>An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. >Worst-case scenario for a well-designed car in

>An obstacle in the LIDAR is an obstacle, there's no common-sense or training needed for the car to know that. >Worst-case scenario for a well-designed car in a situation it can't understand is to park itself and refuse to go on unassisted. All these are false positives. What I object to are the costs of false negatives; A situation where the car mis-recognizes an abnormal situation as normal, and then proceeds to act on it's failed understanding. The Tesla is a good example of this; the car failed to recognize the obstacle in front of it and acted accordingly (namely, crashing full speed into the object). Regardless of the underlying reason, a machine did not recognize it was in an unknown setting, and thus failed to react correctly. A human, on the other hand, notices, and will generally use what capabilities they possess to at least attempt to handle the situation safely. I do acknowledge that self-driving cars will likely be statistically safer, but until these cars completely exceed the all the capabilities of human drivers, I refuse to trust them. Regardless of statistics.