1 citations · 1 across the 1 of their papers we have counts for
4 papers
PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving
Simon Gerstenecker, Andreas Geiger, Katrin Renz
Most recent work in autonomous driving has prioritized benchmark performance and methodological innovation over in-depth analysis of model failures, biases, and shortcut learning.…
CaRL: Learning Scalable Planning Policies with Simple Rewards
Bernhard Jaeger, Daniel Dauner, Jens Beißwenger +3
We investigate reinforcement learning (RL) for privileged planning in autonomous driving. State-of-the-art approaches for this task are rule-based, but these methods do not scale t…
Centaur: Robust End-to-End Autonomous Driving with Test-Time Training
Chonghao Sima, Kashyap Chitta, Zhiding Yu +5
How can we rely on an end-to-end autonomous vehicle's complex decision-making system during deployment? One common solution is to have a ``fallback layer'' that checks the planned…
Hidden Biases of End-to-End Driving Datasets
Julian Zimmerlin, Jens Beißwenger, Bernhard Jaeger +2
End-to-end driving systems have made rapid progress, but have so far not been applied to the challenging new CARLA Leaderboard 2.0. Further, while there is a large body of literatu…