NavDrive: Next-Gen Automated Vehicle Driving with Real-time Intelligent Vision and Engineering

Abstract: The Development of Autonomousvehicles has increased significant attention due to their potential to enhance safety, efficiency and accessibility in transportation. This study focuses on the development of NavDrive, a low-cost autonomous vehicle prototype, which is possible by using the raspberry pi 3, Arduino and the machine learning concept called Behavioral Cloning(BC) – Imitation with the Convolutional Neural Network(CNN). the methodology includes three key faces, data collection, model making, implementation. The data collection by driving the car manually on the custom design indoor track using the white sheets and black tape. The prototype is controlled using the rf based transmitter and receiver. The prototype is equipped with the raspberry pi camera and various other modules ,for the training of the sequential CNN model to mimic the human driving behaviorand the deployment of the model on the raspberry pi to enable the autonomous navigationThe outcomes of this project demonstrate the feasibility of creating a functional autonomous vehicle using readily available and affordable hardware, offering valuable insights into the challenges and successes of such an implementation and highlighting its potential as an educational prototype for exploring autonomous driving principles.