9 papers
Inference-Time Attention Steering for Vision-Language-Action Driving Models
Darshan Nagendra Prasad, Lars Ullrich, Knut Graichen
Vision-language-action (VLA) driving models couple a reasoning stage with a diffusion-based trajectory decoder, but do not give a direct way to redirect attention toward safety-cri…
Robust Meta-Learning of Vehicle Yaw Rate Dynamics via Conditional Neural Processes
Lars Ullrich, Andreas Völz, Knut Graichen
Trajectory planners of autonomous vehicles usually rely on physical models to predict the vehicle behavior. However, despite their suitability, physical models have some shortcomin…
Sampling for Model Predictive Trajectory Planning in Autonomous Driving using Normalizing Flows
Georg Rabenstein, Lars Ullrich, Knut Graichen
Alongside optimization-based planners, sampling-based approaches are often used in trajectory planning for autonomous driving due to their simplicity. Model predictive path integra…
Toward Fully Autonomous Driving: AI, Challenges, Opportunities, and Needs
Lars Ullrich, Michael Buchholz, Klaus Dietmayer +1
Automated driving (AD) is promising, but the transition to fully autonomous driving is, among other things, subject to the real, ever-changing open world and the resulting challeng…
A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differences
Lars Ullrich, Michael Buchholz, Jonathan Petit +2
Efficient scalability of automated driving (AD) is key to reducing costs, enhancing safety, conserving resources, and maximizing impact. However, research focuses on specific vehic…
A New Perspective On AI Safety Through Control Theory Methodologies
Lars Ullrich, Walter Zimmer, Ross Greer +3
While artificial intelligence (AI) is advancing rapidly and mastering increasingly complex problems with astonishing performance, the safety assurance of such systems is a major co…