Behavioral Cloning and Obstacle Avoiding for Two Different Autonomous Vehicles

The problem of dynamic path generation for an autonomous vehicle in environments with unmoving and moving obstacles is presented. The first vehicle kinematical and then an complete mathematical model is given by nonlinear equations describing a 12 state dynamical system simulated in Matlab or Simulink environment. The goal is to find the regulator design method for the named autonomous vehicle in 3D- space in situation with infinite number of obstacles. To design the vehicle regulator in this paper the behavioral cloning approach is applied. In behavioral cloning, the system learns from control traces of a human operator. The advantage of the named approach lies in the fact that a complete path can be defined without using sophisticated symbolical models of obstacles. The proposed methodology it substantially differs from the others. The other advantage of the proposed methodology is the fact meaning that some of the learning algorithms enable a complete path off-line defining