This post is about self driving cars. If u follow the news u would know that there is already an effort to create auto cars or cars that drive themselves. How is statistical pattern recognition applicable here?
Regression can possibly help us here. Regression is a tool which learns a function whose output is continuous (Models in previous posts were discrete). The idea is simple. Let a human drive a car which also has a on board camera and a device to capture the drivers response to various events on the camera. Over time with a good learner and a good driver, it is possible that the learning system may learn how to drive. There can be a preprocessing stage in front of the camera to seperate out obstacles and other moving bodies. Also it may be necessary to find out the speed of a moving object and try to project it in time and provide the projection data to the learner, this may be necessary as it is impossible to encounter all the auto drivers for a trainer in the training period. (This is based on the assumption that autos are quantum vehicles whose absolute position given its current position can only be determined probabilistically).
Since a rigorous proof that this system will work cannot be given it is better to prove it by building such a system. The only problem is the funding.