Advanced Driving Assistance System for Cars Using Raspberry Pi

EasyChair Preprint 9509

Abstract

Hardware implementation of advanced driving assistance system which can be able to identify i). Lane detection and assist system. ii). Blind spot detection and warning system (BSDW). iii). Forward collision and warning system (FCWS). iv). Pedestrian detection system. The primary goal of the developed system is to identify the above features in order to prevent accidents on the road and ensure pedestrian safety. Methods: The suggested method uses a canny edges detection algorithm is used to detect road edges. The input to this system is images captured by the camera with the help of the Open CV library a python image processing algorithm is created that tracks the lane. Histogram of Orientation (HOG) using the sliding window method is used for pedestrian detection. The control unit for the proposed system is Raspberry Pi module 3B, JSN-SR04T ultrasonic sensor and HC-SR04 ultrasonic sensor has been used for (BSDW) system and (FCWS) respectively. Findings: Results demonstrate that the suggested technique can accurately recognize both straight and curved lanes using edge detection algorithm, and also able to identify vehicles in Blind spot area. Novelty: This technology has a high demand in the automotive industry and the system can be implemented in all the future cars which can able to reduce the accident rates.

Keyphrases: Adaptive Cruse Control, Autonomous Driving Assistance system, Forward collision, Lane Detection System, OpenCV, blind spot detection, pedestrian detection

@booklet{EasyChair:9509,
  author    = {A C Ramachandra and V Viswanatha and H Suhas and K Kishor},
  title     = {Advanced Driving Assistance System for Cars Using Raspberry Pi},
  howpublished = {EasyChair Preprint 9509},
  year      = {EasyChair, 2023}}