5 papers
SanDRA: Safe Large-Language-Model-Based Decision Making for Automated Vehicles Using Reachability Analysis
Yuanfei Lin, Sebastian Illing, Matthias Althoff
Large language models (LLMs) have been widely applied to knowledge-driven decision-making for automated vehicles due to their strong generalization and reasoning capabilities. Howe…
Lexicographic Minimum-Violation Motion Planning using Signal Temporal Logic
Patrick Halder, Lothar Kiltz, Hannes Homburger +2
Motion planning for autonomous vehicles often requires satisfying multiple conditionally conflicting specifications. In situations where not all specifications can be met simultane…
Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees
Jakob Thumm, Marian Frei, Tianle Ni +2
We propose a framework for vision-based human pose estimation and motion prediction that gives conformal prediction guarantees for certifiably safe human-robot collaboration. Our f…
Results of the 2024 CommonRoad Motion Planning Competition for Autonomous Vehicles
Yanliang Huang, Xia Yan, Peiran Yin +5
Over the past decade, a wide range of motion planning approaches for autonomous vehicles has been developed to handle increasingly complex traffic scenarios. However, these approac…
Traffic-Rule-Compliant Trajectory Repair via Satisfiability Modulo Theories and Reachability Analysis
Yuanfei Lin, Zekun Xing, Xuyuan Han +1
Complying with traffic rules is challenging for automated vehicles, as numerous rules need to be considered simultaneously. If a planned trajectory violates traffic rules, it is co…