Base for machine learnign

In this devlog I prepared everything to start teaching machines how to ride a car - the car was prepared for them. What has been done:

1. Track generation - trach is 4 mathematic functions that create 1000 line segments in total to serve as walls.
2. Optimized ray logic - car will have only 3 sensors (green) that will tell distance till wall
3. Car class itself - for optimization i wont have 1000s of car object but in the class there will be stored vectorized information about all cars operating with numpy
4. Visual part - I will render only one car, but under the hood there will be much more cars training.