's family, $Y is paid to the federal government, the company's automated vehicle manufacture license is suspended until federal review, etc. Then, its a simple matter of getting humans to sign to agree that they will accept these terms.

luckydata 7y ago
There is already a pretty good framework that can be used: airline regulation.
- otakucode 7y ago
  Companies which produce aircraft must hire licensed engineers to do the design and implementation work. AVs are almost all software. Licensed software engineers do not exist. While there are regulations and standards for every other form of engineering, there is nothing for software. And courts have recognized this. They have stated that companies can not be found criminally negligent regardless of their practices because there are no standards which they are failing to adhere to.
  - anticensor 7y ago
    May making MISRA guidelines an international standard, namely International Standard for Programming Practices in Safety-Critical Environments, solve this?
judge2020 7y ago
> The desire to hold some entity legally responsible for any accidents seems to be the key problem. Kind of off-topic, but do these minivans have insurance policies? Or is there some Alphabet subsidiary that allows them to act as insurance for themselves? If they do basically insure themselves, they will already be paying out insurance whenever their AI fails to follow/obey laws, so the only issue with placing blame is in the public/media's eye.

skywhopper 7y ago

It’s not about safety. These things don’t actually work yet. They can’t make left turns across traffic, they can’t change lanes in heavy traffic, they can’t handle anything but pristine perfectly mapped roads in good weather during daylight. Any non-standard street feature or road usage is an insurmountable roadblock (literally) to them. Promising that they will save lives and disrupt the economy (how you turn robot taxis into a profitable business hasn’t been explained convincingly for that matter) is a hollow delusion until they can actually navigate from point to point in less than perfect conditions without causing traffic backups or making the passengers carsick.

ant6n 7y ago

Not sure how massively increasing VMT will make mobility more sustainable. It`s more likely to do the opposite.

harry8 7y ago

This is going to be just about the only industry without heavy regulatory capture? Why?

z3t4 7y ago

There should be a zero vision. eg. no deaths.

egl2019 7y ago
Better give up eating vegetables, too: people die working on farms.
- WiseWeasel 7y ago
  That’ll be fixed once autonomous farming takes over.
  - mapcars 7y ago
    Then.. farmers will die from not having a job?
- userbinator 7y ago
  Better give up living too; people die by being alive... oh wait.

nathanvanfleet 7y ago

Not sure what you mean, there are all sorts of providers who have been actively on roads for the past few years. Including some giving rides to passengers like Lyft in Las Vegas. There was definitely some controversy last year when there were some crashes and even a death from autonomous vehicles being tested.

quatquat 7y ago

They have the potential, but I think that in practice we are at minimum decades away from having self-driving cars that are as safe as human drivers on average in general conditions.

nothis 7y ago

Since I don't think anyone on hackernews thinks much different, I feel like defending the other side of this: Yes, in theory self-driving cars can be safer than human drivers. But the tech simply isn't mature. It just isn't. Early tech always has hiccups, not the ones that are calculated into the risk but the ones no one expects. So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal. Let's start this, but it's okay to start slow.

King-Aaron 7y ago
> So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal Are you talking about bugs in artificial intelligence, or bugs in regular 'ol human intelligence? Because that statement rings true for both, lol.
- AdieuToLogic 7y ago
  >> So there's a somewhat high probability that a bug that works totally different from what anyone expects is just waiting to happen and it's steering a 4000 pound block of metal > Are you talking about bugs in artificial intelligence, or bugs in regular 'ol human intelligence? > Because that statement rings true for both, lol. Your stated position gives far too much credit to algorithms and far too little to what every capable human driver can do.
  - cthaeh 7y ago
    U give far to much credit to human drivers. Capable human drivers as a subset of human drivers. A large subset to be sure,but nowhere near everyone. At least an av cant get drunk.
    - AdieuToLogic 7y ago
      > U give far to much credit to human drivers. The data available challenges this contention. According to here[0], one estimate is that there are approximately 18,000,000 people driving at any given time in the U.S. And according to here[1], there were 34,439 traffic fatalities in the U.S. for the calendar year of 2016. For the sake of discussion, let's assume that of the 18 million drivers in the U.S. on the road at any given time, there are at least two other drivers which are not on the road at that same time. Further, let's assume these are all of the U.S. drivers for the entire 2016 calendar year. This would put the estimated set of unique drivers at 54,000,000. A conservative estimate by any means. This makes the estimated probability of a human driver being involved in a traffic fatality for the 2016 calendar year to be 34439 : 54000000, or 0.00063776. According to here[2], the probability of being struck by lightning in the U.S. is approximately 1 : 280000, or 0.00000357. While the former is mathematically 200x more probable, the latter is statistically insignificant. > Capable human drivers as a subset of human drivers. Hence my qualification of "capable", included in order to obviate edge condition "whataboutism." > At least an av cant get drunk. But it can get defective updates, be unable to identify unknown conditions, suffer from misidentification of threats, and susceptible to cascading failures affecting all autonomous vehicles in the same situations. 0 - https://www.quora.com/How-many-drivers-are-on-the-road-at-any-given-time-in-the-US https://www.quora.com/How-many-drivers-are-on-the-road-at-an... 1 - https://safer-america.com/car-accident-statistics/#US https://safer-america.com/car-accident-statistics/#US 2 - http://www.lightningsafety.com/nlsi_pls/probability.html http://www.lightningsafety.com/nlsi_pls/probability.html

