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> Driverless cars are coming along just fine. I am curious why you believe this to be the case? Driverless cars have yet to even come close to being workable i

by jimmy1 8y ago

> Driverless cars are coming along just fine. 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.

Fricken 8y ago
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.
- linuxftw 8y ago
  > 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)?
  - Fricken 8y ago
    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.
    - linuxftw 8y ago
      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?
      - Fricken 8y ago
        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.
        linuxftw 8y ago
        And if there are no landmarks, such as you're on a highway or rural area, not in a city?
linuxftw 8y ago
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.
- fipple 8y ago
  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.
  - andymal 8y ago
    People only have to do real driving in the worst conditions? That sounds like it wouldn't work out too well for them.
    - umeshunni 8y ago
      No, there are entire countries that don't have snow.
- tigershark 8y ago
  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.
  - flor1s 8y ago
    Waymo can of course cherry pick the scenarios which they present about. Meanwhile a human driver still has to intervene every few thousands miles.
zanny 8y ago
> 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.
- jimmy1 8y ago
  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.
tim333 8y ago
> 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-yandex-winter-russia 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.
WhiteMonkey 8y ago
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.
briandear 8y ago
Aircraft are the perfect driverless technology candidate.
- xnx 8y ago
  Also trains
  - 100ideas 8y ago
    Yeah and sailboats it’s and horses too! 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.
- stretchwithme 8y ago
  I guess rockets are a kind of aircraft. That's working.
- travisjungroth 8y ago
  Having both flown planes and driven cars, they are definitely not.
ehsankia 8y ago
Waymo already works in light rain, and they've been testing in snow. https://www.engadget.com/2018/05/08/waymo-snow-navigation/ https://www.engadget.com/2018/05/08/waymo-snow-navigation/ 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.
- joe_the_user 8y ago
  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.
bradknowles 8y ago
Improvements have been made in driverless cars, but that doesn’t mean they are perfect. Much more improvement has yet to come before we get to being safe enough with level 5 autonomy. But in the meanwhile, we can also still celebrate the intermediate stepswise improvements that have been made.

by jimmy1 8y ago

Fricken 8y ago

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.

linuxftw 8y ago
> 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)?
- Fricken 8y ago
  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.
  - linuxftw 8y ago
    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?
    - Fricken 8y ago
      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.
      - linuxftw 8y ago
        And if there are no landmarks, such as you're on a highway or rural area, not in a city?

linuxftw 8y ago

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.

fipple 8y ago
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.
- andymal 8y ago
  People only have to do real driving in the worst conditions? That sounds like it wouldn't work out too well for them.
  - umeshunni 8y ago
    No, there are entire countries that don't have snow.
tigershark 8y ago
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.
- flor1s 8y ago
  Waymo can of course cherry pick the scenarios which they present about. Meanwhile a human driver still has to intervene every few thousands miles.

zanny 8y ago

> 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.

jimmy1 8y ago
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.

tim333 8y ago

> 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-yandex-winter-russia 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.

WhiteMonkey 8y ago

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.

briandear 8y ago

Aircraft are the perfect driverless technology candidate.

xnx 8y ago
Also trains
- 100ideas 8y ago
  Yeah and sailboats it’s and horses too! 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.
stretchwithme 8y ago
I guess rockets are a kind of aircraft. That's working.
travisjungroth 8y ago
Having both flown planes and driven cars, they are definitely not.

ehsankia 8y ago

Waymo already works in light rain, and they've been testing in snow. https://www.engadget.com/2018/05/08/waymo-snow-navigation/ https://www.engadget.com/2018/05/08/waymo-snow-navigation/ 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.

joe_the_user 8y ago
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.

bradknowles 8y ago

Improvements have been made in driverless cars, but that doesn’t mean they are perfect. Much more improvement has yet to come before we get to being safe enough with level 5 autonomy. But in the meanwhile, we can also still celebrate the intermediate stepswise improvements that have been made.