Open AccessObject and Lane Detection Technique for Autonomous Car Using Machine Learning Approach
Author(s) -
Raja Muthalagu,
Anudeep Sekhar Bolimera,
Dhruv Duseja,
Shaun Fernandes
Publication year - 2021
Publication title -
transport and telecommunication
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.263
H-Index - 14
eISSN - 1407-6179
pISSN - 1407-6160
DOI - 10.2478/ttj-2021-0029
Subject(s) - computer science , artificial intelligence , computer vision , object detection , work (physics) , object (grammar) , machine vision , perception , engineering , pattern recognition (psychology) , mechanical engineering , neuroscience , biology
The main objective of this work is to develop a perception algorithm for self-driving cars which is based on pure vision data or camera data. The work is divided into two major parts. In part one of the work, we develop a powerful and robust lane detection algorithm which can determine the safely drive-able region in front of the car. In part two we develop and end to end driving model based on CNNs to learn from the drivers driving data and can drive the car with only the camera data from on-board cameras. Performance of the proposed system is observed by the implementation of the autonomous car that can be able to detect and classify the stop signs and other vehicles.