4 papers · 1 filter
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 BeiÃwenger +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…
DriveLM: Driving with Graph Visual Question Answering
Chonghao Sima, Katrin Renz, Kashyap Chitta +7
We study how vision-language models (VLMs) trained on web-scale data can be integrated into end-to-end driving systems to boost generalization and enable interactivity with human u…