shivambmishra10/car-automation

CarAutomation

Overview

CarAutomation focused on the development and optimization of NVIDIA's end-to-end learning framework for self-driving cars. The inspiration for this project stems from NVIDIA's pioneering research paper in the field.

The primary goal of CarAutomation is to leverage Convolutional Neural Networks (CNNs) for predicting nuanced steering angles from diverse road images. The intricately tuned model has achieved a remarkable accuracy exceeding 92.5%, showcasing exceptional proficiency in the complex task of self-driving car automation.

Features

• End-to-End Learning Framework: Implementation and optimization of NVIDIA's end-to-end learning framework for self-driving cars.

• Convolutional Neural Network (CNN): Utilization of a finely-tuned CNN for predicting precise steering angles from a variety of road images.

Implementation

To use CarAutomation, follow these steps:

1. Clone the repository: git clone https://github.com/yourusername/CarAutomation.git
2. Install dependencies: pip install -r requirements.txt
3. Run the application: Execute the main script or follow specific instructions mentioned in the project documentation.

Research Paper

For a deeper understanding of the project, refer to the associated research paper available in this repository.

Video Demo

Explore the capabilities of CarAutomation through the video demo provided in this repository.

Contribution Guidelines

We welcome contributions from the community to enhance CarAutomation further. If you have suggestions, found a bug, or want to add a new feature, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.