  Autonomous driving is one of the most recent topics of interest which is
aimed at replicating human driving behavior keeping in mind the safety issues.
We approach the problem of learning synthetic driving using generative neural
networks. The main idea is to make a controller trainer network using images
plus key press data to mimic human learning. We used the architecture of a
stable GAN to make predictions between driving scenes using key presses. We
train our model on one video game (Road Rash) and tested the accuracy and
compared it by running the model on other maps in Road Rash to determine the
extent of learning.
