6 papers
Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction
Dominique Briechle, Raj Chanchad, Tobias Geger +5
Explicit software architecture models are essential artifacts for communicating, analyzing, and evolving complex software-intensive systems. In ROS~2-based robotic systems, however…
Geo-Data-Driven HD Map Generation Workflow with Integrated Reference-Free Constraint-Based Verification
Ruidi He, Vaibhav Tiwari, Mohanad Al-Ghobari +2
High-definition (HD) maps are core artifacts for automated driving systems, but their generation commonly relies on sensor-intensive mobile mapping campaigns, while quality assessm…
Connected Dependability Cage: Run-Time Function and Anomaly Monitoring for the Development and Operation of Safe Automated Vehicles
Iqra Aslam, Nour Habib, Abhishek Buragohain +4
The advancement of automated vehicles introduces complex safety challenges, particularly in dynamic and unpredictable environments where AI-enabled perception systems must operate…
LLM-Assisted Tool for Joint Generation of Formulas and Functions in Rule-Based Verification of Map Transformations
Ruidi He, Yu Zhang, Meng Zhang +1
High-definition map transformations are essential in autonomous driving systems, enabling interoperability across tools. Ensuring their semantic correctness is challenging, since e…
Towards Selection and Transition Between Behavior-Based Neural Networks for Automated Driving
Iqra Aslam, Igor Anpilogov, Andreas Rausch
Autonomous driving technology is progressing rapidly, largely due to complex End To End systems based on deep neural networks. While these systems are effective, their complexity c…
A Method for the Runtime Validation of AI-based Environment Perception in Automated Driving System
Iqra Aslam, Abhishek Buragohain, Daniel Bamal +3
Environment perception is a fundamental part of the dynamic driving task executed by Autonomous Driving Systems (ADS). Artificial Intelligence (AI)-based approaches have prevailed…