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I dunno, if it decided to ignore the pedestrian because she was in the other lane that's extremely troubling. The pedestrian was moving laterally across the roa

I dunno, if it decided to ignore the pedestrian because she was in the other lane that's extremely troubling. The pedestrian was moving laterally across the road. If the car has detected that, it should infer that she might become an obstacle very shortly. Driving is all about predicting the future. Think of every time you've been able to tell that someone is going to change lanes even though their blinker is off, or slowed down when a ball bounces into the street because you know there's going to be a kid following it. If the car isn't capable of that, it's not ready for public streets.

jozzas 9y ago
When combined with her walking a bicycle, I suspect this is an edge case they never tested. It may have tripped up their pedestrian detection or path prediction (or both) if they got inconsistent hits on the bike.
- 51Cards 9y ago
  There in lies what might be core to the issue though. "An edge case we hadn't tested" Perhaps how we DO AI right now just isn't quite ready for situations this complex yet? Maybe AI based on "oh I've experienced something like this before" is not quite enough? Are we able to do better in getting a system that can infer what's about to happen and make decisions without experiencing it directly... or even indirectly? I know some AI systems are able to do this now with limited cases... but it does make me still wonder if 0.05% of the time the complexity of this task is still just a little outside the capabilities of our learning systems. And maybe we only see the results when something bad happens in that tiny window of time when the AI is unsure. I am obviously no AI expert, just what I know from loosely following the field. But things like this cross my mind from time to time.
galdosdi 9y ago
What's most troubling is it doesn't even matter if the uber car thought the slow object in the other lane was a pedestrian, a car, a tree, whatever. Even if it thought the object was say, the most "normal" thing it could be, another car, this would still be a special situation requiring action. Without knowing the objects classification the estimated speed is enough to decide. Why would a car be stopped in the middle of a lane on a fast road? It should be treated as an obstacle that could grow to the side. After all it could be a police, tow, construction, or disabled vehicle, and a cop or tow worker might be about to walk to the side. Actually many states now require by law that you get as far as possible from a lane with a disabled vehicle, as many human accidents have happened. I am convinced uber has been basically pretending to do the mountains of careful and sophisticated crap waymo actually has gone to great lengths to do, and is just racing to put anything out so they can keep stringing investors along as far as they can before the jig is up. Well the jig is up now.
- HankB99 9y ago
  I think target fixation also contributes to accidents involving emergency vehicles on the shoulder. Back to Uber, the number I hear is that they are striving to go better than 13 miles/intervention to prevent an incident. For Waymo this is over 5000 miles. I'm convinced too.

jozzas 9y ago

When combined with her walking a bicycle, I suspect this is an edge case they never tested. It may have tripped up their pedestrian detection or path prediction (or both) if they got inconsistent hits on the bike.

51Cards 9y ago
There in lies what might be core to the issue though. "An edge case we hadn't tested" Perhaps how we DO AI right now just isn't quite ready for situations this complex yet? Maybe AI based on "oh I've experienced something like this before" is not quite enough? Are we able to do better in getting a system that can infer what's about to happen and make decisions without experiencing it directly... or even indirectly? I know some AI systems are able to do this now with limited cases... but it does make me still wonder if 0.05% of the time the complexity of this task is still just a little outside the capabilities of our learning systems. And maybe we only see the results when something bad happens in that tiny window of time when the AI is unsure. I am obviously no AI expert, just what I know from loosely following the field. But things like this cross my mind from time to time.

galdosdi 9y ago

What's most troubling is it doesn't even matter if the uber car thought the slow object in the other lane was a pedestrian, a car, a tree, whatever. Even if it thought the object was say, the most "normal" thing it could be, another car, this would still be a special situation requiring action. Without knowing the objects classification the estimated speed is enough to decide. Why would a car be stopped in the middle of a lane on a fast road? It should be treated as an obstacle that could grow to the side. After all it could be a police, tow, construction, or disabled vehicle, and a cop or tow worker might be about to walk to the side. Actually many states now require by law that you get as far as possible from a lane with a disabled vehicle, as many human accidents have happened. I am convinced uber has been basically pretending to do the mountains of careful and sophisticated crap waymo actually has gone to great lengths to do, and is just racing to put anything out so they can keep stringing investors along as far as they can before the jig is up. Well the jig is up now.

HankB99 9y ago
I think target fixation also contributes to accidents involving emergency vehicles on the shoulder. Back to Uber, the number I hear is that they are striving to go better than 13 miles/intervention to prevent an incident. For Waymo this is over 5000 miles. I'm convinced too.