Self-Car-Parking

Overview

This project utilizes a Reinforcement Learning (RL) based agent to train a self-parking car. The car can perform different types of parking maneuvers such as perpendicular and parallel parking. The goal is to create an autonomous system that can effectively park a vehicle in a designated space without human intervention.

Getting Started

Follow these instructions to set up the project on your local machine for development and testing purposes.

Prerequisites

Make sure you have Python installed on your system. You can download it from python.org.

Clone the repository

 git clone https://github.com/TejoVK/Self-Car-Parking.git

Set Up a Virtual Environment

It is recommended to create a virtual environment to manage dependencies:

python3 -m venv .venv
source .venv/bin/activate

Install Dependencies

Install the required Python packages using pip:

pip install -r requirements.txt

Running the Application

You can run the application to see the self-parking car in action. There are two scripts available: one for perpendicular parking and another for parallel parking.

Perpendicular Parking

To run the perpendicular parking simulation:

python3 perpend.py

Parallel Parking

To run the parallel parking simulation:

python3 game.py

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

If you have any questions or suggestions, feel free to open an issue or contact the repository owner.