5 ms·

No one thinks that you just hook up ML to a camera and you're done. Literally everyone working on this only uses ML for identification. When that Model X crashe

by pkulak 8y ago

No one thinks that you just hook up ML to a camera and you're done. Literally everyone working on this only uses ML for identification. When that Model X crashed into a highway divider, it was because the lines on the road were very faint and there was a fork in the line that actually wasn't the _real_ lane line. The car followed that by mistake, but only because of the misidentification of the lane line. How are more sensors going to tell the difference between a plastic bag and a cat? How does lidar tell you which car is parked on the side of the road and which one is in your path? Relying on a dozen sensors seems like the crutch to me. Nothing about our current world has been designed for lidar and radar. It was designed for binocular vision. Sure, if your only goal is to not hit things at low speed in perfect weather, lidar is great. But you can't get much further than that.

tomp 8y ago
> It was designed for binocular vision Does binocular vision even matter at such distances (i.e. beyond a few meters)? I thought it was only effective for relatively close objects.
- teraflop 8y ago
  Sure, as long as you have reasonably well-calibrated cameras and optics. Back-of-the-envelope calculation: assuming 1920x1080 camera sensors with a 90-degree horizontal field of view, each pixel covers a visual angle of approximately 0.001 radians. If you have two cameras separated by 5 feet horizontally, and your measurements are accurate to within a pixel, then you can measure the distance to an object 500 feet away with roughly 10% accuracy. That's a reasonably conservative following distance at typical highway speeds. And that's just from a single parallax measurement. By using other visual cues (e.g. apparent size of an object whose physical dimensions are known) and averaging measurements across multiple frames, you can get a more accurate measurement.
  - tomp 8y ago
    Ah, I meant for humans. As in, how much is depth-perception actually necessary for driving... Obviously, humans also use higher-level cues, which IMO are much more important.
    - teraflop 8y ago
      Whoops, my bad for skimming the comments and overlooking the context of your question. I found a page [1] that summarizes the level of visual acuity required to obtain a driver's license in each US state. It appears that all states will potentially issue a license to someone with vision in only one eye. Some states impose additional conditions, such as requiring a favorable report from an ophthalmologist, limiting the maximum speed, or restricting the driver to vehicles with outside rear-view mirrors (to compensate for the loss of peripheral vision on one side). [1]: http://lowvision.preventblindness.org/daily-living-2/state-vision-screening-and-standards-for-license-to-drive/ http://lowvision.preventblindness.org/daily-living-2/state-v...
- monocularvision 8y ago
  As evidenced by my username, I can say confidently that you are correct. The depth perception gained from two eyes is only good at very close ranges and doesn’t play a big factor in most driving situations.
01100011 8y ago
Well, my optical sensors(i.e. eyes) provide me with enough information to discriminate a cat from a bag, so I suppose with enough processing we should be able to do the same with a control system. Cars have an added advantage that their vision systems could work in lower light and non-optical wavelengths. I don't see any fundamental issues with getting self-driving cars working. It may not happen in 5 years, but it will happen.
- thanatropism 8y ago
  Yes, but your machine learning algos are much much better.
- eddieplan9 8y ago
  An intelligence animal being able to do something != "with enough processing we should be able to do the same with a control system".
  - ddoolin 8y ago
    Why not?
    - pretendscholar 8y ago
      One possible answer would be that we aren't intelligent enough to create such systems. I don't think that's true but its a possibility.
      - majewsky 8y ago
        > we aren't intelligent enough to create such systems Evolution suggests that you can, in fact, create systems that are more intelligent than what came before them.
        mattnewport 8y ago
        Evolution achieves that in part by a callous disregard for individual lives. The intelligences that evolution has produced are built on an unimaginable pile of corpses. Even Uber doesn't seem quite as willing as mother nature to spend quite so many lives to achieve incremental improvements.
mikedh 8y ago
If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world, which it could have then used to say "there is an object in the path I'm on, maybe I shouldn't plow into it." As opposed to relying on implicit and apparently unreliable cues like lane markers. That particular fatal crash seems like a sensors and geometry problem. "Nothing about our current world has been designed for lidar and radar. It was designed for binocular vision." Really? Was the world designed for binocular vision, or is it just three dimensional? Having more sensors, especially when they have different failure modes seems like the only possible way to create a reliable system. LIDAR isn't super dense, but generally has accurate returns. Binocular vision sucks on untextured objects, like the side of a white truck in the fatal Model S collision. Why wouldn't you want the crutch of both types of measurement?
- gaius 8y ago
  Was the world designed for binocular vision Ermm, actually yes, in the sense that anything human made was designed for and by those with binocular vision themselves.
- pkulak 8y ago
  > If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world No it wouldn't. The whole problem with avoiding stationary objects is that they are _everywhere_. Do you really think radar and vision didn't "see" the barrier? Should it have known that it was in it's path? For sure. But that has nothing to do with sensors. Stationary objects are in our paths constantly while we drive, but we tend not to hit them because they are usually only temporarily so. At 80 mph the difference between a parked car being in our path and not, at the stopping distance of over 300 feet, is only a degree or two of wheel turn. We have enough information. Acting on it appropriately every single second of operation is the problem. > Really? Was the world designed for binocular vision... Yes. That's why we have road signs, stripes on the road, reflectors, lights on cars, lights hung over the road which light up in different colors to indicate right of way, etc. LIDAR is useless with all of the most important signals on our roads.
BugsJustFindMe 8y ago
> How are more sensors going to tell the difference between a plastic bag and a cat? Infrared transparency? Radar cross section? There are so many ways. Sensor doesn't just mean "webcam".
deepnotderp 8y ago
Lidar gives you high precision depth, so you can tell whether or not the car is parked or in the lane.
KKKKkkkk1 8y ago
What do you mean "no one"? Press coverage of Waymo is full of references to engineers who are teaching cars and cars that are learning. The AI car is a big part of the hype.

