This article describes a prototype vehicle that recognizes the lanes of a road and plans its movements accordingly without human intervention. Pi Camera 1.3 captures real-time video and is processed by Raspberry Pi 3.0 Model B. The image processing algorithm is written in Python 3.7.4 using OpenCV 4.2. The Arduino Uno is used to control the PID algorithm that controls the motor controller, which controls the wheels. The algorithms used to detect lanes are the cany edge detection algorithm and the Hough transform. 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 detected. This is the first steering direction. This initial control direction is further smoothed using the cumulative averaging method of the past and the Kalman filter prediction method. The prototype was tested in real time in a controlled environment. Extensive test results show that this prototype can recognize road trails and plan their movements well.
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Component List
- raspberry pi
- webCam
- Powersupply
- wires and connector
Features
- Detects Lane of the road and hepls in future self driving cars
