53 citations
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cs.RO2025
Comparison of Localization Algorithms between Reduced-Scale and Real-Sized Vehicles Using Visual and Inertial Sensors
Tobias Kern, Leon Tolksdorf, Christian Birkner
Physically reduced-scale vehicles are emerging to accelerate the development of advanced automated driving functions. In this paper, we investigate the effects of scaling on self-l…
cs.RO2025★ 1 cited
Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation
Abinav Kalyanasundaram, Karthikeyan Chandra Sekaran, Philipp Stauber +3
Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor syst…
cs.RO2025★ 6 cited
Hybrid Machine Learning Model with a Constrained Action Space for Trajectory Prediction
Alexander Fertig, Lakshman Balasubramanian, Michael Botsch
Trajectory prediction is crucial to advance autonomous driving, improving safety, and efficiency. Although end-to-end models based on deep learning have great potential, they often…