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Tesla "Autopilot" cannot see stationary objects. It has a radar, but it is 1-D and low resolution. It uses this to localize other moving cars. In theory, it

Tesla "Autopilot" cannot see stationary objects. It has a radar, but it is 1-D and low resolution. It uses this to localize other moving cars. In theory, it could use this to see a highway divider or firetruck it's about to hit, but since it's 1-D that would also mean that it would have to slam on the brakes when it sees an overpass coming up, because it can't tell the difference between an overpass and a highway divider or a firetruck. It can assume that overpasses aren't driving at 60mph, so it will see other cars. The Tesla algorithm is "look for lane markings and try to stay between them, and don't hit any moving vehicles. If there is any stationary object, including another a vehicle in your lane, the "Autopilot" will plow right into it. If they're not explaining this to customers, it's negligent.

aerovistae 8y ago
source?
- deelowe 8y ago
  https://www.wired.com/story/tesla-autopilot-why-crash-radar/ https://www.wired.com/story/tesla-autopilot-why-crash-radar/
erikb 8y ago
Also there was a car between the truck and the Tesla for some time. Since they are not specific about the timing, the car in front might have just avoided the truck which leaves little time for sensors below the lights to even register that there is something else. Does Tesla also have sensors at the top to see two+ cars ahead?
- piva00 8y ago
  My gripe with this argument is that even some humans can have a reaction time to at least start braking under these circumstances, I don't mean all drivers but as an example: I raced go-karts (just as an amateur but took some lessons and also some racing classes in cars with 300 hp) and sometimes my reflexes while racing were surprising, even for myself, narrowly avoiding collisions at 100+ km/h in tight circuits. With that said I'd have thought that sensors and computers could be much faster than even my trained reflexes.
  - barrkel 8y ago
    In a continuous system like racing, there are two more things to consider: prediction and relative motion. Avoiding something you can predict, or avoiding something which is moving much slower than 100+ km/h relative to you, isn't too difficult (I do it all the time on motorbikes and scooters). But this perception can fool you into thinking you have more control than you do - should something really unexpected occur, your reaction time will surprise you by being slower.
danmaz74 8y ago
What do you mean by "1-D"? If it doesn't measure height, then it would still be 2-D. EDIT: it's a 1-D array of distances, ie, an array of polar coordinates on the 2-D plane. So, it's 2-D data.
- willvarfar 8y ago
  So its 2D if it returns a 1D array of distances? If it returns a 2D array then its 'seeing in 3D'. So I guess that works out.
  - danmaz74 8y ago
    Ok, now I understand the confusion. The array is 1-D, but it is a representation of polar coordinates on the 2-D plane. So, the data is 2-D.
- cameldrv 8y ago
  Definitely, these things are subject to differences of opinion in terminology. What I mean is that Tesla's radar produces something like 1-3 1-D arrays as output. Those arrays are probably distance, intensity, and doppler. A normal camera produces three 2-D array of R, G, and B. Something like a Kinect produces arrays of R, G, B, and depth/distance. When one of the parameters is distance, sometimes people talk about a sensor having an extra 0.5D. A Kinect might be 2.5D. In this world, the Tesla radar is 1.5D. Fundamentally though, it can't discriminate by height, and so it can't solve the overpass/overhead sign problem. In a very real sense, that is why these accidents have happened.
  - danmaz74 8y ago
    I got it later - I'm not used to the terminology, thanks for the explanation :)
stoddur 8y ago
Precicely this scenario you are describing is in the owners manual that comes with the car.
- fredoralive 8y ago
  Nobody actually reads the manual though.
  - madez 8y ago
    I read manuals, back-to-back. Admittingly, I skip legalese disclaimers because they are intellectual noise. However, many manuals contain golden nuggets of information revealing that most people misuse a certain product or don't use it the best possible way. A well written manual can be a teaching lesson about the relevant stuff given by domain experts for regular users. Who'd say No to that?
    - saiya-jin 8y ago
      What you describe makes complete sense and is very logical and I can't agree more. The problem is, most people don't behave very logically, are lazy, scared of any technical details or simply don't understand them and don't even try (it's some technical mumbo jumbo, just gimme remote and how do I turn it on). You can't reach those with a nice manual apart from maybe initial drawings on how to plug things
    - carlivar 8y ago
      Hacker News commenters seem to be a poor representation of the average population.
