Search Results for author: Philip Schörner

Found 3 papers, 0 papers with code

KI-PMF: Knowledge Integrated Plausible Motion Forecasting

no code implementations18 Oct 2023 Abhishek Vivekanandan, Ahmed Abouelazm, Philip Schörner, J. Marius Zöllner

Accurately forecasting the motion of traffic actors is crucial for the deployment of autonomous vehicles at a large scale.

Autonomous Vehicles Motion Forecasting +1

Holistic Graph-based Motion Prediction

no code implementations31 Jan 2023 Daniel Grimm, Philip Schörner, Moritz Dreßler, J. -Marius Zöllner

Motion prediction for automated vehicles in complex environments is a difficult task that is to be mastered when automated vehicles are to be used in arbitrary situations.

motion prediction

Generalizing Decision Making for Automated Driving with an Invariant Environment Representation using Deep Reinforcement Learning

no code implementations12 Feb 2021 Karl Kurzer, Philip Schörner, Alexander Albers, Hauke Thomsen, Karam Daaboul, J. Marius Zöllner

Data driven approaches for decision making applied to automated driving require appropriate generalization strategies, to ensure applicability to the world's variability.

Decision Making Navigate

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