/CarND-MPC-Project

Primary LanguageC++

CarND-Controls-MPC

Self-Driving Car Engineer Nanodegree Program

This is a project for Udacity MPC.

The Model

We use the kinematickinematic model for the vehicle in this project. The states for the model are: [x,y,psi,v] which stand for the position in x and y, the yaw angle, and the speed. The actuators are [delta,a] which stand for the steering angle and the acceleration. The state update equations are

and the error equations are

Parameters

This project uses N=15 and dt=0.05. The weights for the costs are: 1, 10, 1 for the reference states and 10, 1, for the actuators and 600, 1 for sequential actuation. We use a large weight on the cost relates to the change of delta to ensure a smooth change of steering angle. We use dt=0.05 so that a the delay of 100ms can be incorporate easily. N0=15 is to ensure that the trajectory extend long enough into the future but not to long to cost a numerical instability. The target speed is set for 60mph. The parameters tried before are all be 1 expect the change of delta to be 500, which also works.

Way points

The way points are used to fit to a third order polynomial. The fitting process is in the car coordinates, so that the way points are transformed from the map coordinates to the car coordinates. One thing to notice is that the map coordinates are left-handed while the car coordinates are right-handed so the y values from in the map coordinates are reversed before the coordinate transformation.

Latency

There is a 100ms delay in the code to simulate the latency of the actuations. In order to account the latency, we use the solution from the solver at a t=0.1s delay. A better way is to transform the vehicle location using the motion model.

Dependencies

  • cmake >= 3.5
  • All OSes: click here for installation instructions
  • make >= 4.1
  • gcc/g++ >= 5.4
  • 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.
  • Fortran Compiler
    • Mac: brew install gcc (might not be required)
    • Linux: sudo apt-get install gfortran. Additionall you have also have to install gcc and g++, sudo apt-get install gcc g++. Look in this Dockerfile for more info.
  • Ipopt
    • Mac: brew install ipopt
    • Linux
      • You will need a version of Ipopt 3.12.1 or higher. The version available through apt-get is 3.11.x. If you can get that version to work great but if not there's a script install_ipopt.sh that will install Ipopt. You just need to download the source from the Ipopt releases page or the Github releases page.
      • Then call install_ipopt.sh with the source directory as the first argument, ex: bash install_ipopt.sh Ipopt-3.12.1.
    • Windows: TODO. If you can use the Linux subsystem and follow the Linux instructions.
  • CppAD
    • Mac: brew install cppad
    • Linux sudo apt-get install cppad or equivalent.
    • Windows: TODO. If you can use the Linux subsystem and follow the Linux instructions.
  • Eigen. This is already part of the repo so you shouldn't have to worry about it.
  • Simulator. You can download these from the releases tab.
  • Not a dependency but read the DATA.md for a description of the data sent back from the simulator.

Basic Build Instructions

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

Tips

  1. It's recommended to test the MPC on basic examples to see if your implementation behaves as desired. One possible example is the vehicle starting offset of a straight line (reference). If the MPC implementation is correct, after some number of timesteps (not too many) it should find and track the reference line.
  2. The lake_track_waypoints.csv file has the waypoints of the lake track. You could use this to fit polynomials and points and see of how well your model tracks curve. NOTE: This file might be not completely in sync with the simulator so your solution should NOT depend on it.
  3. For visualization this C++ matplotlib wrapper could be helpful.

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.