https://github.com/elymsyr/autonomous-car-in-unity
The project mainly aims to develop an autonomous car to complete the NHTSA Levels of Automation in a 3D Unity environment.
https://github.com/elymsyr/autonomous-car-in-unity
autonomous-car autonomous-driving unity unity3d
Last synced: 3 months ago
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The project mainly aims to develop an autonomous car to complete the NHTSA Levels of Automation in a 3D Unity environment.
- Host: GitHub
- URL: https://github.com/elymsyr/autonomous-car-in-unity
- Owner: elymsyr
- License: mit
- Created: 2024-11-08T20:35:30.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-12-20T21:31:35.000Z (6 months ago)
- Last Synced: 2025-02-25T01:43:51.064Z (3 months ago)
- Topics: autonomous-car, autonomous-driving, unity, unity3d
- Language: C#
- Homepage:
- Size: 117 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Security: .github/SECURITY.md
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README
# Autonomous Car in Unity
The project mainly aims to develop an autonomous car using a Unity 3D environment and complete the [NHTSA Levels of Automation](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) one by one. See [Roadmap](#roadmap) and [Technologies](#technologies) for more detail.
## Roadmap
- [x] Simple Unity 3D Environment
- The environment should be suitable for object detection tasks.
- Car controls must be realistic enough to simulate an autonomous vehicle.
- Integration with stereo camera sensors for realistic input data.
- [ ] Road Segmantation and Lane Detection
- [ ] Model Training with Reinforcement Learning for [Level 1](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) Vehicle (Steering) Assist.
- [ ] 3D Object Detection Model (KITTI Dataset)
- Train a 3D object detection model using the KITTI dataset.
- The autonomous car should rely on stereo cameras (no LiDAR).
- Apply the trained model to detect and localize objects in the Unity environment.
- [ ] Bird’s Eye View (BEV) Transformer System
- Implement a BEV Transformer System for 3D space prediction.
- Utilize stereo vision to predict the 3D structure of the environment.
- Explore combining the stereo vision system with more advanced models for enhanced accuracy.
- [ ] [Level 2](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) Vehicle Assist
- [ ] Rule-based System Design for Realistic Traffic Ride
- [ ] [Level 3](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) Vehicle Assist
- [ ] [Level 4](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) Vehicle (Parking in Selected Parking Areas and Highway Riding) Assist
- [ ] [Level 5](https://www.nhtsa.gov/sites/nhtsa.gov/files/2022-05/Level-of-Automation-052522-tag.pdf) Vehicle (Currently Dreaming) Assist
## Documentation
See the detailed [`documentation`](documentaion.html).
## Notes
See my [`notes`](https://elymsyr0000.notion.site/autonomous-systems-python-13652999cef8802a943ae7a23eb94d25?pvs=4).
## License
See the [`LICENSE`](LICENSE)
## Screenshots
Screenshots will be updated.
## Technologies
Technologies will be updated.
## Installation
Installation will be updated.
## Run Locally
Local Run will be updated.
## Support
For support, email [[email protected]](mailto:[email protected]).
## Contributing
All contributions are welcome.
See [`CONTRIBUTING`](CONTRIBUTING.md) for ways to get started.
Please adhere to this project's [`CODE OF CONDUCT`](CODEOFCONDUCT.md).
## Acknowledgements
- [Datasets](https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d)
- [CNN for Road Segmantation](https://www.kaggle.com/code/sakshaymahna/fully-convolutional-network)
## Appendix
Appendix will be updated.