This repo contains the code for our paper entitled "Multi-Agent Trajectory Prediction with Heterogeneous Edge-Enhanced Graph Attention Network", IEEE T-ITS, 2022.
pip install -r requirements.txt
The strucutre of the raw INTERACTION Dataset can be found in INTERACTION Dataset Tree.txt.
To obtain the sorted dataset, please refer to INTERPRET_challenge_regular_generalizability_track.
Run bash datapre_run.sh to process all the scenarios provided by the INTERACTION dataset.
Base model -> Heat model -> HeatIR model.
Run python it_all_train.py -m Heat to train the one-channel HEAT-based trajectory predictor.
If you have found this work to be useful, please consider citing our paper:
@article{mo2022multi,
title={Multi-agent trajectory prediction with heterogeneous edge-enhanced graph attention network},
author={Mo, Xiaoyu and Huang, Zhiyu and Xing, Yang and Lv, Chen},
journal={IEEE Transactions on Intelligent Transportation Systems},
year={2022},
publisher={IEEE}
}