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My amateur interpretation of this is that the vision algorithm briefly confused the yellow of the headlights of the oncoming car as the double yellow line in th
by SQueeeeeL 5y ago
My amateur interpretation of this is that the vision algorithm briefly confused the yellow of the headlights of the oncoming car as the double yellow line in the road, which caused it to believe it was seriously out of lane. After verring, the algorithm reoriented, and realized an impact was imminent and diverted off the road.
I think what's interesting about this example is that in this case, an alert human driver would not be confused in this way. It shows issues with the particular machine learning approach to automated driving.
- jarolinvargas 5y agoThe driver intervened and lost control. It looks like Autopilot was going all in on that incoming vehicle.
- rightiousrob 5y agoI don't think that a root cause analysis like this is good for anything else than improving the algorithm. It's the same as with face detection. The algorithms are better far superior to humans, but they fail at occasions where a human would not even think twice
- rasz 5y ago>vision algorithm briefly confused the yellow of the headlights of the oncoming car as the double yellow line not the lights, but the vertical lens flares captured by single front facing center mounted camera cluster - afaik Tesla still has no stereo vision. >the algorithm reoriented more like driver jerked to the right while having a heart attack and seeing itself going into a full frontal collision thanks to move fast and break things mentality
- catlikesshrimp 5y agoWow, you just slapped me with this idea: - What should be the core tenet of the self driving system for a car? - Why, of course it should be "Move fast and break things"!
- deleted 5y ago[deleted]