In the context of autonomous driving, two main stages are typically implemented: an image processing stage and a control stage. The first aims at extracting useful information from the acquired image while the second employs those information to control the vehicle.
As far as concerning the processing stage, semantic segmentation is typically used. The input image is divided in different areas with a specific meaning (road, sky, car etc...). Here is an example of semantic segmentation:
The output of the segmentation stage is very complex. I am trying to understand how this information is typically used in the control stage, and how to use the information on the segmented areas to control the vehicle.
For simplicity, let's just consider a vehicle that has to follow a path.
TL;DR: what are the typical control algorithms for autonomous driving based on semantic segmentation?