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

Real-time Lane detection and Motion Planning in Raspberry Pi and Arduino for an Autonomous Vehicle Prototype