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By interpreting a traffic scene as a graph of interacting vehicles, we gain a flexible abstract representation which allows us to apply Graph Neural Network (GNN) models for traffic prediction.
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“Pitfalls of Graph Neural Network Evaluation” arXiv: 1811.05868
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Thomas. Kipf and Max Welling · 2016
Cited alongside, same era.
“Factor Graph Scene Distributions for Automotive Safety Analysis”
T.. Wheeler and M.. Kochenderfer · 2016
Cited alongside, same era.
“Designing a far-reaching view for highway traffic scenarios with 5G-based intelligent infrastructure”, 2017, pp. 8
Gereon Hinz et al · 2017
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Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski and Stephan Günnemann · 2018
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“The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems”
Robert Krajewski, Julian Bock, Laurent Kloeker and Lutz Eckstein · 2018
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“SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels”
Matthias Fey, Jan Lenssen, Frank Weichert and Heinrich Müller · 2018
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