  - Rapzid 8y ago
    Heaps of people read the manual.
- PhasmaFelis 8y ago
  I feel like this is the kind of thing you should be made aware of (for real, not just in impenetrable terms of service) before you even buy the car.
econochoice 8y ago
> If they're not explaining this to customers, it's negligent. Offering a footgun to consumers which puts other people in danger is a questionable choice.
- ddoolin 8y ago
  How is this a footgun significantly more than the plethora of other vehicles with the same functionality?
  - realusername 8y ago
    The problem is calling it "Autopilot" in the first place compared to other brands. If you call it "Autopilot", people expect it to be an autopilot.
    - ddoolin 8y ago
      This is kind of a kicking-a-dead-horse discussion, because as others have pointed out, "autopilot will fly you into a mountain" (complete with warnings).
      - carlivar 8y ago
        But does the average driver know that? It is their perception that's important here. The Utah driver expected the car would not fly her into the mountain, so to speak. Naming, marketing context of self driving alongside this feature, and driver instruction are all likely part of the puzzle. If you think the name has nothing to do with it, would you also say that if it had the name "Deluxe Cruise Control" people would treat it the same? I'm not so sure about that. Engineers maybe.
      - lmm 8y ago
        It's a dangerously misleading name in aeroplanes too.
      - mannykannot 8y ago
        I agree that the name issue is a red herring, but not for this reason. Autopilots are operated by people who are trained in their use, and, for the most part [1], understand their limitations. 'Understanding their limitations' is exactly the issue here. [1] Following a number of WTF-type accidents, there is some concern that airplane automation has become too complex for pilots to reason about when it partially fails, but if that is actually the case, it raises the bar for all partial automation, including for cars.
biswaroop 8y ago
But the Autopilot has cameras, and therefore it has 3+1D data (2D frames, 1D inferred depth from stereo or training, 1D time from frame diffs). Even with a 30fps frame rate at 60mph, two frames from a video feed would see the truck move closer by a meter. The network can be trained to distinguish a truck in the lane from an overpass, so those two frames should be sufficient to signal danger. Instead, the car accelerated over 70 meters before the human, again using just her eyes, applied the brakes. This is an edge case, and clearly something that requires more training to avoid. The challenge in edge-case learning is to encounter them often enough, or perhaps create them artificially, and then to ensure the learning can be transferred and generalized to all similar situations.
- pavs 8y ago
  This is not even the first time they hit a giant red stationary fire truck.
  - biswaroop 8y ago
    Seems like it happens whenever a car in front moves out of the way. It goes full stupid-cruise-control mode and just accelerates to the stored speed. Of course there's a lot of noise in terms of things in the stationary reference frame, but still, big red firetrucks don't exactly look like lane markings. At the very least, as a driver, I'm slightly cautious when I see a car move out of the lane in front. I feel like the solution lies in: (a) separating the signal from the noise in the set of things moving with the ground, and (b) getting the car to 'understand' why other cars change lanes. Sometimes it's so they can avoid obstacles in the road. It almost feels like cars need to have a theory of mind of other cars. I certainly drive with an intuition of driver intentions stuck in my head.
    - pavs 8y ago
      The thing is Tesla will never be an autonomous car or a reliable semi-autonomous car with its current hardware. Elon needs to admit it (he insist, this isn't the case) and he needs to reliably convince his customers this isn't the case. Tesla needs to see a couple of cars before, in order to drive safely (these are no edge cases, this happens in real life a lot), but it can't see ahead without LiDAR but Elon insists they don't need LiDAR. The problem is you can't have a pre-existing bias when working with this kind of technology, you need to be able to adapt to whatever changes that need to be made.
spyder 8y ago
And what about the ultrasonic sensors?
sometimesijust 8y ago
The primary sensors are the multiple cameras so this criticism is not relevant. The radar is primarily for low visibility situations (according to marketing). Of course the use of cameras as the primary itself is controversial but they do in theory disambiguate the situations you describe regarding stationary objects, limited resolution, and degrees of vision. In balance: https://www.theverge.com/2018/2/7/16988628/elon-musk-lidar-self-driving-car-tesla https://www.theverge.com/2018/2/7/16988628/elon-musk-lidar-s...
deleted 8y ago
[deleted]

aerovistae 8y ago

source?

