Self-Driving Car Engineer Nanodegree Program
The vehicle model used here is the suggested Global Kinemtic Model. It has 6 states, position of x, and y, velocity, orientation, cross track error and orientation error. 2 actuators are used, throttle ranges from -1 to 1, where negative value means breaking and steering angle from -25 degree to 25 degree. The update equation is as follows:
x_[t+1] = x[t] + v[t] * cos(psi[t]) * dt
y_[t+1] = y[t] + v[t] * sin(psi[t]) * dt
psi_[t+1] = psi[t] + v[t] / Lf * (-delta[t]) * dt
v_[t+1] = v[t] + a[t] * dt
cte[t+1] = f(x[t]) - y[t] + v[t] * sin(epsi[t]) * dt
epsi[t+1] = psi[t] - psides[t] + v[t] * (-delta[t]) / Lf * dt
The delta here is negative because the delta is positive anti-clockwise while the simulator takes the delta negative anti-clockwise.
The timestep here is 100 milliseconds and N is 10. As of the latency the simulator in the VM, The total time T here is set to 1s, and N is set to 10 to lower down the use of CPU. Other values are tested but the final one is 1 second with timestep in 100 milliseconds and number N in 10.
To make life easier, fisrt I change the waypoint received from simulator from map coordinate to vehicle coordinate with coordinate transform equation. Then with the transformed coordinate, the coefficiencies are calculated with ployfit function. the coefficiencies are used to calculate the cross track error and orientation error. the cte is equal with 'polyeval(coeffs, 0)' since the y is 0, and epsi is equal with the first order derivative of reference trajectory. The coefficiencies are also used for the reference trajectory ploting.
As I running the simulator within the virtual machine in the VirtualBox. The latency here is quite significant, which confused me a lot at the beginning. To reduce the impact of latency I put much more weight on the cost of delta change and throttle change. The cost weights are as follows:
const int cte_cost_weight = 20;
const int epsi_cost_weight = 20;
const int v_cost_weight = 1;
const int delta_cost_weight = 10;
const int a_cost_weight = 10;
const int delta_change_cost_weight = 1000;
const int a_change_cost_weight = 1000;
And to tackle with latency, I start projecting the vehicle position forward and slow down the reference velocity. The following choices are tested,
speed | dt | result |
---|---|---|
40 | 0.2 | nok with cost 500 |
40 | 0.3 | nok |
30 | 0.2 | ok with cost 200 |
30 | 0.1 | nok |
10 | 0.1 | ok |
20 | 0.1 | nok |
And it seems that setting 200ms forward with 30 mph can make through the cirle, though the cost is nearly 200.
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cmake >= 3.5
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All OSes: click here for installation instructions
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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
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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
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- Run either
install-mac.sh
orinstall-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
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Ipopt and CppAD: Please refer to this document for installation instructions.
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Eigen. This is already part of the repo so you shouldn't have to worry about it.
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Simulator. You can download these from the releases tab.
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Not a dependency but read the DATA.md for a description of the data sent back from the simulator.
- Clone this repo.
- Make a build directory:
mkdir build && cd build
- Compile:
cmake .. && make
- Run it:
./mpc
.
The docker-compose can run the project into a container and exposes the port required by the simulator to run.
- Clone this repo.
- Build image:
docker-compose build
- Run Container:
docker-compose up
- On code changes repeat steps 2 and 3.
- The MPC is recommended to be tested on examples to see if implementation behaves as desired. One possible example is the vehicle offset of a straight line (reference). If the MPC implementation is correct, it tracks the reference line after some timesteps(not too many).
- The
lake_track_waypoints.csv
file has waypoints of the lake track. This could 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. - For visualization this C++ matplotlib wrapper could be helpful.)
- Tips for setting up your environment are available here
- VM Latency: Some students have reported differences in behavior using VM's ostensibly a result of latency. Please let us know if issues arise as a result of a VM environment.
We have kept editor configuration files out of this repo 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. We omitted IDE profiles to ensure 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 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. 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./
A well written README file can enhance your project and portfolio and develop your abilities to create professional README files by completing this free course.