Control and Trajectory Tracking for Autonomous Vehicle

Proportional-Integral-Derivative (PID)

In this project I have implemented a PID controller to control the steering and throttle of a vehicle in carla simulator. The trajectory is given by the path planner and PID controller is reponsible for following this trajectory. Implementaion was done by first creating a PID class, creating PID objects for steering and throttle and finally tuning the proportional ,derivative and integral parameters so as to follow the trajectory given by the path planner.The controller was tested in carla simulator and the outputs were plotted using a python script.

Installation

Run the following commands to install the starter code in the Udacity Workspace:

Clone the repository:

git clone https://github.com/udacity/nd013-c6-control-starter.git

Run Carla Simulator

Open new window

• su - student // Will say permission denied, ignore and continue
• cd /opt/carla-simulator/
• SDL_VIDEODRIVER=offscreen ./CarlaUE4.sh -opengl

Compile and Run the Controller

Open new window

• cd nd013-c6-control-starter/project
• ./install-ubuntu.sh
• cd pid_controller/
• rm -rf rpclib
• git clone https://github.com/rpclib/rpclib.git
• cmake .
• make (This last command compiles your c++ code, run it after every change in your code)

Testing

To test your installation run the following commands.

• cd nd013-c6-control-starter/project
• ./run_main_pid.sh This will silently fail ctrl + C to stop
• ./run_main_pid.sh (again) Go to desktop mode to see CARLA

If error bind is already in use, or address already being used

• ps -aux | grep carla
• kill id

Project Instructions

In the previous project you built a path planner for the autonomous vehicle. Now you will build the steer and throttle controller so that the car follows the trajectory.

You will design and run the a PID controller as described in the previous course.

In the directory /pid_controller you will find the files pid_controller.cpp and pid_controller.h. This is where you will code your pid controller. The function pid is called in main.cpp.

Step 1: Build the PID controller object

Complete the TODO in the pid_controller.h and pid_controller.cpp.

Run the simulator and see in the desktop mode the car in the CARLA simulator. Take a screenshot and add it to your report. The car should not move in the simulation.

Step 2: PID controller for throttle:

1. In main.cpp, complete the TODO (step 2) to compute the error for the throttle pid. The error is the speed difference between the actual speed and the desired speed.

Useful variables:

• nx_pt stores the index of waypoint ahead of current position.
• The last point of v_points vector contains the velocity computed by the path planner.
• velocity contains the actual velocity.
• The output of the controller should be inside [-1, 1].

2. Comment your code to explain why did you computed the error this way.

3. Tune the parameters of the pid until you get satisfying results (a perfect trajectory is not expected).

Step 3: PID controller for steer:

1. In main.cpp, complete the TODO (step 3) to compute the error for the steer pid. The error is the angle difference between the actual steer and the desired steer to reach the planned position.

Useful variables:

• The variable y_points and x_point gives the desired trajectory planned by the path_planner.
• yaw gives the actual rotational angle of the car.
• The output of the controller should be inside [-1.2, 1.2].
• If needed, the position of the car is stored in the variables x_position, y_position and z_position

2. Comment your code to explain why did you computed the error this way.

3. Tune the parameters of the pid until you get satisfying results (a perfect trajectory is not expected).

Step 4: Evaluate the PID efficiency

The values of the error and the pid command are saved in thottle_data.txt and steer_data.txt. Plot the saved values using the command (in nd013-c6-control-refresh/project):

python3 plot_pid.py

You might need to install a few additional python modules:

pip3 install pandas
pip3 install matplotlib

Answer the following questions Answers:

• Add the plots to your report and explain them (describe what you see)
• What is the effect of the PID according to the plots, how each part of the PID affects the control command?
• How would you design a way to automatically tune the PID parameters?
• PID controller is a model free controller, i.e. it does not use a model of the car. Could you explain the pros and cons of this type of controller?
• (Optional) What would you do to improve the PID controller?

Project Review: