Traffic Flow Prediction Research Based on an Interactive Dynamic Spatial–Temporal Graph Convolutional Probabilistic Sparse Attention Mechanism (IDG-PSAtt)

Z Ding, Z He, Z Huang, J Wang, H Yin - Atmosphere, 2024 - mdpi.com
Accurate traffic flow prediction is highly important for relieving road congestion. Due to the
intricate spatial–temporal dependence of traffic flows, especially the hidden dynamic …

Traffic Flow Prediction Based on Interactive Dynamic Spatio-Temporal Graph Convolution with a Probabilistic Sparse Attention Mechanism

L Chen, L Chen, H Wang… - Transportation Research …, 2024 - journals.sagepub.com
Accurate traffic flow prediction is of great practical significance to alleviate road congestion.
Existing methods ignore the hidden dynamic associations between road nodes, and for the …

STC-PSSA: A New Model of Traffic Flow Forecasting Based on Spatiotemporal Convolution and Probabilistic Sparse Self-Attention

H Zhang, L Chen, X Zhang… - Transportation Research …, 2024 - journals.sagepub.com
Traffic flow forecasting is the foundation of the dynamic control and application of intelligent
transportation systems (ITS). It is also of significant practical value in alleviating road …

[HTML][HTML] Road traffic flow prediction based on dynamic spatiotemporal graph attention network

Y Chen, J Huang, H Xu, J Guo, L Su - Scientific reports, 2023 - nature.com
To improve the prediction accuracy of traffic flow under the influence of nearby time traffic
flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction …

[HTML][HTML] A deep learning framework about traffic flow forecasting for urban traffic emission monitoring system

B Yao, A Ma, R Feng, X Shen, M Zhang… - Frontiers in public …, 2022 - frontiersin.org
As urban traffic pollution continues to increase, there is an urgent need to build traffic
emission monitoring and forecasting system for the urban traffic construction. The traffic …

[HTML][HTML] STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional Networks for Traffic-Flow Prediction

Z Chang, C Liu, J Jia - Applied Sciences, 2023 - mdpi.com
As an important component of intelligent transportation-management systems, accurate
traffic-parameter prediction can help traffic-management departments to conduct effective …

Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction

Y Xu, X Cai, E Wang, W Liu, Y Yang, F Yang - Information Sciences, 2023 - Elsevier
Accurate urban traffic prediction is a critical issue in Intelligent Transportation Systems (ITS).
It is challenging since urban traffic usually indicates high dynamic spatio-temporal …

Research on Traffic Flow Forecasting Based on Dynamic Spatial-Temporal Transformer

H Zhang, H Wang, X Zhang… - Transportation Research …, 2023 - journals.sagepub.com
Accurate traffic flow forecasting is crucial for urban traffic control and route planning. Aiming
at the difficulty in capturing dynamic spatio-temporal complexity of traffic flow, a dynamic …

STCGAT: A spatio-temporal causal graph attention network for traffic flow prediction in intelligent transportation systems

W Zhao, S Zhang, B Zhou, B Wang - arXiv preprint arXiv:2203.10749, 2022 - arxiv.org
Air pollution and carbon emissions caused by modern transportation are closely related to
global climate change. With the help of next-generation information technology such as …

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 …