  This paper discusses a vehicle prototype that recognizes streets' lanes and
plans its motion accordingly without any human input. Pi Camera 1.3 captures
real-time video, which is then processed by Raspberry-Pi 3.0 Model B. The image
processing algorithms are written in Python 3.7.4 with OpenCV 4.2. Arduino Uno
is utilized to control the PID algorithm that controls the motor controller,
which in turn controls the wheels. Algorithms that are used to detect the lanes
are the Canny edge detection algorithm and Hough transformation. Elementary
algebra is used to draw the detected lanes. After detection, the lanes are
tracked using the Kalman filter prediction method. Then the midpoint of the two
lanes is found, which is the initial steering direction. This initial steering
direction is further smoothed by using the Past Accumulation Average Method and
Kalman Filter Prediction Method. The prototype was tested in a controlled
environment in real-time. Results from comprehensive testing suggest that this
prototype can detect road lanes and plan its motion successfully.
