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
Designing for Dignity while Driving: Interaction Needs of Blind and Low-Vision Passengers in Fully Automated Vehicles
Zhengtao Ma, Rafael Gomez, Togtokhtur Batbold +3
Fully automated vehicles (FAVs) hold promise for enhancing the mobility of blind and low-vision (BLV) individuals. To understand the situated interaction needs of BLV passengers, w…