Projects per year
The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important intelligent transportation applications. Graph Convolutional Networks (GCNs) are neural networks that are capable of leveraging the structure of a network. However, many implicit assumptions of GCNs do not apply to road networks. We introduce the Relational Fusion Network (RFN), a novel type of Graph Convolutional Network (GCN) designed specifically for road networks. In particular, we propose methods that outperform state-of-the-art GCN architectures by up to 21-40% on two machine learning tasks in road networks. Furthermore, we show that state-of-the-art GCNs may fail to effectively leverage road network structure and may not generalize well to other road networks.
|Journal||IEEE Transactions on Intelligent Transportation Systems|
|Number of pages||12|
|Publication status||Published - Jan 2022|
Bibliographical noteCenter for Data-Intensive Cyber-Physical Systems (DiCyPS) Project
10.13039/100008398-Obel Family Foundation and the Villum Foundation
- graph convolutional networks (GCNs)
- graph representation learning
- machine learning
- road network
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- 1 Finished
01/01/2015 → 31/12/2020
Skovgaard Jepsen, T., 2021, Aalborg Universitetsforlag. 169 p. (Ph.d.-serien for Det Tekniske Fakultet for IT og Design, Aalborg Universitet).
Research output: Book/Report › Ph.D. thesis › ResearchOpen AccessFile34 Downloads (Pure)
Barth, F., Funke, S., Skovgaard Jepsen, T. & Proissl, C., 3 Nov 2020, BIGSPATIAL '20: Proceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data. Chandola, V., Vatsavai, R. R. & Shashidharan, A. (eds.). Association for Computing Machinery, p. 1-10 10 p. 6
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-reviewFile
Skovgaard Jepsen, T., Jensen, C. S. & Nielsen, T. D., 5 Nov 2019, Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Banaei-Kashani, F., Trajcevski, G., Guting, R. H., Kulik, L. & Newsam, S. (eds.). Association for Computing Machinery, p. 460-463 4 p.
Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-reviewOpen AccessFile