Graph Convolutional Networks for Road Networks

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Abstrakt

The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important 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 GCN designed specifically for road networks. In particular, we pro- pose methods that substantially outperform state-of-the-art GCNs on two machine learning tasks in road networks. Furthermore, we show that state-of-the-art GCNs fail to effectively leverage road network structure on these tasks.
OriginalsprogEngelsk
TitelProceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
RedaktørerFarnoush Banaei-Kashani, Goce Trajcevski, Ralf Hartmut Guting, Lars Kulik, Shawn Newsam
Antal sider4
ForlagAssociation for Computing Machinery
Publikationsdato5 nov. 2019
Sider460-463
ISBN (Trykt)9781450369091
ISBN (Elektronisk)9781450369091
DOI
StatusUdgivet - 5 nov. 2019
Begivenhed27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - 350 W Mart Center Dr, Chicago, USA
Varighed: 5 nov. 20198 nov. 2019
https://sigspatial2019.sigspatial.org/

Konference

Konference27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Lokation350 W Mart Center Dr
LandUSA
ByChicago
Periode05/11/201908/11/2019
Internetadresse

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  • Publikation

    • 1 Citationer
    • 1 Tidsskriftartikel

    Relational Fusion Networks: Graph Convolutional Networks for Road Networks

    Skovgaard Jepsen, T., Jensen, C. S. & Nielsen, T. D., 14 aug. 2020, I : IEEE Transactions on Intelligent Transportation Systems. s. 1-12 12 s.

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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    Citationsformater

    Skovgaard Jepsen, T., Jensen, C. S., & Nielsen, T. D. (2019). Graph Convolutional Networks for Road Networks. I F. Banaei-Kashani, G. Trajcevski, R. H. Guting, L. Kulik, & S. Newsam (red.), Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (s. 460-463). Association for Computing Machinery. https://doi.org/10.1145/3347146.3359094