15 citations · 25 across the 11 of their papers we have counts for
5 papers · 1 filter
Conditional Unscented Autoencoders for Trajectory Prediction
Faris Janjoš, Marcel Hallgarten, Anthony Knittel +3
The CVAE is one of the most widely-used models in trajectory prediction for AD. It captures the interplay between a driving context and its ground-truth future into a probabilistic…
The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review
Steffen Hagedorn, Marcel Hallgarten, Martin Stoll +1
Automated driving has the potential to revolutionize personal, public, and freight mobility. Beside accurately perceiving the environment, automated vehicles must plan a safe, comf…
Parting with Misconceptions about Learning-based Vehicle Motion Planning
Daniel Dauner, Marcel Hallgarten, Andreas Geiger +1
The release of nuPlan marks a new era in vehicle motion planning research, offering the first large-scale real-world dataset and evaluation schemes requiring both precise short-ter…
Stay on Track: A Frenet Wrapper to Overcome Off-road Trajectories in Vehicle Motion Prediction
Marcel Hallgarten, Ismail Kisa, Martin Stoll +1
Predicting the future motion of observed vehicles is a crucial enabler for safe autonomous driving. The field of motion prediction has seen large progress recently with state-of-th…
From Prediction to Planning With Goal Conditioned Lane Graph Traversals
Marcel Hallgarten, Martin Stoll, Andreas Zell
The field of motion prediction for automated driving has seen tremendous progress recently, bearing ever-more mighty neural network architectures. Leveraging these powerful models…