206 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Duisburg-EssenDE3 papers
- Helmholtz-Zentrum HereonDE2 papers
- Baden-Wuerttemberg Cooperative State UniversityDE1 paper
- Entwicklungszentrum für Schiffstechnik und TransportsystemeDE1 paper
- Leibniz Institute for Baltic Sea Research WarnemündeDE1 paper
- Shanghai Jiao Tong UniversityCN1 paper
- Universität HamburgDE1 paper
- University of GenevaCH1 paper
- University of StuttgartDE1 paper
3 papers · 1 filter
Towards Explainable Deep Learning for Ship Trajectory Prediction in Inland Waterways
Tom Legel, Dirk Söffker, Roland Schätzle +1
Accurate predictions of ship trajectories in crowded environments are essential to ensure safety in inland waterways traffic. Recent advances in deep learning promise increased acc…
Improved context-sensitive transformer model for inland vessel trajectory prediction
Kathrin Donandt, Karim Böttger, Dirk Söffker
Physics-related and model-based vessel trajectory prediction is highly accurate but requires specific knowledge of the vessel under consideration which is not always practical. Mac…
Incorporating Navigation Context into Inland Vessel Trajectory Prediction: A Gaussian Mixture Model and Transformer Approach
Kathrin Donandt, Dirk Söffker
Using data sources beyond the Automatic Identification System to represent the context a vessel is navigating in and consequently improve situation awareness is still rare in machi…