I've read many times that Autopilot learns as we drive, that Tesla is creating an ultra-precision map based on the cars' experiences on the road. Sounds very convincing and logical. But I still have no clue how that learning process is supposed to work in detail, in particular what kind of user input is used to improve the car's behavior. I read that users report that cars had learned with time to avoid taking certain highway exits, or similar improvements. But it what user action does Autopilot use to "learn"? I think it must be one of these two: A) User steering that causes Autopilot to disengage (like: car wants to take an exit, user brings it back into the straight lane, canceling Autopilot in the process) B) User steering that corrects the heading of the car slightly, Autopilot stays on (like: car is too near the median, I steer it slightly to the right to better center it in the lane) I have problems with either option (and can't think of others): Everybody has to cancel Autopilot occasionally, usually at the same spots, where the car wants to follow the road but we must take a turn. How can the algorithm distinguish between that situation (where there is nothing to learn, the car is doing the right thing but I must take my own route, while most others will want to continue following the road) from the "correction" that keeps the car in straight at an exit ramp? And the slight corrections, they are really difficult (the wheel stiffly wants the car to keep going too far left, in my example), and if I use too much force Autopilot disengages. In any case, my car doesn't show any signs of learning on my daily route, it still wants to hit the traffic island that I must steer around each time (turning off Autopilot in the process ), and it keeps almost hitting the median where in one stretch of road it only recognizes the center line ... How does Auot-Learning really work, does anybody know?