3 ms·

None of those limitations should have mattered in this case, since they all relate to the sensors. We can see the Tesla's view of the world on screen. It knows

None of those limitations should have mattered in this case, since they all relate to the sensors. We can see the Tesla's view of the world on screen. It knows there are double yellow lines. It knows there is a car in the oncoming lane. It just decides to drive diagonally into oncoming traffic anyway for some reason. There's no way you can blame this on sensor problems. It's just a plain old software bug.

ra7 4y ago
I think this is also a perception failure. If you closely watch the video, the detected car appears on the visualization way too late after the Tesla has already swerved to the oncoming lane. A good enough sensor stack (read Lidar) would have detected a solid obstacle at X distance (real measurement) way earlier than a camera making sense of the pixels, classifying it as an object and then providing an ML estimated distance (not real measurement) to the object. All you need in this scenario is to be able to tell there is an obstacle without having to even know it's a car, which Lidar is very good at doing.
- ntoskrnl 4y ago
  Hmm, the view of the screen isn't clear enough to tell when exactly the car appears. An eerily familiar problem, lol. But that's kind of beside the point. Here's a screengrab of slightly sooner, at 8:05. https://i.imgur.com/Hj6glgu.png https://i.imgur.com/Hj6glgu.png The car made a plan to cut across the yellows and then continue straight down the opposing lane. It shouldn't do that whether or not it sees traffic up ahead.
  - ra7 4y ago
    https://imgur.com/a/y1MDoUn https://imgur.com/a/y1MDoUn Here's the screen grab of when it decides to cut across the yellows (see the path plotted). The car is clearly visible in the oncoming lane with headlights on. There's also another car closer in the farther left lane. Neither of them is detected in the visualization. This is where a system with more robust sensors would detect objects way earlier and would never decide to cross lanes, whether it's double yellow or not. https://imgur.com/a/o7hV45F https://imgur.com/a/o7hV45F Here's after it has crossed the yellow lines. The car is again clearly visible, but no detection yet. Clear perception failure.
    - dcow 4y ago
      Interesting how the oncoming car appears to have one brighter headlight than the other. I wonder if that's what confused it...
      - HackOfAllTrades 4y ago
        Following that thought... confused it into thinking what? (Allowing for anthropomorphic use of 'thought'.) Really, the key here is that it's on-screen model shows the yellow lines. It must have become terminally confused to plot that course. Looks like it threw away the model and the rules and just decided to end it all. Headline: "Tesla computer, in fit of depression, commits murder/suicide". (With a number of !s appropriate to the publishing venue.) What's the name for the slash marks sometimes found on suicide victims, where they tried to cut their own throat or wrists several times before they succeed? Hesitation marks? Maybe that's what we're seeing here. /facetious
    - ntoskrnl 4y ago
      I agree there were perception failures, but that's besides the point. The car made a plan to drive on the wrong side of the road. It shouldn't ever do that, no matter what it perceives. It's illegal whether or not there's oncoming traffic. You can't blame sensors for those kinds of logic errors. On the plus side, the computer did say "I'm sorry" after almost killing the driver. So I guess that's something.

ra7 4y ago

I think this is also a perception failure. If you closely watch the video, the detected car appears on the visualization way too late after the Tesla has already swerved to the oncoming lane. A good enough sensor stack (read Lidar) would have detected a solid obstacle at X distance (real measurement) way earlier than a camera making sense of the pixels, classifying it as an object and then providing an ML estimated distance (not real measurement) to the object. All you need in this scenario is to be able to tell there is an obstacle without having to even know it's a car, which Lidar is very good at doing.

ntoskrnl 4y ago
Hmm, the view of the screen isn't clear enough to tell when exactly the car appears. An eerily familiar problem, lol. But that's kind of beside the point. Here's a screengrab of slightly sooner, at 8:05. https://i.imgur.com/Hj6glgu.png https://i.imgur.com/Hj6glgu.png The car made a plan to cut across the yellows and then continue straight down the opposing lane. It shouldn't do that whether or not it sees traffic up ahead.
- ra7 4y ago
  https://imgur.com/a/y1MDoUn https://imgur.com/a/y1MDoUn Here's the screen grab of when it decides to cut across the yellows (see the path plotted). The car is clearly visible in the oncoming lane with headlights on. There's also another car closer in the farther left lane. Neither of them is detected in the visualization. This is where a system with more robust sensors would detect objects way earlier and would never decide to cross lanes, whether it's double yellow or not. https://imgur.com/a/o7hV45F https://imgur.com/a/o7hV45F Here's after it has crossed the yellow lines. The car is again clearly visible, but no detection yet. Clear perception failure.
  - dcow 4y ago
    Interesting how the oncoming car appears to have one brighter headlight than the other. I wonder if that's what confused it...
    - HackOfAllTrades 4y ago
      Following that thought... confused it into thinking what? (Allowing for anthropomorphic use of 'thought'.) Really, the key here is that it's on-screen model shows the yellow lines. It must have become terminally confused to plot that course. Looks like it threw away the model and the rules and just decided to end it all. Headline: "Tesla computer, in fit of depression, commits murder/suicide". (With a number of !s appropriate to the publishing venue.) What's the name for the slash marks sometimes found on suicide victims, where they tried to cut their own throat or wrists several times before they succeed? Hesitation marks? Maybe that's what we're seeing here. /facetious
  - ntoskrnl 4y ago
    I agree there were perception failures, but that's besides the point. The car made a plan to drive on the wrong side of the road. It shouldn't ever do that, no matter what it perceives. It's illegal whether or not there's oncoming traffic. You can't blame sensors for those kinds of logic errors. On the plus side, the computer did say "I'm sorry" after almost killing the driver. So I guess that's something.