Abstract:
Artificial intelligence plays a vital role in self driving vehicle. The direction in which
the automotive industry is headed it is expected that autonomous vehicles capable of
driving without human supervision will be released to market in the next decade. The
development of such intelligence is fairly in its early stages. The problem of creating
such intelligence is that the real-world environment is ever-changing. To solve this
problem the autonomous vehicle needs to have such intelligence that it can cope with
the changing real-world environment. We though can achieve such intelligence by
simulating an autonomous self-driving agent in a virtual 2D platform where it will be
able to follow the track on its own. Using supervised learning to solve this problem will
not be an efficient approach to this problem because no matter how much training and
testing is done, it will not be able to keep up with the dynamic real-world environments.
Therefore, we are proposing a novel approach for creating autonomous AI powered
virtual vehicle using Reinforcement Learning.
