  This report demonstrates several methods used to make a self-driving vehicle
using a supervised learning algorithm and a forward-facing RGBD camera. The
project originally involved research in creating an adversarial attack on the
vehicle's model, but due to difficulties with the initial training of the car,
the plans were discarded in favor of completing the imitation learning portion
of the project. Many approaches were explored, but due to challenges introduced
by an unbalanced data set, the approaches had limited effectiveness.
