Self-Driving Car Engineer Nanodegree Program
The purpose of this project was to "build a PID controller and tune the PID hyperparameters by applying the general processing flow as described in the lessons," and to "test your solution on the simulator!" The simulator provides cross-track error (CTE), speed, and steering angle data via local websocket. The PID (proportional/integral/differential) controller must respond with steering and throttle commands to drive the car reliably around the simulator track. PID control is a simple control scheme where the error between desired and true state is taken as input, and its value, integral and derivatives are multipled by scalars to compute the commanded control input. The proportional term drives the error to zero, however, this results in error oscillating about the set point. To supress these oscillations a derivative term is introduced.
Finally, due to modeling errors, set point not being zero or other errors, a control based on proportional and derivative term alone can have a drift. To avoid this drift, an integral term is introduced. The integral term accumulates error, and pushes the control in the opposite direction of accumulated error. This results in the steady state offset error to go to zero.
The P, or "proportional", component had the most directly observable effect on the car's behavior. It causes the car to steer proportional (and opposite) to the car's distance from the lane center (which is the CTE) - if the car is far to the right it steers hard to the left, if it's slightly to the left it steers slightly to the right.
The D, or "differential", component counteracts the P component's tendency to ring and overshoot the center line. A properly tuned D parameter will cause the car to approach the center line smoothly without ringing.
The I, or "integral", component counteracts a bias in the CTE which prevents the P-D controller from reaching the center line. This bias can take several forms, such as a steering drift (as in the Control unit lessons), but I believe that in this particular implementation the I component particularly serves to reduce the CTE around curves.
When attempting to perform parameter optimisation using twiddle often the car left the track. So before the complete twiddle implementation it is important to maunally tweak the parameters first such that the car is on te track.Constantly change parameters with settle in steps being 100 and evaluation steps being 2000.After continuous evaluation I settled for the following final values (P: 0.134611, I: 0.000270736, D: 3.05349).
Also, with twiddle the PID controller converges faster but we overshoot drastically at first so it's a tradeoff. The throttle controller was also fine-tuned using the same Twiddle loop.
The throttle control was implemented as,
Throttle=Ksp(speeddesired−speed)−Ks(Steering angle)−DBsteer−DBcte
- 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.shor./install-ubuntu.sh. - If you install from source, checkout to commit
e94b6e1, i.e.Some function signatures have changed in v0.14.x. See this PR for more details.git clone https://github.com/uWebSockets/uWebSockets cd uWebSockets git checkout e94b6e1
- Run either
- Simulator. You can download these from the project intro page in the classroom.
There's an experimental patch for windows in this PR
- 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
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)
Please (do your best to) stick to Google's C++ style guide.
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.
- 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.
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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