Bilinear Multi-Head Attention Graph Neural Network for Traffic Prediction

Haibing Hu, Kai Han, Zhizhuo Yin

2022

Abstract

Traffic forecasting is an important component of Intelligent Transportation System (ITS) and it has the significance for reducing traffic accidents and improving public safety. Due to the complex spatial-temporal dependencies and the uncertainty of road network, the research on this problem is quite challenging. Some of the latest studies utilize graph convolutional networks (GCNs) to model spatial-temporal relationships. However, these methods are only based on the linear weighted summation of the neighborhood to form the representation of the target node, which cannot capture the signal between pairwise node interactions. In many scenes, adding pairwise node interaction features is an essential way to better represent the target node. Therefore, in this article, we propose an end-to-end novel framework named Bilinear Multi-Head Attention Graph Neural Network (BMHA-GNN) for traffic prediction. We propose a new aggregation operator which utilizes the weighted sum of pairwise interactions of the neighbour nodes and improves the representation ability of GCN based models. We adopt the encoder-decoder framework, the encoder module outputs the representation of traffic data, and the decoder module outputs the prediction results. The multi-head attention mechanism is introduced to aggregate information of different neighbour nodes automatically and stabilize the training process. Extensive experiments are conducted on two real-world datasets (METR-LA, PEMS-BAY) showing that the proposed model BMHA-GNN achieves the state-of-the-art results.

Paper Citation

in Harvard Style

Hu H., Han K. and Yin Z. (2022). Bilinear Multi-Head Attention Graph Neural Network for Traffic Prediction. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-547-0, pages 33-43. DOI: 10.5220/0010763400003116

in Bibtex Style

@conference{icaart22,
author={Haibing Hu and Kai Han and Zhizhuo Yin},
title={Bilinear Multi-Head Attention Graph Neural Network for Traffic Prediction},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2022},
pages={33-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010763400003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Bilinear Multi-Head Attention Graph Neural Network for Traffic Prediction
SN - 978-989-758-547-0
AU - Hu H.
AU - Han K.
AU - Yin Z.
PY - 2022
SP - 33
EP - 43
DO - 10.5220/0010763400003116