Graph neural network for traffic forecasting: A survey

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

(2021) Jiandong Bai et al.   ISPRS International Journal of Geo-Information

Graph-based deep learning for communication networks: A survey

(2021) Weiwei Jiang   COMPUTER COMMUNICATIONS

Multistep Flow Prediction on Car-Sharing Systems: A Multi-Graph Convolutional Neural Network with Attention Mechanism

(2020) Hongming Zhu et al.   INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING

A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data

(2020) Toon Bogaerts et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Global Spatial-Temporal Graph Convolutional Network for Urban Traffic Speed Prediction

(2020) Liang Ge et al.   Applied Sciences-Basel

A Performance Modeling and Analysis of a Novel Vehicular Traffic Flow Prediction System Using a Hybrid Machine Learning-Based Model

(2020) Azzedine Boukerche et al.   Ad Hoc Networks

Multi-Graph Convolutional Network for Short-Term Passenger Flow Forecasting in Urban Rail Transit

(2020) Jinlei Zhang et al.   IET Intelligent Transport Systems

Short-term prediction of traffic flow under incident conditions using graph convolutional recurrent neural network and traffic simulation

(2020) Shota Fukuda et al.   IET Intelligent Transport Systems

Exploiting Multiple Correlations Among Urban Regions for Crowd Flow Prediction

(2020) Qiang Zhou et al.   JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY

Forecasting road traffic speeds by considering area-wide spatio-temporal dependencies based on a graph convolutional neural network (GCN)

(2020) Byeonghyeop Yu et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Dynamic Origin–Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter

(2020) Xi Xiong et al.   TRANSPORTATION RESEARCH RECORD

Urban flow prediction from spatiotemporal data using machine learning: A survey

(2020) Peng Xie et al.   Information Fusion

Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting

(2020) Hao Peng et al.   INFORMATION SCIENCES

Multitask Learning and GCN-Based Taxi Demand Prediction for a Traffic Road Network

(2020) Zhe Chen et al.   SENSORS

Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting

(2020) Tanwi Mallick et al.   TRANSPORTATION RESEARCH RECORD

Traffic Prediction Using Multifaceted Techniques: A Survey

(2020) Shiju George et al.   WIRELESS PERSONAL COMMUNICATIONS

An urban commuters’ OD hybrid prediction method based on big GPS data

(2020) Yongdong Wang et al.   CHAOS

Urban Traffic Flow Forecast Based on FastGCRNN

(2020) Ya Zhang et al.   JOURNAL OF ADVANCED TRANSPORTATION

A Novel Traffic Flow Forecasting Method Based on RNN-GCN and BRB

(2020) Hailong Zhu et al.   JOURNAL OF ADVANCED TRANSPORTATION

Short-term traffic speed forecasting based on graph attention temporal convolutional networks

(2020) Ge Guo et al.   NEUROCOMPUTING

Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems

(2020) Azzedine Boukerche et al.   Computer Networks

Feature selection and extraction in spatiotemporal traffic forecasting: a systematic literature review

(2019) Dmitry Pavlyuk   European Transport Research Review

A graph deep learning method for short‐term traffic forecasting on large road networks

(2019) Yang Zhang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks

(2019) Han et al.   ISPRS International Journal of Geo-Information

Graph convolutional network approach applied to predict hourly bike-sharing demands considering spatial, temporal, and global effects

(2019) Tae San Kim et al.   PLoS One

Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies

(2019) Zhengchao Zhang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Incorporating Graph Attention and Recurrent Architectures for City-Wide Taxi Demand Prediction

(2019) Ying Xu et al.   ISPRS International Journal of Geo-Information

Road traffic state prediction based on a graph embedding recurrent neural network under the SCATS

(2019) Dongwei Xu et al.   CHAOS

Real-Time Traffic Speed Estimation With Graph Convolutional Generative Autoencoder

(2019) James Jian Qiao Yu et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

A deep learning approach to real-time parking occupancy prediction in transportation networks incorporating multiple spatio-temporal data sources

(2019) Shuguan Yang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

A novel residual graph convolution deep learning model for short-term network-based traffic forecasting

(2019) Yang Zhang et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

A hybrid deep learning based traffic flow prediction method and its understanding

(2018) Yuankai Wu et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Predicting station-level hourly demand in a large-scale bike-sharing network: A graph convolutional neural network approach

(2018) Lei Lin et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Geospatial data to images: A deep-learning framework for traffic forecasting

(2018) Weiwei Jiang et al.   TSINGHUA SCIENCE AND TECHNOLOGY

The Graph Neural Network Model

(2008) F. Scarselli et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS