Graph neural network for traffic forecasting: the research progress
Traffic forecasting has been regarded as the basis for many intelligent transportation system (ITS) applications, including but not limited to trip planning, road traffic control, and vehicle routing. Various forecasting methods have been proposed in the literature, including statistical models, sha...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/169720 |
| _version_ | 1811697662077960192 |
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| author | Jiang, Weiwei Luo, Jiayun He, Miao Gu, Weixi |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Jiang, Weiwei Luo, Jiayun He, Miao Gu, Weixi |
| author_sort | Jiang, Weiwei |
| collection | NTU |
| description | Traffic forecasting has been regarded as the basis for many intelligent transportation system (ITS) applications, including but not limited to trip planning, road traffic control, and vehicle routing. Various forecasting methods have been proposed in the literature, including statistical models, shallow machine learning models, and deep learning models. Recently, graph neural networks (GNNs) have emerged as state-of-the-art traffic forecasting solutions because they are well suited for traffic systems with graph structures. This survey aims to introduce the research progress on graph neural networks for traffic forecasting and the research trends observed from the most recent studies. Furthermore, this survey summarizes the latest open-source datasets and code resources for sharing with the research community. Finally, research challenges and opportunities are proposed to inspire follow-up research. |
| first_indexed | 2024-10-01T07:58:49Z |
| format | Journal Article |
| id | ntu-10356/169720 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:58:49Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1697202023-08-04T15:36:12Z Graph neural network for traffic forecasting: the research progress Jiang, Weiwei Luo, Jiayun He, Miao Gu, Weixi School of Computer Science and Engineering Engineering::Computer science and engineering Traffic Forecasting Graph Neural Network Traffic forecasting has been regarded as the basis for many intelligent transportation system (ITS) applications, including but not limited to trip planning, road traffic control, and vehicle routing. Various forecasting methods have been proposed in the literature, including statistical models, shallow machine learning models, and deep learning models. Recently, graph neural networks (GNNs) have emerged as state-of-the-art traffic forecasting solutions because they are well suited for traffic systems with graph structures. This survey aims to introduce the research progress on graph neural networks for traffic forecasting and the research trends observed from the most recent studies. Furthermore, this survey summarizes the latest open-source datasets and code resources for sharing with the research community. Finally, research challenges and opportunities are proposed to inspire follow-up research. Published version This research was supported by the Fundamental Research Funds for the Central Universities. 2023-08-01T05:13:33Z 2023-08-01T05:13:33Z 2023 Journal Article Jiang, W., Luo, J., He, M. & Gu, W. (2023). Graph neural network for traffic forecasting: the research progress. ISPRS International Journal of Geo-Information, 12(3), 100-. https://dx.doi.org/10.3390/ijgi12030100 2220-9964 https://hdl.handle.net/10356/169720 10.3390/ijgi12030100 2-s2.0-85151355102 3 12 100 en ISPRS International Journal of Geo-Information © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
| spellingShingle | Engineering::Computer science and engineering Traffic Forecasting Graph Neural Network Jiang, Weiwei Luo, Jiayun He, Miao Gu, Weixi Graph neural network for traffic forecasting: the research progress |
| title | Graph neural network for traffic forecasting: the research progress |
| title_full | Graph neural network for traffic forecasting: the research progress |
| title_fullStr | Graph neural network for traffic forecasting: the research progress |
| title_full_unstemmed | Graph neural network for traffic forecasting: the research progress |
| title_short | Graph neural network for traffic forecasting: the research progress |
| title_sort | graph neural network for traffic forecasting the research progress |
| topic | Engineering::Computer science and engineering Traffic Forecasting Graph Neural Network |
| url | https://hdl.handle.net/10356/169720 |
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