> It is worth pointing out that this strategy can likely overfit on the data that you have used for training: when you change the track, your car may not behave as good as before. In other words: the coefficients are only good for that specific track(s).

More generally, I think this approach is only suited to "static" courses, which only matter in contrived demos. Any real use of a steering algorithm requires reacting to conditions that can't be predicted a priori; e.g. if you have to avoid collisions with other cars, and one car is controlled by a human player, every run is effectively a different track and overfitting like this would not be an option.