Unscented Kalman Filter

In this project, an Unscented Kalman Filter is implemented to estimate the state of multiple cars on a highway using noisy lidar and radar measurements.

The main program can be built and ran by doing the following from the project top directory.

1. mkdir build
2. cd build
3. cmake ..
4. make
5. ./ukf_highway

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main.cpp is using highway.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 individual 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. The Z axis is not taken into account for tracking, so we are only tracking along the X/Y axis.

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Other Important Dependencies

• 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

Basic Build Instructions

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

Project Instructions and Rubric

This information is only accessible by people who are already enrolled in Sensor Fusion. If you are enrolled, see the project page in the classroom for instructions and the project rubric.