FDSA-STG: Fully dynamic self-attention spatio-temporal graph networks for intelligent traffic flow prediction
Y Duan, N Chen, S Shen, P Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of transportation and the ever-improving of vehicular technology,
Artificial Intelligence (AI) has been popularized in Intelligent Transportation Systems (ITS) …
Artificial Intelligence (AI) has been popularized in Intelligent Transportation Systems (ITS) …
Automated dilated spatio-temporal synchronous graph modeling for traffic prediction
Accurate traffic prediction is a challenging task in intelligent transportation systems because
of the complex spatio-temporal dependencies in transportation networks. Many existing …
of the complex spatio-temporal dependencies in transportation networks. Many existing …
Attention-based spatial–temporal adaptive dual-graph convolutional network for traffic flow forecasting
Accurate traffic flow forecasting (TFF) is a prerequisite for urban traffic control and guidance,
which has become the key to avoiding traffic congestion and improving traffic management …
which has become the key to avoiding traffic congestion and improving traffic management …
Traffic-GGNN: predicting traffic flow via attentional spatial-temporal gated graph neural networks
Y Wang, J Zheng, Y Du, C Huang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent spatial-temporal graph-based deep learning methods for Traffic Flow Prediction
(TFP) problems have shown superior performance in modeling higher-level spatial …
(TFP) problems have shown superior performance in modeling higher-level spatial …
Spatiotemporal residual graph attention network for traffic flow forecasting
Q Zhang, C Li, F Su, Y Li - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Accurate spatiotemporal traffic flow forecasting is significant for the modern traffic
management and control. In order to capture the spatiotemporal characteristics of the traffic …
management and control. In order to capture the spatiotemporal characteristics of the traffic …
A general traffic flow prediction approach based on spatial-temporal graph attention
C Tang, J Sun, Y Sun, M Peng, N Gan - IEEE Access, 2020 - ieeexplore.ieee.org
Accurate and reliable traffic flow prediction is critical to the safe and stable deployment of
intelligent transportation systems. However, it is very challenging since the complex spatial …
intelligent transportation systems. However, it is very challenging since the complex spatial …
STGAT: Spatial-temporal graph attention networks for traffic flow forecasting
Traffic flow forecasting is a critical task for urban traffic control and dispatch in the field of
transportation, which is characterized by the high nonlinearity and complexity. In this paper …
transportation, which is characterized by the high nonlinearity and complexity. In this paper …
Graph attention network with spatial-temporal clustering for traffic flow forecasting in intelligent transportation system
Y Chen, T Shu, X Zhou, X Zheng… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
With the development of the Internet of Things (IoT) and 5G technologies, IoT devices
deployed on roads are able to collect a large amount of traffic data at any time. Road …
deployed on roads are able to collect a large amount of traffic data at any time. Road …
MS-Net: Multi-source spatio-temporal network for traffic flow prediction
Predicting urban traffic flow is a challenging task, due to the complicated spatio-temporal
dependencies on traffic networks. Urban traffic flow usually has both short-term neighboring …
dependencies on traffic networks. Urban traffic flow usually has both short-term neighboring …
Pdformer: Propagation delay-aware dynamic long-range transformer for traffic flow prediction
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 …
range of applications. The fundamental challenge in traffic flow prediction is to effectively …