viburnum 7y ago

Robot cars don’t work, and as long as they share the streets with autonomous humans, they never will. But don’t give up hope, because maybe corporations can make it illegal to be outside unless you’re inside a robot car.

OrgNet 7y ago

The company implementing the autonomous vehicles still need to be held accountable no matter what... otherwise you could pay them to kill anyone...

jancsika 7y ago

> Like with Tesla, every accident and injury caused by a Waymo vehicle is going recieve disproportionate media coverage and subsequent public backlash. Explain the universe where humans are rational enough to give "proportionate" attention to tech as novel as self-driving cars, yet irrational enough to have preferred private car ownership over mass transit in the first place.

conanbatt 7y ago
Why irrational? Cabs are SO convenient, and public transportation has all kinds of issues world-wide. Buenos Aires, for example, has subsidized metro (about 0.50U$S per ticket) vs a non-subsidized uber (5U$S per ride~) and still the experience is so much better and convenient and reliable that 5U$S is really worth it. I think that the ride-hailing revolution is a classic case of great microeconomics.
- robotresearcher 7y ago
  Uber rides are subsidized by investors.
  - conanbatt 7y ago
    Even better, rich people giving free money to drivers and riders world-wide is one the most fantastic charity project in the world.
rayiner 7y ago
Fun fact: the U.S. has among the shortest commute times in the entire OECD, because we rely more on point-to-point private car ownership and less on mass transit: https://www.oecd.org/els/family/LMF2_6_Time_spent_travelling_to_and_from_work.pdf https://www.oecd.org/els/family/LMF2_6_Time_spent_travelling...

justapassenger 7y ago

> ABSURDLY dangerous driving is already It's very dangerous in some places in the world. Majority of deaths are happening in places with poor infrastructure[1], that autonomous vehicles are very far away from being able to handle. For current state of AV, bar it has to meet and exceed are places with good infrastructure, fairly new cars and reasonably good driving culture, as those are first targets of rollout. For example, in Phoenix, AZ, about 250 people die per year from accidents[2], with about 9k miles driven per person[3] and metropolitan area having 4.7m people, to just match human levels AVs to have less than 1 fatality per 170 million miles driven. [1] https://en.wikipedia.org/wiki/List_of_countries_by_traffic-related_death_rate https://en.wikipedia.org/wiki/List_of_countries_by_traffic-r... [2] http://www.city-data.com/accidents/acc-Phoenix-Arizona.html http://www.city-data.com/accidents/acc-Phoenix-Arizona.html [3] https://arizonapirgedfund.org/sites/pirg/files/reports/FINAL%20Bikes%2C%20Trains%20%26%20Less%20Driving%207-14.pdf https://arizonapirgedfund.org/sites/pirg/files/reports/FINAL...

userbinator 7y ago
Majority of deaths are happening in places with poor infrastructure[1], that autonomous vehicles are very far away from being able to handle. In other words, it's still more like a better cruise control: it makes the easy part of driving easier, but doesn't help with the hard parts (and may make them even harder.)

erobbins 7y ago

Driving is not dangerous. Millions of people drive hundreds of millions of miles a day in the US, and the number of deaths is a statistical blip.

kalenx 7y ago
Then, by this reasoning, autonomous driving is not dangerous either.
- erobbins 7y ago
  It's more dangerous, and I trust distributed systems (humans) more than a monolith (waymo). Sure, an individual human may from time to time screw up, but there aren't any defects present in every single person just waiting for the right edge case to appear.
  - jefftk 7y ago
    There definitely are! Consider blind spots / limited field of view, slow reflexes, and tendencies towards distracted driving. AVs certainly have bugs, and some may lead to accidents and even deaths, but each one will be examined in an enormous amount of detail to figure out what sort of edge case it was and prevent similar ones from happening.
_delirium 7y ago
It's a pretty big blip! About 2.2 million people a year are injured in automobile accidents in the U.S., and around 35,000 are killed. Granted, you're still much more likely to die of heart disease. But if we're going to care about any non-disease causes of death or injury at all, automobile accidents are near the top of the ones to worry about. It's a much bigger cause of both deaths and injuries than violent crime is, for example.

