In this project, an Unscented Kalman Filter is implemented to track and estimate the state of multiple cars on a highway using noisy lidar and radar measurements as shown.
main.cpp
is usinghighway.h
to create a straight 3 lane highway environment with 3 traffic cars and the main ego car at the center.- The viewer scene is centered around the ego car and the coordinate system is relative to the ego car as well. The ego car is green while the other traffic cars are blue.
- The traffic cars will be accelerating and altering their steering to change lanes.
- Each of the traffic car's has it's own UKF object generated for it, and will update each indidual one during every time step.
- The red spheres above cars represent the (x,y) lidar detection and the purple lines show the radar measurements with the velocity magnitude along the detected angle.
- Tracking is along the X/Z axis only. The Z axis is not taken into account for tracking.
- cmake >= 3.5
- All OSes: click here for installation instructions
- make >= 4.1 (Linux, Mac), 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
- Windows: recommend using MinGW
- PCL 1.2
- Clone this repo.
- Make a build directory:
mkdir build && cd build
- Compile:
cmake .. && make
- Run it:
./ukf_highway
Custom radar and lidar can be generated by modifying the code in highway.h
to alter the cars. Also, tools.cpp
can be modified to
change how measurements are taken, for instance lidar markers could be the (x,y) center of bounding boxes by scanning the PCD environment
and performing clustering.