  We apply Deep Q-network (DQN) with the consideration of safety during the
task for deciding whether to conduct the maneuver. Furthermore, we design two
similar Deep Q learning frameworks with quadratic approximator for deciding how
to select a comfortable gap and just follow the preceding vehicle. Finally, a
polynomial lane change trajectory is generated and Pure Pursuit Control is
implemented for path tracking. We demonstrate the effectiveness of this
framework in simulation, from both the decision-making and control layers. The
proposed architecture also has the potential to be extended to other autonomous
driving scenarios.
