Search Results for author:
Found 8 papers, 1 papers with code
Exploring Large Language Models as a Source of Common-Sense Knowledge for Robots
This paper shows that the technique used for knowledge extraction can be applied to populate a minimalist ontology, showcasing the potential of LLMs in synergy with formal knowledge representation.
Introducing Risk Shadowing For Decisive and Comfortable Behavior Planning
In this paper, we develop risk shadowing, a situation understanding method that allows us to go beyond single interactions by analyzing group interactions between three agents.
A Glimpse in ChatGPT Capabilities and its impact for AI research
Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Tesla, and Apple (GAFA) investing heavily in their development.
Continuous Risk Measures for Driving Support
In this paper, we compare three different model-based risk measures by evaluating their stengths and weaknesses qualitatively and testing them quantitatively on a set of real longitudinal and intersection scenarios.
Intersection Warning System for Occlusion Risks using Relational Local Dynamic Maps
Here, we concentrate on intersection scenarios that are difficult to access visually.
Probabilistic Uncertainty-Aware Risk Spot Detector for Naturalistic Driving
Risk assessment is a central element for the development and validation of Autonomous Vehicles (AV).
Optimization of Velocity Ramps with Survival Analysis for Intersection Merge-Ins
We consider the problem of correct motion planning for T-intersection merge-ins of arbitrary geometry and vehicle density.
Importance Filtering with Risk Models for Complex Driving Situations
Based on the results, we can further derive a novel filter architecture with multiple filter steps, for which risk models are recommended for each step, to further improve the robustness.
