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README

CarlaFLCAV

carla_flcav

CarlaFLCAV is an open-source FLCAV simulation platform based on CARLA simulator that supports:

  • Multi-modal dataset generation: Including point-cloud, image, radar data with associated calibration, synchronization, and annotation

  • Training and inference: Examples for CAV perception, including object detection, traffic sign detection, and weather classification

  • Various FL frameworks: FedAvg, device selection, noisy aggregation, parameter selection, distillation, and personalization

  • Optimization based modules: Network resource and road sensor pose optimization.

Demo

https://user-images.githubusercontent.com/38368612/206344921-f52956af-86bc-48b6-aee1-388febc233d7.mp4

Federated SECOND for 3D point cloud object detection

https://user-images.githubusercontent.com/38368612/206344904-d2d7d194-d104-4701-a771-a97a6136e3a6.mp4

Federated YOLOV5 for 2D image object detection

https://user-images.githubusercontent.com/38368612/206665655-c8653bb0-3e25-4071-9797-8e76255b4eab.mp4

Federated LSTM for BEV trajectory prediction

https://user-images.githubusercontent.com/38368612/206345017-5c8a764a-44fb-4282-b832-cb8e55090d7d.mp4

Cooperative perceptioin with road sensors for federated distillation

Test Environment

  • Ubuntu 20.04
  • Python 3.8
  • CARLA 0.9.13
  • CUDA 11.3 (Nvidia Driver 470)
  • Pytorch 1.10.0

Citation

CarlaFLCAV can reproduce results in the following papers:

@article{CarlaFLCAV,
  title={Federated deep learning meets autonomous vehicle perception: Design and verification},
  author={Shuai Wang and Chengyang Li and Derrick Wing Kwan Ng and Yonina C. Eldar and H. Vincent Poor and Qi Hao and Chengzhong Xu},
  journal={IEEE Network},
  year={2023},
  volume={37},
  number={3},
  pages={16--25}
}

@article{CarlaFLOTA,
  title={Edge federated learning via unit-modulus over-the-air computation},
  author={Shuai Wang and Yuncong Hong and Rui Wang and Qi Hao and Yik-Chung Wu and Derrick Wing Kwan Ng},
  journal={IEEE Transactions on Communications},
  year={2022},
  volume={70},
  number={5},
  pages={3141--3156}
}

CarlaFLCAV Arxiv version: http://arxiv.org/abs/2206.01748

CarlaFLOTA Arxiv version: https://arxiv.org/abs/2101.12051

Acknowledgement

Authors

Shuai Wang

Chengyang Li

Core symbols most depended-on inside this repo

info
called by 134
FLYolo/yolov5/models/yolo.py
max
called by 103
FLPCDet/pcdet/ops/iou3d_nms/src/iou3d_cpu.cpp
min
called by 74
FLPCDet/pcdet/ops/iou3d_nms/src/iou3d_cpu.cpp
update
called by 54
FLPCDet/pcdet/utils/common_utils.py
tolist
called by 42
FLYolo/yolov5/models/common.py
colorstr
called by 40
FLYolo/yolov5/utils/general.py
save
called by 38
FLYolo/yolov5/models/common.py
run
called by 35
FLYolo/yolov5/utils/callbacks.py

Shape

Method 1,037
Function 719
Class 259
Route 1

Languages

Python97%
C++3%

Modules by API surface

FLYolo/yolov5/models/common.py71 symbols
FLYolo/yolov5/utils/general.py61 symbols
FLYolo/yolov5/models/tf.py52 symbols
FLYolo/yolov5/utils/datasets.py48 symbols
FLFusion/road/Scenario_Infrastructure.py48 symbols
FLDatasetTool/utils/geometry_types.py37 symbols
FLPCDet/tools/train_utils/optimization/fastai_optim.py26 symbols
FLPCDet/pcdet/utils/loss_utils.py26 symbols
FLPCDet/pcdet/ops/pointnet2/pointnet2_stack/pointnet2_utils.py26 symbols
FLYolo/yolov5/utils/torch_utils.py25 symbols
FLYolo/yolov5/utils/plots.py25 symbols
FLPCDet/pcdet/ops/pointnet2/pointnet2_batch/pointnet2_utils.py24 symbols

For agents

$ claude mcp add CarlaFLCAV \
  -- python -m otcore.mcp_server <graph>

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