Welcome to the AD-PPnC repository, a comprehensive collection of code, papers, and notes on prediction, planning, and control in autonomous driving.
In this repository, you will find:
- Code: Implementations of various algorithms and techniques used in autonomous driving.
- Papers: A curated list of research papers that have contributed to the field of prediction, planning, and control in autonomous driving.
- Notes: Detailed notes and summaries of key concepts, methodologies, and findings in the domain.
- Prediction: Explore methods for forecasting the behavior of surrounding vehicles and pedestrians.
- Planning: Discover algorithms for path planning, trajectory generation, and decision making.
- Control: Delve into techniques for vehicle control and stability, ensuring safe and efficient driving.
We are in the process of uploading the code and other resources. Please stay tuned and check back soon for updates!
We welcome contributions from the community. If you have any improvements, bug fixes, or new content to add, please feel free to submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.