Spatiotemporal Exogenous Variables Enhanced Model for Traffic Flow Prediction

Spatiotemporal Exogenous Variables Enhanced Model for Traffic Flow Prediction

Traffic flow prediction is a vital component of Intelligent Transportation Systems (ITS). However, it is extremely challenging to predict traffic flow accurately for a large-scale road network over multiple time horizons, due to the complex and dynamic spatiotemporal dependencies involved. To addres...

Full description

Bibliographic Details
Main Authors:	Chengxiang Dong, Xiaoliang Feng, Yongchao Wang, Xin Wei
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Series:	IEEE Access
Subjects:	Traffic flow prediction exogenous variables spatiotemporal dependencies graph attention networks transformer
Online Access:	https://ieeexplore.ieee.org/document/10239160/

Similar Items

GLSNN Network: A Multi-Scale Spatiotemporal Prediction Model for Urban Traffic Flow
by: Benhe Cai, et al.
Published: (2022-11-01)

FASTNN: A Deep Learning Approach for Traffic Flow Prediction Considering Spatiotemporal Features
by: Qianqian Zhou, et al.
Published: (2022-09-01)

Self-Supervised Spatiotemporal Masking Strategy-Based Models for Traffic Flow Forecasting
by: Gang Liu, et al.
Published: (2023-10-01)

Research on Multi-Port Ship Traffic Prediction Method Based on Spatiotemporal Graph Neural Networks
by: Yong Li, et al.
Published: (2023-07-01)

Gated Recurrent Unit Embedded with Dual Spatial Convolution for Long-Term Traffic Flow Prediction
by: Qingyong Zhang, et al.
Published: (2023-09-01)

Ship Traffic Flow Prediction in Wind Farms Water Area Based on Spatiotemporal Dependence
by: Tian Xu, et al.
Published: (2022-02-01)

Weather Interaction-Aware Spatio-Temporal Attention Networks for Urban Traffic Flow Prediction
by: Hua Zhong, et al.
Published: (2024-02-01)

Multi-time Scale Spatial-Temporal Graph Neural Network for Traffic Flow Prediction
by: WANG Ming, PENG Jian, HUANG Fei-hu
Published: (2022-08-01)

Attention-based spatio-temporal graph convolutional network considering external factors for multi-step traffic flow prediction
by: Jihua Ye, et al.
Published: (2022-06-01)

Multistep Coupled Graph Convolution With Temporal-Attention for Traffic Flow Prediction
by: Xiaohui Huang, et al.
Published: (2022-01-01)

Attention-Based Multiscale Spatiotemporal Network for Traffic Forecast with Fusion of External Factors
by: Jeba Nadarajan, et al.
Published: (2022-12-01)

Graph Neural Network for Traffic Flow Situation Prediction
by: JIANG Shan, DING Zhiming, XU Xinrun, YAN Jin
Published: (2021-06-01)

PMGCN: Progressive Multi-Graph Convolutional Network for Traffic Forecasting
by: Zhenxin Li, et al.
Published: (2023-06-01)

Spatiotemporal Graph Indicators for Air Traffic Complexity Analysis
by: Ralvi Isufaj, et al.
Published: (2021-11-01)

Dynamic Graph Convolution Network with Multi-head Attention for Traffic Flow Prediction
by: Hanyou DENG, et al.
Published: (2024-01-01)

Hybrid Graph Models for Traffic Prediction
by: Renyi Chen, et al.
Published: (2023-07-01)

Spatiotemporal Graph Convolutional Network for Multi-Scale Traffic Forecasting
by: Yi Wang, et al.
Published: (2022-02-01)

Advances in spatiotemporal graph neural network prediction research
by: Yi Wang
Published: (2023-12-01)

Time-Evolving Graph Convolutional Recurrent Network for Traffic Prediction
by: Weimin Mai, et al.
Published: (2022-03-01)

AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting
by: Jiawei Zhu, et al.
Published: (2021-01-01)

STHSGCN: Spatial-temporal heterogeneous and synchronous graph convolution network for traffic flow prediction
by: Xian Yu, et al.
Published: (2023-09-01)

Cross-Attention Fusion Based Spatial-Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction
by: Kun Yu, et al.
Published: (2021-12-01)

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting
by: Shifen Cheng, et al.
Published: (2018-06-01)

Spatio-Temporal Residual Graph Convolutional Network for Short-Term Traffic Flow Prediction
by: Qingyong Zhang, et al.
Published: (2023-01-01)

Short‐term traffic flow prediction based on AST‐MTL‐CNN‐GRU
by: Zijing Yang, et al.
Published: (2023-11-01)

MTESformer: Multi-Scale Temporal and Enhance Spatial Transformer for Traffic Flow Prediction
by: Xinhua Dong, et al.
Published: (2024-01-01)

Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
by: Zhang, Ying, et al.
Published: (2024)

Multi-Scale Residual Depthwise Separable Convolution for Metro Passenger Flow Prediction
by: Taoying Li, et al.
Published: (2023-10-01)

Prediction of High-Speed Traffic Flow around City Based on BO-XGBoost Model
by: Xin Lu, et al.
Published: (2023-07-01)

Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting
by: Dmitry Pavlyuk
Published: (2020-02-01)

Forecasting long range dependent time series with exogenous variable using ARFIMAX model
by: Krishna Pada Sarkar, et al.
Published: (2020-10-01)

A Spatiotemporal Graph Neural Network with Graph Adaptive and Attention Mechanisms for Traffic Flow Prediction
by: Yanqiang Huo, et al.
Published: (2024-01-01)

A Deep Learning Framework About Traffic Flow Forecasting for Urban Traffic Emission Monitoring System
by: Baozhen Yao, et al.
Published: (2022-01-01)

Lane-Level Traffic Flow Prediction with Heterogeneous Data and Dynamic Graphs
by: Junjie Zhou, et al.
Published: (2022-05-01)

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting
by: Jiandong Bai, et al.
Published: (2021-07-01)

Spatio-temporal information enhance graph convolutional networks: A deep learning framework for ride-hailing demand prediction
by: Zhenglong Tang, et al.
Published: (2024-01-01)

An attention-based deep learning model for citywide traffic flow forecasting
by: Tao Zhou, et al.
Published: (2022-12-01)

A General Traffic Flow Prediction Approach Based on Spatial-Temporal Graph Attention
by: Cong Tang, et al.
Published: (2020-01-01)

A multi-task deep learning model for short-term taxi demand forecasting considering spatiotemporal dependences
by: Huimin Luo, et al.
Published: (2021-02-01)

Local-Global Spatial-Temporal Graph Convolutional Network for Traffic Flow Forecasting
by: Xinlu Zong, et al.
Published: (2024-02-01)