no code implementations • 27 Apr 2021 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
An empirical study finds that an instance of UniTE can improve the accuracies of travel speed distribution and travel time estimation by $40-64\%$ and $3-23\%$, respectively, compared to using function fitting or aggregation alone
no code implementations • 23 Oct 2020 • Florian Barth, Stefan Funke, Tobias Skovgaard Jepsen, Claudius Proissl
We present analysis techniques for large trajectory data sets that aim to provide a semantic understanding of trajectories reaching beyond them being point sequences in time and space.
1 code implementation • 16 Jun 2020 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important intelligent transportation applications.
no code implementations • 14 Nov 2019 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
This is problematic for analysis tasks that rely on such information for machine learning.
1 code implementation • 30 Aug 2019 • Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
In addition, we provide experimental evidence of the short-comings of state-of-the-art GCNs in the context of road networks: unlike our method, they cannot effectively leverage the road network structure for road segment classification and fail to outperform a regular multi-layer perceptron.