HGARN

Source codes for Activity-aware human mobility prediction with hierarchical graph attention recurrent network., published in IEEE Transactions on Intelligent Transportation Systems (TITS) in 2024.

Requirements

• python == 3.6
• torch == 1.7.0+cu110
• mpu == 0.23.1

See requirements.txt for more details.

Datasets

NYC and Tokyo Check-in Dataset.

Please refer to this repo.

Run

python train.py

Reference

Please cite our paper if you use the model in your own work:

@article{tang2024activity,
  title={Activity-aware human mobility prediction with hierarchical graph attention recurrent network},
  author={Tang, Yihong and He, Junlin and Zhao, Zhan},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2024},
  publisher={IEEE}
}

Acknowledgments

We refer to some of the data processing codes in this repo.