ab_c 7y ago

I feel this has been the case with e-scooters in SF. People being disproportionately angry at tech companies for making these devices available. And yet, before them, you'd see an army of social activists riding their bikes thru thru red lights and being general assholes.

computerex 7y ago

I don't necessarily disagree with you, but the comparison between Tesla and Waymo seems absurd. Tesla doesn't have the greatest track record when it comes to safety. Waymo has been moving very slowly and meticulously, and their tech is light-years ahead of Tesla.

rayiner 7y ago

> Of course we all want a safe and responsible rollout of this tech, but people too easily forget how ABSURDLY dangerous driving is already. I don't really understand how this meme gets so much traction. It just ignores the enormous number of miles driven by Americans every year. Last year, Americans drove 3.22 trillion miles. There were about 6 million accidents, or 500,000 miles between accidents. (Or about 37 years of driving at typical rates). Driving results in a death every 85 million miles traveled. Driving is actually very safe. Conversely, because it is so safe, it wouldn't take much to dramatically increase accident rates from driving.

blub 7y ago
I guess many of us have such an inflated sense of self-importance that we think we can save humans from themselves, without stopping to think who will save everyone from crappy software.
michaelt 7y ago
I don't really understand how this meme gets so much traction. The trick is to compare driving deaths to other things where we had a much bigger (or smaller) reaction relative to the number of lives lost. For example, tell someone "cars kill as many people as twelve September-11th attacks every year" and they might wonder where the trillion-dollar war on road deaths is. On the other hand, tell someone "heart disease kills 17 times as many people as cars every year" and you'll give them the opposite impression.

shirro 7y ago

Better driver assist technology could have the same benefits but it is not equally distributed due to cost. Automation is going to go from luxury vehicles to commercial vehicles and be funded by labor savings. Good luck affording even basic collision avoidance tech in a family car if you are an unemployed driver.

nradov 7y ago

Driving is actually quite safe, if you have a late model car with top safety ratings and never drive drunk or distracted.

slavik81 7y ago
Or tired. Or at night, especially on rural roads.
glenneroo 7y ago
As someone else mentioned, there were an estimated 1.3 million road deaths in 2016. The number of injuries is considerably higher. Do you consider that "quite safe"?

agildehaus 7y ago

It's important to remember that flying was ridiculously unsafe when it first appeared. Now they're the safest form of travel. Not to say that self-driving cars will be ridiculously unsafe when the first commercial service appears, but they share one thing with planes: increased safety is an engineering problem. Every incident that occurs with these vehicles will have tons of data and people looking over that data to fix the issue. Human brains can't be fixed, sensors and computer software can.

simion314 7y ago

>I hope we can view these incidents in context. The context is that Tesla hardware is not sufficiently powerful, so they do "optimizations" and ignore stationary objects. This is not a video game where we can trick the player with some clever hacks, if the hardware is not fast enough the solution is to use better hardware and I think is very normal to see in newspaper when "autopilot" hits a wall, it is a public service even if Tesla fans and shareholders don't like it and try to play with numbers to show some statistics to favor Tesla(AFAIK Tesla still keeps the safety numbers they were using to promote their cools stats a secret)

dalbasal 7y ago

Is that such a terrible thing? Sure, our perception of risk and regulatory responses are not statistically accurate. Commercial air travel is much safer than cars, yet regulatory resposnses to risk are stricter. Is that a bad thing? It creates a very safe mode of transport. Going driverless is a new mode, and an opportunity to create a safer future. Why not set a standard that is much higher than human operated cars? Also, a lot is unknown. We won't know what driveless' safety record is until it truly exists in the wild. The economic pressures to go driverless will be immense^. Meanwhile, a high safety standard could require a some counterpressure, and the starting point will set the stage for the future. ^two kinds. It could be a huge win for consumers, with taxis prices halving or better. It is alsi an opportunity to "put capital to work," in a (current) market that is starved for such. A robo-taxi fleet is just the kind of thing a massive fund can erm.. fund.

