> Why aren't they driving the cars with the driverless software in learn mode, scaled up to many human drivers that are training the autonomous classifiers edge

> Why aren't they driving the cars with the driverless software in learn mode, scaled up to many human drivers that are training the autonomous classifiers edge case dataset e.g. human driver stops for this particular shaped object (person in darkness entering street) in 99% of cases, so we stop as well. (As opposed to not stopping for a floating grocery bag where it applies the opposite rule to keep driving based off recorded human driving behavior) This basically is being done already - recorded data is hand labeled as ground truth for classifiers. "human in darkness entering the street" might be a rare case, though. Humans in the dark on the sidewalk should be pretty common. > Also, we can detect human gait already can't we? There has to be better signifiers for human life that we can override these computer vision systems with to prevent these tragedies. I'm not a perception expert - it looks like in this case the victim was mostly classified by LIDAR capture. I don't know if the cameras were not good enough for conditions or if their tech was not up to the task. This is sort of a red herring though - even if the victim was classified as "bicycle" or "car" she still should have been avoided. > What about external safety features, such as an external airbag that deploys on impact, cushioning the object being struck if the system senses immediate collision is unavoidable. Some food for thought for anyone working in this space, would love to hear your thoughts and ideas. Why not do this on all cars?