Log In Sign Up

Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting

by   Weiqi Chen, et al.

Traffic forecasting is of great importance to transportation management and public safety, and very challenging due to the complicated spatial-temporal dependency and essential uncertainty brought about by the road network and traffic conditions. Latest studies mainly focus on modeling the spatial dependency by utilizing graph convolutional networks (GCNs) throughout a fixed weighted graph. However, edges, i.e., the correlations between pair-wise nodes, are much more complicated and interact with each other. In this paper, we propose the Multi-Range Attentive Bicomponent GCN (MRA-BGCN), a novel deep learning model for traffic forecasting. We first build the node-wise graph according to the road network distance and the edge-wise graph according to various edge interaction patterns. Then, we implement the interactions of both nodes and edges using bicomponent graph convolution. The multi-range attention mechanism is introduced to aggregate information in different neighborhood ranges and automatically learn the importance of different ranges. Extensive experiments on two real-world road network traffic datasets, METR-LA and PEMS-BAY, show that our MRA-BGCN achieves the state-of-the-art results.


page 1

page 2

page 3

page 4


Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting

Traffic forecasting influences various intelligent transportation system...

A Graph and Attentive Multi-Path Convolutional Network for Traffic Prediction

Traffic prediction is an important and yet highly challenging problem du...

Residual Correction in Real-Time Traffic Forecasting

Predicting traffic conditions is tremendously challenging since every ro...

GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs

We propose a new network architecture, Gated Attention Networks (GaAN), ...

Finding Appropriate Traffic Regulations via Graph Convolutional Networks

Appropriate traffic regulations, e.g. planned road closure, are importan...

Cyclic Graph Attentive Match Encoder (CGAME): A Novel Neural Network For OD Estimation

Origin-Destination Estimation plays an important role in traffic managem...