CarND-Controls-PID

Self-Driving Car Engineer Nanodegree Program

Project Basics

In this C++ project, I use a Proportional-Integral-Derivative Controller, or PID for short, in order to drive a simulated car around a virtual track. The project involves implementing the controller primarily for the steering angle of the car (although I used the value from this controller to also determine throttle), as well as tuning coefficients for each PID value in order to calculate a steering angle that keeps the car on the track.

Project Steps

• Implement PID Controller for Steering (optional: controlling throttle as well)
• Optimize init parameters for each PID coefficient

Results / Reflection

A video of the simulated car driving around the track can be found here.

Components of PID

The actual implementation of code for a basic PID controller is fairly straightforward, but making the controller actually perform well is the tough part. Having knowledge of each part of "PID" is important:

• The "P" for proportional means that the car will steer in proportion to the cross-track error, or CTE. CTE is essentially how far from the middle line of the road the car is. This makes sense, as if the car is to the left of the line then you would want to steer to the right; if it is far to the left of the middle with a high CTE then you want a higher steering angle. However, if the coefficient is set too high for P, the car will oscillate a ton, as the car will constantly overcorrect and overshoot the middle. If the coefficient is too low, the car may react too slowly to curves when the car gets off-center with a higher CTE.
• The "I" for integral sums up all CTEs up to that point, such that too many negative CTEs (in this case, meaning the car has been to the left of the middle of the lane for awhile) will drive up this value, causing the car to turn back toward the middle, preventing the car from driving on one side of the lane the whole time. If the coefficient is too high for I, the car tends to have quicker oscillations, and does not tend to get up to a quick speed. A low coefficent for I will cause the car to tend to drift to one side of the lane or the other for longer periods of time.
• The "D" for derivate is the change in CTE from one value to the next. This means that 1) if the derivative is quickly changing, the car will correct itself (i.e. higher steering angle) faster, such as in the case of a curve, and 2) if the car is moving outward from the middle, this will cause the steering to get larger (as the derivative sign will match the proportional sign), but if the car is moving toward the center (meaning the derivative value will be negative), the car's steering angle will get smoothed out, leading to a more smoother driving experience. Too high of a coefficient leads to almost constant steering angle changes of large degrees, where although the car will be well-centered it can hardly move. Too low of a D coefficient will lead to the oscillations being too high with more overshooting.

These behaved fairly in line with what I was expecting.

Finding the right coefficients

I used Twiddle to optimize the parameters and found (0.121, 0.001, 1.0) are the best values. I checked the driving simulation and the car can keep in the lane pretty well.

Dependencies

• cmake >= 3.5
• All OSes: click here for installation instructions
• make >= 4.1(mac, linux), 3.81(Windows)
  • Linux: make is installed by default on most Linux distros
  • Mac: install Xcode command line tools to get make
  • Windows: Click here for installation instructions
• gcc/g++ >= 5.4
  • Linux: gcc / g++ is installed by default on most Linux distros
  • Mac: same deal as make - [install Xcode command line tools]((https://developer.apple.com/xcode/features/)
  • Windows: recommend using MinGW
• uWebSockets
  • Run either ./install-mac.sh or ./install-ubuntu.sh.
  • If you install from source, checkout to commit e94b6e1, i.e.

    git clone https://github.com/uWebSockets/uWebSockets 
    cd uWebSockets
    git checkout e94b6e1
    

    Some function signatures have changed in v0.14.x. See this PR for more details.
• Simulator. You can download these from the project intro page in the classroom.

Fellow students have put together a guide to Windows set-up for the project here if the environment you have set up for the Sensor Fusion projects does not work for this project. There's also an experimental patch for windows in this PR.

Basic Build Instructions

1. Clone this repo.
2. Make a build directory: mkdir build && cd build
3. Compile: cmake .. && make
4. Run it: ./pid.