High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

RPI Guided Vehicle using Image Processing


Ramanand Bhatt , K.J. Somaiya Institute of Engineering & Information Technology; Akshay Divecha, K.J. Somaiya Institute of Engineering & Information Technology; Sharang Bhide, K.J. Somaiya Institute of Engineering & Information Technology


RPi, AGV, Hough Transform, RPi Camera Board


The leading cause of accidents on highways is found to be rash driving and lane cutting. Often it’s a case of not knowing what kind of a vehicle around our vehicle can cause damage in any way. Hence, there is a need for inbuilt safety systems in cars to prevent accidents. The project is based on Raspberry Pi (RPi). As we see nowadays there are automatic controls in many luxurious cars using different sensors for different parameters. Automatic Guided Vehicle(AGV) is nothing but vehicle guideline provided by capturing images of the road. Intelligent driver assistance system will provide guidance to the driver with the help of sensors and white lane detection system as well as help in reverse and parallel parking. The System consists of the camera module used to take continuous video streaming which will be stored into the SD card. The idea is to use Hough transform which is used for edge, curve detection. Basically the aim is to help the driver keep his vehicle in between the the two lines on the road i.e, a lane and provide a lane departure warning should the vehicle cross the white line. Detection of the obstacle in front & rear direction will be done using an ultrasonic sensor which will detect any obstacle within the range of 4 meters. Full driver assistance is provided by detecting the side lane by taking the video streaming by using RPi camera board mounted on the car & obstacle detection is done by using the Ultrasonic sensor module. It is possible to display the distance apart from obstacle on the display. Display consist of TFT screen connected to the system to display.

Other Details

Paper ID: IJSRDV5I21106
Published in: Volume : 5, Issue : 2
Publication Date: 01/05/2017
Page(s): 1222-1224

Article Preview

Download Article