This repository contains the codebase and documentation for the "Reinforcement Learning Model for Platooning in Autonomous Driving" project. The project aims to develop an intelligent system using reinforcement learning to enable autonomous vehicles to platoon effectively, enhancing traffic flow, fuel efficiency, and road safety.
- Design a reinforcement learning model that optimizes platooning decisions such as vehicle spacing, speed adjustments, and lane changes.
- Create a simulation environment that accurately represents real-world driving scenarios to train and evaluate the model.
- Integrate the reinforcement learning model with the broader context of autonomous driving decision-making.
- Evaluate the model's performance based on metrics like traffic efficiency, fuel consumption, and safety.
- Python 3.x
- [List any additional prerequisites]
- Clone this repository:
git clone https://github.com/your-username/platooning-rl-project.git - Navigate to the project directory:
cd platooning-rl-project - Install required dependencies:
pip install -r requirements.txt - [Add any other installation instructions]
- [Explain how to run/execute the project]
- [Provide command line examples or usage instructions]
[Explain how others can contribute to your project]
[Specify the project's license]
[Give credit to any resources, libraries, or individuals that inspired or supported your project]