by pkulak 8y ago

tomp 8y ago

> It was designed for binocular vision Does binocular vision even matter at such distances (i.e. beyond a few meters)? I thought it was only effective for relatively close objects.

teraflop 8y ago
Sure, as long as you have reasonably well-calibrated cameras and optics. Back-of-the-envelope calculation: assuming 1920x1080 camera sensors with a 90-degree horizontal field of view, each pixel covers a visual angle of approximately 0.001 radians. If you have two cameras separated by 5 feet horizontally, and your measurements are accurate to within a pixel, then you can measure the distance to an object 500 feet away with roughly 10% accuracy. That's a reasonably conservative following distance at typical highway speeds. And that's just from a single parallax measurement. By using other visual cues (e.g. apparent size of an object whose physical dimensions are known) and averaging measurements across multiple frames, you can get a more accurate measurement.
- tomp 8y ago
  Ah, I meant for humans. As in, how much is depth-perception actually necessary for driving... Obviously, humans also use higher-level cues, which IMO are much more important.
  - teraflop 8y ago
    Whoops, my bad for skimming the comments and overlooking the context of your question. I found a page [1] that summarizes the level of visual acuity required to obtain a driver's license in each US state. It appears that all states will potentially issue a license to someone with vision in only one eye. Some states impose additional conditions, such as requiring a favorable report from an ophthalmologist, limiting the maximum speed, or restricting the driver to vehicles with outside rear-view mirrors (to compensate for the loss of peripheral vision on one side). [1]: http://lowvision.preventblindness.org/daily-living-2/state-vision-screening-and-standards-for-license-to-drive/ http://lowvision.preventblindness.org/daily-living-2/state-v...
monocularvision 8y ago
As evidenced by my username, I can say confidently that you are correct. The depth perception gained from two eyes is only good at very close ranges and doesn’t play a big factor in most driving situations.

01100011 8y ago

Well, my optical sensors(i.e. eyes) provide me with enough information to discriminate a cat from a bag, so I suppose with enough processing we should be able to do the same with a control system. Cars have an added advantage that their vision systems could work in lower light and non-optical wavelengths. I don't see any fundamental issues with getting self-driving cars working. It may not happen in 5 years, but it will happen.

thanatropism 8y ago
Yes, but your machine learning algos are much much better.
eddieplan9 8y ago
An intelligence animal being able to do something != "with enough processing we should be able to do the same with a control system".
- ddoolin 8y ago
  Why not?
  - pretendscholar 8y ago
    One possible answer would be that we aren't intelligent enough to create such systems. I don't think that's true but its a possibility.
    - majewsky 8y ago
      > we aren't intelligent enough to create such systems Evolution suggests that you can, in fact, create systems that are more intelligent than what came before them.
      - mattnewport 8y ago
        Evolution achieves that in part by a callous disregard for individual lives. The intelligences that evolution has produced are built on an unimaginable pile of corpses. Even Uber doesn't seem quite as willing as mother nature to spend quite so many lives to achieve incremental improvements.

mikedh 8y ago

If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world, which it could have then used to say "there is an object in the path I'm on, maybe I shouldn't plow into it." As opposed to relying on implicit and apparently unreliable cues like lane markers. That particular fatal crash seems like a sensors and geometry problem. "Nothing about our current world has been designed for lidar and radar. It was designed for binocular vision." Really? Was the world designed for binocular vision, or is it just three dimensional? Having more sensors, especially when they have different failure modes seems like the only possible way to create a reliable system. LIDAR isn't super dense, but generally has accurate returns. Binocular vision sucks on untextured objects, like the side of a white truck in the fatal Model S collision. Why wouldn't you want the crutch of both types of measurement?

gaius 8y ago
Was the world designed for binocular vision Ermm, actually yes, in the sense that anything human made was designed for and by those with binocular vision themselves.
pkulak 8y ago
> If the Model X in your example had LIDAR, it would have been able to build up a decently accurate collision model of the world No it wouldn't. The whole problem with avoiding stationary objects is that they are _everywhere_. Do you really think radar and vision didn't "see" the barrier? Should it have known that it was in it's path? For sure. But that has nothing to do with sensors. Stationary objects are in our paths constantly while we drive, but we tend not to hit them because they are usually only temporarily so. At 80 mph the difference between a parked car being in our path and not, at the stopping distance of over 300 feet, is only a degree or two of wheel turn. We have enough information. Acting on it appropriately every single second of operation is the problem. > Really? Was the world designed for binocular vision... Yes. That's why we have road signs, stripes on the road, reflectors, lights on cars, lights hung over the road which light up in different colors to indicate right of way, etc. LIDAR is useless with all of the most important signals on our roads.

BugsJustFindMe 8y ago

> How are more sensors going to tell the difference between a plastic bag and a cat? Infrared transparency? Radar cross section? There are so many ways. Sensor doesn't just mean "webcam".

deepnotderp 8y ago

Lidar gives you high precision depth, so you can tell whether or not the car is parked or in the lane.

KKKKkkkk1 8y ago

What do you mean "no one"? Press coverage of Waymo is full of references to engineers who are teaching cars and cars that are learning. The AI car is a big part of the hype.