5 ms·

Apparently many or all of the current self driving cars don't do well when running into fixed (ie stopped) physical objects. It must mean somehow in the way tha

Apparently many or all of the current self driving cars don't do well when running into fixed (ie stopped) physical objects. It must mean somehow in the way that they detect things, they must have to discount stopped objects, and 'moving objects', like cars are detected in a different way. I'd love to hear more background about why this is the way it is. I agree that when you can't handle this kind of situation in a tesla it really challenges the idea that we'll have total self driving in a year. There must be a lot of software that is under testing that could be more reliable than what they have today, yet the issue is still there. The last part (5 or 10%) of regular software dev is really hard, and it should be even harder for self-driving, never yet approved or safe enough self driving software.

sokoloff 7y ago
I predict we won't have fully autonomous ("total") self-driving in the next 25 years. To think it will be out in the next year or even in the reasonably expected lifespan of currently shipping Teslas is utter folly, IMO.
- flukus 7y ago
  When I see long haul trucks driving along highways with humans only taking over in the populated areas I'll believe full self driving may only be a decade away. Tackling the full self driving consumer market when there's lower hanging fruit makes no sense.
  - sundvor 7y ago
    They could wipe out Über.
- pas 7y ago
  Based on what? It seems this is a classic estimation problem, and we need performance data points to fit a curve. Do we have anyting? Do we even know if this is a problem where we have a chance at accelerated compounding (so exponential improvement rate)?
  - sokoloff 7y ago
    Based on the fact that we don't have acceptable performance on clear, sunny, well-marked roads today, I don't expect that we're within a year of handling snow-covered roads, road detours, human flagged construction details, etc. I think the self-driving car efforts are dramatically underestimating the effort required to close those gaps to zero at least in the hype machine but also perhaps in the daily working cycle. (That's all well and good; I'm sure that any audacious engineering program should discount some of the hardest parts lest everyone get discouraged and never begin.)
ygra 7y ago
As far as I remember, it is because radar gives you too many points that are usually false positives if you don't discard stopped objects (which include signs, guiderails, anything on the border of the road (which you'll be driving right at in a corner, after all)). This is something that ACC in all radar-using cars does, AFAIK. AEB works differently in that stopped objects are tracked, but it only works well at slower speeds. If I had to guess it's because they have to track a potential stationary object over time to determine that, yes, it's an object that concerns us, it's in the way, and it's not just noise. In case of the first trailer crash it apparently looked similar to an overhead sign to the sensors, also approaching a stopped object would be AEB territory, not ACC, which doesn't work well at higher speeds.
- jonathankoren 7y ago
  The first trailer crash wasn't just that it looked like a sign to the vision system. It's that the radar saw it and alerted, but the AEB was configured to do nothing unless both the radar and the vision system alerted. Since it was a white trailer against a bright sky, the vision system couldn't see it. Tesla later pushed a software fix for the AEB to trigger even if only the radar alerted. https://electrek.co/2016/07/01/understanding-fatal-tesla-accident-autopilot-nhtsa-probe/ https://electrek.co/2016/07/01/understanding-fatal-tesla-acc...
- gamblor956 7y ago
  Step 1: identify where stopped objects are relative to the sensor Step 2: if stopped object is immediately not in front of the car, otherwise, ANALYZE IMMEDIATELY because a stopped object is right in front of the car. It's not rocket science, and it's something so ridiculously basic that Tesla's failure to do something this simple borders of gross criminal negligence. It's something their competitors already do; in fact Waymo's problem is that it's too sensitive to stopped objects in front of the vehicle, hence the Waymo's constantly stopping and starting or driving very slowly...but that's the better and safer way to do it, especially when you're testing on real streets with third-party vehicles.
  - deleted 7y ago
    [deleted]
manicdee 7y ago
Autopilot is not self driving. The human is still driving the vehicle and the human is still responsible for stopping the car from hitting things.
- romwell 7y ago
  Well, then what is it doing? Crashing your vehicle into semis when your attention lapses for a second? Then it should be properly marketed as autocrasher, not autopilot. An autopilot that requires that you have your hands on wheels and pay attention at all times is missing the auto part of the autopilot (reminder that auto means self). So such a system can't be called an autopilot.
  - kozak 7y ago
    It's not too bad if you compare it with the meaning of the original word as used in aviation context: a relatively primitive device that automatically keeps the trajectory of the aircraft (regardless of what is ahead by that trajectory). But it does sound misleading when presented to the general public (as opposed to highly trained professionals, which is the case in aviation context).
  - manicdee 7y ago
    It’s auto pilot where pilot means the person steering ng a ship. There is still executive oversight required as in a captain or at least a navigator. It’s not “autodrive”.
    - romwell 7y ago
      sigh Piloting here means "controlling a vehicle", i.e. driving. As in "Formula 1 pilot". Do you think "Formula 1 pilots" are sailors?
  - nick_kline 7y ago
    It's analogous to an autopilot of an airplane. It keeps going straight, direction, speed, altitude. An airplane can fly straight and level right into an airplane. For some reason (partly Teslas'), people look at a tesla autopilot and think it does everything reliable. They used this misleading name, but people should understand it same way they understand a plane's autopilot.
gruturo 7y ago
To my understanding, this is why they don't have a real model of the world. They don't understand that the road signal right ahead of you poses no danger, because you're actually in the middle of a curve and your trajectory won't actually intersect it. Or that driving below a bridge is fine, even though you're pointing straight at it. Once they are sophisticated enough to have an actual world model (something which, to my knowledge, only Waymo actually has ATM) they can stop ignoring static objects. Until then, they would keep slamming the brakes every 30 seconds for all the stuff they don't understand.
- pas 7y ago
  They probably bet on having the DNN figure this out from the data. Of course this seems like a really hard thing. Probably with enough layers and with the right learning tasks it might be able to do it eventually. But the probability for noise and various learning artifacts is enormous, when you want to learn a sort of model of everything road related.
usrusr 7y ago
> they must have to discount stopped objects Well, there are just a lot of them, outside the lane markers, and those never kill you. And while the systems surely try to classify parked cars as well, detection quality isn't under much scrutiny. Then when that one exception is sitting in the lane, good luck, your life depends on a second class feature. Anecdotal evidence suggests that a similar perception vulnerability exists in long distance cyclists who spend many hours on the own road: lanekeeping and pothole/junk avoidance get more and more delegated to subconscious processes which work with eerie (and enticing) reliability. But that "mental autopilot", tuned to the open road, knows the back of cars only as something that pulls away from you, the simple model knows them as something not worth "raising an interrupt" over. Similar learned routines certainly exists with highway driving as well, but when driving, there isn't a class of objects which is routinely there but almost universally not a concern, like backs of cars are for a cyclist. Reports of that cyclist hitting a car parked in the open road always earn a lot of ridicule, but it's not quite as surprising as it seems at first glance (the very majority certainly succeeds at "disengaging" in time, but the exception make the news, same thing in every field)