deelowe 8y ago
https://www.wired.com/story/tesla-autopilot-why-crash-radar/ https://www.wired.com/story/tesla-autopilot-why-crash-radar/

erikb 8y ago

Also there was a car between the truck and the Tesla for some time. Since they are not specific about the timing, the car in front might have just avoided the truck which leaves little time for sensors below the lights to even register that there is something else. Does Tesla also have sensors at the top to see two+ cars ahead?

piva00 8y ago
My gripe with this argument is that even some humans can have a reaction time to at least start braking under these circumstances, I don't mean all drivers but as an example: I raced go-karts (just as an amateur but took some lessons and also some racing classes in cars with 300 hp) and sometimes my reflexes while racing were surprising, even for myself, narrowly avoiding collisions at 100+ km/h in tight circuits. With that said I'd have thought that sensors and computers could be much faster than even my trained reflexes.
- barrkel 8y ago
  In a continuous system like racing, there are two more things to consider: prediction and relative motion. Avoiding something you can predict, or avoiding something which is moving much slower than 100+ km/h relative to you, isn't too difficult (I do it all the time on motorbikes and scooters). But this perception can fool you into thinking you have more control than you do - should something really unexpected occur, your reaction time will surprise you by being slower.

danmaz74 8y ago

What do you mean by "1-D"? If it doesn't measure height, then it would still be 2-D. EDIT: it's a 1-D array of distances, ie, an array of polar coordinates on the 2-D plane. So, it's 2-D data.

willvarfar 8y ago
So its 2D if it returns a 1D array of distances? If it returns a 2D array then its 'seeing in 3D'. So I guess that works out.
- danmaz74 8y ago
  Ok, now I understand the confusion. The array is 1-D, but it is a representation of polar coordinates on the 2-D plane. So, the data is 2-D.
cameldrv 8y ago
Definitely, these things are subject to differences of opinion in terminology. What I mean is that Tesla's radar produces something like 1-3 1-D arrays as output. Those arrays are probably distance, intensity, and doppler. A normal camera produces three 2-D array of R, G, and B. Something like a Kinect produces arrays of R, G, B, and depth/distance. When one of the parameters is distance, sometimes people talk about a sensor having an extra 0.5D. A Kinect might be 2.5D. In this world, the Tesla radar is 1.5D. Fundamentally though, it can't discriminate by height, and so it can't solve the overpass/overhead sign problem. In a very real sense, that is why these accidents have happened.
- danmaz74 8y ago
  I got it later - I'm not used to the terminology, thanks for the explanation :)

stoddur 8y ago

Precicely this scenario you are describing is in the owners manual that comes with the car.

fredoralive 8y ago
Nobody actually reads the manual though.
- madez 8y ago
  I read manuals, back-to-back. Admittingly, I skip legalese disclaimers because they are intellectual noise. However, many manuals contain golden nuggets of information revealing that most people misuse a certain product or don't use it the best possible way. A well written manual can be a teaching lesson about the relevant stuff given by domain experts for regular users. Who'd say No to that?
  - saiya-jin 8y ago
    What you describe makes complete sense and is very logical and I can't agree more. The problem is, most people don't behave very logically, are lazy, scared of any technical details or simply don't understand them and don't even try (it's some technical mumbo jumbo, just gimme remote and how do I turn it on). You can't reach those with a nice manual apart from maybe initial drawings on how to plug things
  - carlivar 8y ago
    Hacker News commenters seem to be a poor representation of the average population.
- Rapzid 8y ago
  Heaps of people read the manual.
PhasmaFelis 8y ago
I feel like this is the kind of thing you should be made aware of (for real, not just in impenetrable terms of service) before you even buy the car.

