Call for Papers: ITSC 2022 Special Session on "Graph Neural Network for Traffic Forecasting"

[Weiwei Jiang]

Dear Colleagues,

We would like to cordially invite you to submit a paper to our special session on "Graph Neural Network for Traffic Forecasting" for the 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022). Please find the description below:

Special session code: 6495a

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CALL FOR PAPERS

Special Session on Graph Neural Network for Traffic Forecasting

within the 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022)

https://www.ieee-itsc2022.org/

*AIM AND SCOPE*
Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have been extensively applied in traffic forecasting problems to model spatial and temporal dependencies. In recent years, to model the graph structures in transportation systems as well as contextual information, graph neural networks (GNNs) have been introduced and have achieved state-of-the-art performance in a series of traffic forecasting problems. In this special session, we aim to collect the studies that explore the application of graph neural networks for traffic forecasting problems.

*TOPICS*
- Novel graph neural networks, e.g. graph convolutional and graph attention networks, spatio-temporal graph neural networks
- GNNs for traffic forecasting problems, e.g. road traffic flow and speed forecasting, passenger flow forecasting in urban rail transit systems, and demand forecasting in ride-hailing platforms
- Open data and source resources for traffic forecasting problems

*SUBMISSION PROCEDURE*
Manuscripts submitted to this special session should be done through the paper submission website of the main conference: http://its.papercept.net/

Choose Special Session Paper, enter the code 6495a and follow the regular submission process.

Best regards,
Weiwei Jiang
Tsinghua University