3 papers
cs.CV2026
NARRATE: A Multimodal Real-World Australian Driving Dataset for Human-Centred Explanations in Automated Driving
Ashkan Yousefi Zadeh, Zishuo Zhu, Xiaomeng Li +5
Automated vehicles must explain their decisions in ways that passengers can understand, monitor, and trust. Existing language-annotated driving datasets are mostly observer-written…
cs.AI2026
X-Blocks: Linguistic Building Blocks of Natural Language Explanations for Automated Vehicles
Ashkan Y. Zadeh, Xiaomeng Li, Andry Rakotonirainy +3
Natural language explanations play a critical role in establishing trust and acceptance of automated vehicles (AVs), yet existing approaches lack systematic frameworks for analysin…
cs.HC2025
Small Talk, Big Impact? LLM-based Conversational Agents to Mitigate Passive Fatigue in Conditional Automated Driving
Lewis Cockram, Yueteng Yu, Jorge Pardo +6
Passive fatigue during conditional automated driving can compromise driver readiness and safety. This paper presents findings from a test-track study with 40 participants in a real…