An Adaptive Ontology–LLM Framework for Simulation-Based Reenactment of Korean Traffic Accidents
Simulation-based testing is fundamental for validating automated driving systems (ADSs), and real-world traffic accident records provide realistic scenario data. However, converting such records into executable simulations requires addressing structural incompleteness, geographic bias in large language models (LLMs), a...