sokoloff 7y ago

I predict we won't have fully autonomous ("total") self-driving in the next 25 years. To think it will be out in the next year or even in the reasonably expected lifespan of currently shipping Teslas is utter folly, IMO.

flukus 7y ago
When I see long haul trucks driving along highways with humans only taking over in the populated areas I'll believe full self driving may only be a decade away. Tackling the full self driving consumer market when there's lower hanging fruit makes no sense.
- sundvor 7y ago
  They could wipe out Über.
pas 7y ago
Based on what? It seems this is a classic estimation problem, and we need performance data points to fit a curve. Do we have anyting? Do we even know if this is a problem where we have a chance at accelerated compounding (so exponential improvement rate)?
- sokoloff 7y ago
  Based on the fact that we don't have acceptable performance on clear, sunny, well-marked roads today, I don't expect that we're within a year of handling snow-covered roads, road detours, human flagged construction details, etc. I think the self-driving car efforts are dramatically underestimating the effort required to close those gaps to zero at least in the hype machine but also perhaps in the daily working cycle. (That's all well and good; I'm sure that any audacious engineering program should discount some of the hardest parts lest everyone get discouraged and never begin.)

ygra 7y ago

As far as I remember, it is because radar gives you too many points that are usually false positives if you don't discard stopped objects (which include signs, guiderails, anything on the border of the road (which you'll be driving right at in a corner, after all)). This is something that ACC in all radar-using cars does, AFAIK. AEB works differently in that stopped objects are tracked, but it only works well at slower speeds. If I had to guess it's because they have to track a potential stationary object over time to determine that, yes, it's an object that concerns us, it's in the way, and it's not just noise. In case of the first trailer crash it apparently looked similar to an overhead sign to the sensors, also approaching a stopped object would be AEB territory, not ACC, which doesn't work well at higher speeds.

