PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction

arXiv:2301.07945v3 Announce Type: replace
Abstract: As a core technology of Intelligent Transportation System, traffic flow prediction has a wide range of applications. The fundamental challenge in traffic flow prediction is to effectively model the complex spatial-temporal dependencies in traffic data. Spatial-temporal Graph Neural Network (GNN) models have emerged as one of the most promising methods to solve this problem. However, GNN-based models have three major limitations for traffic prediction: i) Most methods model spatial dependencies in a static manner, which …

abstract applications arxiv challenge core cs.lg data delay dependencies dynamic flow gnn graph graph neural network intelligent intelligent transportation network neural network prediction propagation spatial technology temporal traffic transformer transportation type