Hough transforms are "old-school" computer vision. They rely on a know parameter-space, "This is a circle, that is a straight line" and that isn't super robust

Hough transforms are "old-school" computer vision. They rely on a know parameter-space, "This is a circle, that is a straight line" and that isn't super robust to noise or to unfamiliar curves. I don't know for sure, but I imagine these days the techniques are closer to what you're more likely to call Machine Learning. Probably neural net classifiers trained on manually tagged data, and maybe augmented with a lot of map data. Maybe with some memory too -- I want to say you'd use a particle filter, but there's probably some newfangled ML technique that does a better job than those.