CarND-Controls-PID

Self-Driving Car Engineer Nanodegree Program

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PID Controller

The PID controller make a self driving car steering smoothly and it's based on three components.

• The P (proportional) component apply a proportional steering angle correction based on the cross-track error (cte), higher is the cte and higher (and inverse) is the steering angle applied by the P component;

• The D (differential) component apply a differential correction based the actual cte and the previous, this component smooth the overshooting effect caused by the P component;

• The I (integral) component that complete the PID controller by apply a correction to the possible steering bias introduced by the D component.

Each component has an hyperparameter defined as tau.

Hyperparameters tuning

In first place i tried to tuning manually in order to reach at least the bridge, even if the oscillations go out of the road and I've found the following parameters Kp 0.1, Ki 0.001, Kd 2. After that I've implemented the twiddle algorithm by calculating the error whin the sum of the square cte (to avoid negative numbers) in more steps (PID.cpp:56-119). I've followed the basic idea of Ashish Raste in its implementation. The algorithm starts only by call the InitTuning function and ends automatically when reach the maximum steps configured.

With this algorithm it's easier to tuning the PID parameters but I have to be careful and starts with short runs to not make the car going out of the track and after increase the steps included in the error calculation to avoid biases introduced by the straight parts of the track.

• First run:

  • Steps per iteration: 15
  • Maximum iterations: 100
  • Starting parameters: [0.1, 0.001, 2]
  • Tuned parameters: [0.133233, 0.001331, 2.80441]

First tuning run video

• Second run:

  • Steps per iteration: 2000
  • Maximum iterations: 100
  • Starting parameters: [0.133233, 0.001331, 2.80441]
  • Tuned parameters: [0.172805, 0.00130463, 2.85638]

Final run after tuning

Improvements

A possible improvement is use the pid control to tune the throttle of the car to reduce the oscillations during a curve.

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.

Tips for setting up your environment can be found here

Editor Settings

We've purposefully kept editor configuration files out of this repo in order to keep it as simple and environment agnostic as possible. However, we recommend using the following settings:

• indent using spaces
• set tab width to 2 spaces (keeps the matrices in source code aligned)

Code Style

Please (do your best to) stick to Google's C++ style guide.

Project Instructions and Rubric

Note: regardless of the changes you make, your project must be buildable using cmake and make!

More information is only accessible by people who are already enrolled in Term 2 of CarND. If you are enrolled, see the project page for instructions and the project rubric.

Hints!

• You don't have to follow this directory structure, but if you do, your work will span all of the .cpp files here. Keep an eye out for TODOs.

Call for IDE Profiles Pull Requests

Help your fellow students!

We decided to create Makefiles with cmake to keep this project as platform agnostic as possible. Similarly, we omitted IDE profiles in order to we ensure that students don't feel pressured to use one IDE or another.

However! I'd love to help people get up and running with their IDEs of choice. If you've created a profile for an IDE that you think other students would appreciate, we'd love to have you add the requisite profile files and instructions to ide_profiles/. For example if you wanted to add a VS Code profile, you'd add:

• /ide_profiles/vscode/.vscode
• /ide_profiles/vscode/README.md

The README should explain what the profile does, how to take advantage of it, and how to install it.

Frankly, I've never been involved in a project with multiple IDE profiles before. I believe the best way to handle this would be to keep them out of the repo root to avoid clutter. My expectation is that most profiles will include instructions to copy files to a new location to get picked up by the IDE, but that's just a guess.

One last note here: regardless of the IDE used, every submitted project must still be compilable with cmake and make./

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