jonathankoren 7y ago
The first trailer crash wasn't just that it looked like a sign to the vision system. It's that the radar saw it and alerted, but the AEB was configured to do nothing unless both the radar and the vision system alerted. Since it was a white trailer against a bright sky, the vision system couldn't see it. Tesla later pushed a software fix for the AEB to trigger even if only the radar alerted. https://electrek.co/2016/07/01/understanding-fatal-tesla-accident-autopilot-nhtsa-probe/ https://electrek.co/2016/07/01/understanding-fatal-tesla-acc...
gamblor956 7y ago
Step 1: identify where stopped objects are relative to the sensor Step 2: if stopped object is immediately not in front of the car, otherwise, ANALYZE IMMEDIATELY because a stopped object is right in front of the car. It's not rocket science, and it's something so ridiculously basic that Tesla's failure to do something this simple borders of gross criminal negligence. It's something their competitors already do; in fact Waymo's problem is that it's too sensitive to stopped objects in front of the vehicle, hence the Waymo's constantly stopping and starting or driving very slowly...but that's the better and safer way to do it, especially when you're testing on real streets with third-party vehicles.
- deleted 7y ago
  [deleted]

manicdee 7y ago

Autopilot is not self driving. The human is still driving the vehicle and the human is still responsible for stopping the car from hitting things.

romwell 7y ago
Well, then what is it doing? Crashing your vehicle into semis when your attention lapses for a second? Then it should be properly marketed as autocrasher, not autopilot. An autopilot that requires that you have your hands on wheels and pay attention at all times is missing the auto part of the autopilot (reminder that auto means self). So such a system can't be called an autopilot.
- kozak 7y ago
  It's not too bad if you compare it with the meaning of the original word as used in aviation context: a relatively primitive device that automatically keeps the trajectory of the aircraft (regardless of what is ahead by that trajectory). But it does sound misleading when presented to the general public (as opposed to highly trained professionals, which is the case in aviation context).
- manicdee 7y ago
  It’s auto pilot where pilot means the person steering ng a ship. There is still executive oversight required as in a captain or at least a navigator. It’s not “autodrive”.
  - romwell 7y ago
    sigh Piloting here means "controlling a vehicle", i.e. driving. As in "Formula 1 pilot". Do you think "Formula 1 pilots" are sailors?
- nick_kline 7y ago
  It's analogous to an autopilot of an airplane. It keeps going straight, direction, speed, altitude. An airplane can fly straight and level right into an airplane. For some reason (partly Teslas'), people look at a tesla autopilot and think it does everything reliable. They used this misleading name, but people should understand it same way they understand a plane's autopilot.

gruturo 7y ago

To my understanding, this is why they don't have a real model of the world. They don't understand that the road signal right ahead of you poses no danger, because you're actually in the middle of a curve and your trajectory won't actually intersect it. Or that driving below a bridge is fine, even though you're pointing straight at it. Once they are sophisticated enough to have an actual world model (something which, to my knowledge, only Waymo actually has ATM) they can stop ignoring static objects. Until then, they would keep slamming the brakes every 30 seconds for all the stuff they don't understand.

pas 7y ago
They probably bet on having the DNN figure this out from the data. Of course this seems like a really hard thing. Probably with enough layers and with the right learning tasks it might be able to do it eventually. But the probability for noise and various learning artifacts is enormous, when you want to learn a sort of model of everything road related.

usrusr 7y ago

> they must have to discount stopped objects Well, there are just a lot of them, outside the lane markers, and those never kill you. And while the systems surely try to classify parked cars as well, detection quality isn't under much scrutiny. Then when that one exception is sitting in the lane, good luck, your life depends on a second class feature. Anecdotal evidence suggests that a similar perception vulnerability exists in long distance cyclists who spend many hours on the own road: lanekeeping and pothole/junk avoidance get more and more delegated to subconscious processes which work with eerie (and enticing) reliability. But that "mental autopilot", tuned to the open road, knows the back of cars only as something that pulls away from you, the simple model knows them as something not worth "raising an interrupt" over. Similar learned routines certainly exists with highway driving as well, but when driving, there isn't a class of objects which is routinely there but almost universally not a concern, like backs of cars are for a cyclist. Reports of that cyclist hitting a car parked in the open road always earn a lot of ridicule, but it's not quite as surprising as it seems at first glance (the very majority certainly succeeds at "disengaging" in time, but the exception make the news, same thing in every field)