CarND-Controls-PID

Self-Driving Car Engineer Nanodegree Program

Note: This project makes use of Udacity Driving Simulator and Udacity Workspace. Specific imformation please refer to the program website.

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

Clone this repo.
Make a build directory: mkdir build && cd build
Compile: cmake .. && make
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.

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./

Implementation

The p, i, and d of the PID controller are initialized(see PID.cpp, PID::Init() ) and the "cross track error" (cte) is used to calculate the steering value for steering the vehicle.

Describtion of the effect the P, I, D components each had in my implementation.

I Parameter -

P: proportion

This component computes an output proportional to the cte, it can effectively control the vehicle to turn, make it close to the target as soon as possible, but it alse bring oscillates.

I: integration

Only "P" is not enough as the car has the accumulated error of steering which results in oscillation. The integration item computes an output relate to the sum up of the cte over time, it is taken into account to reduce the oscillation.

D: differentiation

Sometimes the car has some fixed bias which makes the correction made by P and D ineffective. I provides an additional correction based on the sum of cte.

How the final hyperparameters were chosen.

The parameters are tuned manually.

When set all P, I, and D as zero. Controller makes steering value zero. The steering angle feedback received is also 0. This means there is no bias in the car. So the "I" can be set to zero. When set a P value as a constant and set I and D as 0, endless oscillation will occur. After tuning and tuning, I got P = 0.28, I =0.0, and D = 2.8. With this controller, the car runs well in the track.

SidSong01/CarND-PID-Controller