econochoice 8y ago

> If they're not explaining this to customers, it's negligent. Offering a footgun to consumers which puts other people in danger is a questionable choice.

ddoolin 8y ago
How is this a footgun significantly more than the plethora of other vehicles with the same functionality?
- realusername 8y ago
  The problem is calling it "Autopilot" in the first place compared to other brands. If you call it "Autopilot", people expect it to be an autopilot.
  - ddoolin 8y ago
    This is kind of a kicking-a-dead-horse discussion, because as others have pointed out, "autopilot will fly you into a mountain" (complete with warnings).
    - carlivar 8y ago
      But does the average driver know that? It is their perception that's important here. The Utah driver expected the car would not fly her into the mountain, so to speak. Naming, marketing context of self driving alongside this feature, and driver instruction are all likely part of the puzzle. If you think the name has nothing to do with it, would you also say that if it had the name "Deluxe Cruise Control" people would treat it the same? I'm not so sure about that. Engineers maybe.
    - lmm 8y ago
      It's a dangerously misleading name in aeroplanes too.
    - mannykannot 8y ago
      I agree that the name issue is a red herring, but not for this reason. Autopilots are operated by people who are trained in their use, and, for the most part [1], understand their limitations. 'Understanding their limitations' is exactly the issue here. [1] Following a number of WTF-type accidents, there is some concern that airplane automation has become too complex for pilots to reason about when it partially fails, but if that is actually the case, it raises the bar for all partial automation, including for cars.

biswaroop 8y ago

But the Autopilot has cameras, and therefore it has 3+1D data (2D frames, 1D inferred depth from stereo or training, 1D time from frame diffs). Even with a 30fps frame rate at 60mph, two frames from a video feed would see the truck move closer by a meter. The network can be trained to distinguish a truck in the lane from an overpass, so those two frames should be sufficient to signal danger. Instead, the car accelerated over 70 meters before the human, again using just her eyes, applied the brakes. This is an edge case, and clearly something that requires more training to avoid. The challenge in edge-case learning is to encounter them often enough, or perhaps create them artificially, and then to ensure the learning can be transferred and generalized to all similar situations.

pavs 8y ago
This is not even the first time they hit a giant red stationary fire truck.
- biswaroop 8y ago
  Seems like it happens whenever a car in front moves out of the way. It goes full stupid-cruise-control mode and just accelerates to the stored speed. Of course there's a lot of noise in terms of things in the stationary reference frame, but still, big red firetrucks don't exactly look like lane markings. At the very least, as a driver, I'm slightly cautious when I see a car move out of the lane in front. I feel like the solution lies in: (a) separating the signal from the noise in the set of things moving with the ground, and (b) getting the car to 'understand' why other cars change lanes. Sometimes it's so they can avoid obstacles in the road. It almost feels like cars need to have a theory of mind of other cars. I certainly drive with an intuition of driver intentions stuck in my head.
  - pavs 8y ago
    The thing is Tesla will never be an autonomous car or a reliable semi-autonomous car with its current hardware. Elon needs to admit it (he insist, this isn't the case) and he needs to reliably convince his customers this isn't the case. Tesla needs to see a couple of cars before, in order to drive safely (these are no edge cases, this happens in real life a lot), but it can't see ahead without LiDAR but Elon insists they don't need LiDAR. The problem is you can't have a pre-existing bias when working with this kind of technology, you need to be able to adapt to whatever changes that need to be made.

spyder 8y ago

And what about the ultrasonic sensors?

sometimesijust 8y ago

The primary sensors are the multiple cameras so this criticism is not relevant. The radar is primarily for low visibility situations (according to marketing). Of course the use of cameras as the primary itself is controversial but they do in theory disambiguate the situations you describe regarding stationary objects, limited resolution, and degrees of vision. In balance: https://www.theverge.com/2018/2/7/16988628/elon-musk-lidar-self-driving-car-tesla https://www.theverge.com/2018/2/7/16988628/elon-musk-lidar-s...

deleted 8y ago

[deleted]