diff --git a/README.md b/README.md
index 7b4f9ab..991f54c 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
 
 This is a module assgnment from Motion Planning for Self-Driving Cars course of Self-Driving Cars Specialization on Coursera.org.
 
-This assginment implements Lane Keeping Assist function by applying pure pursuit method for lateral control and PID controller for longitudinal control using Python as the programming language.
+This assginment implements Lane Keeping Assist function by applying pure pursuit and Stanley methods for lateral control and PID controller for longitudinal control using Python as the programming language.
 
 The waypoints and corresponding velocities for the track are pre-defined.
 
@@ -32,18 +32,22 @@ Open another terminal and do `cd ~/opt/CarlaSimulator/PythonClient/Lane-Keeping-
 
 (optional) do `sudo apt-get install python3-tk` in case you do not have `Tkinter` module.
 
-Then do `python3 module_7.py`.
+Then do `python3 module_7.py --control-method Stanley` or `python3 module_7.py --control-method PurePursuit`.
 
 The vehicle should starting driving and following the track.
 
 ## Simulation results
-The image shown below is the result of vehicle trajectory.
+The images shown below is the result of vehicle trajectory(Stanley and Pure Pursuit method).
 
 The green line is the track(ground truth) and the orange line is the trajectory.
-<p align="center">
-  <img  src="https://github.com/paulyehtw/Lane-Keeping-Assist-on-CARLA/blob/master/controller_output/trajectory_good.png">
+
+<p align="center"><b>Stanley Method</b>
+  <img  src="https://github.com/paulyehtw/Lane-Keeping-Assist-on-CARLA/blob/master/controller_output/trajectory_Stanley.png">
+</p>
+
+<p align="center"><b>Pure Pursuit Method</b>
+  <img  src="https://github.com/paulyehtw/Lane-Keeping-Assist-on-CARLA/blob/master/controller_output/trajectory_PurePursuit.png">
 </p>
 
 #### TODO
-1. Implement Feed Forward method for longitudinal control.
-2. Implement Stanley and MPC approaches for lateral control.
+- Implement MPC approach for lateral control.