Supervisors: Dr. Janaki Meena
Our model(fully funtional) won an S-grade in Final Year Project submission of batch 2018 at VIT University. We applied
Driverless cars are the future. It is one of the most trending technology in which almost every major tech giant is trying to get involved. Tesla, Uber, and Google are the leading companies in this sector. As everyone knows, Artificial Intelligence is the foundation of science that powers most of the technology inside self-driving cars. It relies on many important concepts and models of Machine Learning and Deep Learning. The aim of the project is to build an Autonomous Remote-Controlled (RC) car.
The primary goal behind choosing this topic was to get familiar with some of the cutting-edge machine learning concepts and its applications in self-driving cars through project-based-learning.
The input feed from the car would be transferred to a computing source. On the computing source training and predictions would be carried out. For intelligent decision making, deep learning neural networks would be used. Specifically, in this project, Artificial Neural Net implementation of OpenCV is used. The model will take the camera feed as the input and predict left, right, forward and backward commands for the car. For detection of stop signs and traffic signals, OpenCV classifiers have been used. The classifiers have been trained for both positive and negative samples for efficient detection of traffic lights and stop signs.
Our model(fully functional) won an S-grade in Final Year Project submission of batch 2018 at VIT University.