not_a_moth 7y ago

If you're a top 1% driver, defensive, experienced etc., then putting yourself in an AV means assuming greater risk. If you're in the latter group, you would be rightly horrified each time there's an AV accident. (the "on average across the population it will be safer" doesn't mean anything for drivers who are already well above average)

taneq 7y ago
True, assuming you're in top-1% condition. Even a usually top-1% driver is going to be far worse off if they're tired, or distracted, or had a fight with their partner that morning, etc.
unionpivo 7y ago
Problem is that about half of my friends think they are in that top 1% Besides we need solution that works for 80% of the people. there will always be some edge cases

jillesvangurp 7y ago

Peer pressure will counter initial regulatory hostility. Inevitably there are going to be some early adopter areas and a lot of people scrutinizing what is happening there. When some of those early adopter areas are are getting clear benefits, there's going to be a lot of pressure on neighboring areas to do imitate what their neighbors are doing. From there, it is just a matter of time. Eventually it will turn around and regulation will start making non autonomous driving harder to wield out the remaining accidents involving drunk/tired/incompetent/reckless/etc. drivers. Insurers will be a major factor here. They should start getting some pretty good insights in accident rates involving AVs vs. normal cars.

walrus1066 7y ago

In my view, accidents aren't the main issue, it's more the disruption caused if an AV, with no human driver, encounters the 'freezing robot problem' (I.e. When traffic lights not working, with policeman directing traffic) & gets stuck in a busy city centre, blocking traffic all around. I'm not aware of any fallback remote takeover mechanism that can be used to recover AV's on this situation. EDIT: I'm convinced, that until we majorly overhaul our road infrastructure to be more 'robot friendly', it's hard to see _fully_ autonomous AV's work in major cities I.e. electronic beacons on lane dividers, electronic signals on traffic lights, vastly stronger GPS network or replacement thereof, six nines level mobile network coverage at high bandwidth.

Traster 7y ago

Well we're really talking about two different things here: The first one is manufacturing a product, and the second is using the product. It's systemic risk. Airplane manufacturing is extremely highly regulated - the reason being that if there's a bug, then the bug is in every airplane. And when that bug appears there's often very little opportunity to mitigate it and the consequences are huge, it's the Manufacturer that's responsible, but the passengers (and bystanders) who pay the price. Similarly, the standard for safety in car manufacture is much higher than the standard of safety for becoming a driver. Partly because the problems for the former are systematic, and partly because the latter primarily poses a risk to themselves. There's self-regulation there. When Tesla tells everyone they have autopilot it isn't Elon Musk whose Tesla slams into a lane divider at 70mph, it's one of the customers he lied to, and it's likely not even one customer, it's a systematic issue where every driver in that situation will face danger.

otakucode 7y ago

>I hope we can view these incidents in context. That is extremely unlikely and borders on impossible. AVs have some profound things working against them. They share the problem airplanes have. Human beings are abysmal at risk estimation, and a very large factor of the estimation they do is whether they have personal control. It doesn't matter that planes are much safer than driving, the fact that people don't have direct control of the aircraft makes them feel unsafe to the point that some people are paralyzed by their fear of flying. The same will be true of AVs, and for the same (un)reasons. But I have my own doubts that it will even get far enough for that to pose a serious problem. We have a more general problem with technology in our society. It is nearly unanswerable to the law. Take the Toyota "unintended acceleration" scandal from a few years ago for example. Investigation of that issue determined firmware flaws were the cause, and led to the deaths of over a dozen people. The criminal court case against Toyota unearthed that while the automotive industry had coding practices that established 'required' and 'suggested' techniques, lists of around 100 practices. Toyota followed 4 of them. Firmware developers working for Toyota did not even have access to a bug tracker at all. They did not have access to static analysis tools. They had no role in determining scheduling. They were found 'not guilty' for criminal negligence. The reason given by the court was that because the problem involved software, criminal negligence was impossible. No standards exist governing software, and therefor no company can be held criminally responsible regardless of their practices. During the civil case, they were found guilty and responsible for the deaths, but before the jury could award damages, Toyota settled with the victims families. That legal precedent is terrifying. The first AV to market will inevitably be the one that cuts the most corners and is rushed the most in its development. When it kills someone, as is basically guaranteed to happen by simple statistics, the public will be paying more attention than they did to the Toyota case. And when the public at large hears that tech company executives are literally above the law, the outrage and consequences will likely be swift and severe. Sensing political opportunity, the legislators will descend and could very well end up dictating what language must be used, what coding standards must be followed, what tools must be used (you know the tool vendors will be lobbying hard), etc. The ACM (Association of Computing Machinery) has been discussing this issue for years, debating the potential merits and pitfalls of establishing a licensing system for software engineers. Thus far, the discussion always ends with 'companies would have to pay more for licensed developers and the cost of labor must be contained.' The looming pitfall of avoiding certification and licensing, however, is that government will step in and do it themselves which is virtually guaranteed to enact the greatest pain on the software industry.