InteractTraj

Language-Driven Interactive Traffic Trajectory Generation

Environment setup

git clone -b dev https://github.com/X1a-jk/InteractTraj.git
cd InteractTraj

# Create virtual environment
conda create -n InteractTraj python=3.8
conda activate InteractTraj

# Install other dependency
pip install -r requirements.txt

Download full dataset

We follow the data processing process in TrafficGen and LCTGen:

1. Download from Waymo Open Dataset:

• Register your Google account in: https://waymo.com/open/
• Open the following link with your Google account logged in: https://console.cloud.google.com/storage/browser/waymo_open_dataset_motion_v_1_1_0
• Download all the proto files from waymo_open_dataset_motion_v_1_1_0/uncompressed/scenario/training_20s
• Move download files to PATH_A, where you store the raw tf_record files.

2. Data Preprocess

python srcs/utils/process_all_data.py PATH_A PATH_B

• Note: PATH_B is where you store the processed data.

3. Change _C.DATASET.DATA_PATH to PATH_B in srcs/configs/path_cfg.py.

Training with full data

chmod +x scripts/train.sh
./scripts/train.sh

Inference and visualization

Modify the path of pre-trained model in srcs/configs/inference.py and the api_key in srcs/utils/inference.py in advance.

python srcs/utils/inference.py

TODO

• arxiv paper release
• code release
• nuPlan dataset preprocess

Related repositories

We use code in TrafficGen and LCTGen. Many thanks to them for the selfless open source of the code and their previous work!

Citation

@misc{xia2024languagedriveninteractivetraffictrajectory,
      title={Language-Driven Interactive Traffic Trajectory Generation}, 
      author={Junkai Xia and Chenxin Xu and Qingyao Xu and Chen Xie and Yanfeng Wang and Siheng Chen},
      year={2024},
      eprint={2405.15388},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2405.15388}, 
}