Update README.md

README.md

@@ -1,7 +1,7 @@
 # SFND_Unscented_Kalman_Filter
 Sensor Fusion UKF Highway Project Starter Code
 
-<img src="media/ukf_highway.png" width="700" height="400" />
+<img src="media/ukf_highway_tracked.gif" width="700" height="400" />
 
 In this project you will implement an Unscented Kalman Filter to estimate the state of multiple cars on a highway using noisy lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower that the tolerance outlined in the project rubric. 
 
@@ -17,11 +17,15 @@ Note that the programs that need to be written to accomplish the project are src
 
 The program main.cpp has already been filled out, but feel free to modify it.
 
+<img src="media/ukf_highway.png" width="700" height="400" />
+
 `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 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. The Z axis is not taken into account for tracking, so you are only tracking along the X/Y axis.
+
 ---
 
 ## Other Important Dependencies