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New dataset NARRATE aims to improve AI driving explanations

Researchers have introduced NARRATE, a new multimodal dataset designed to improve human-centered explanations for automated driving systems. The dataset includes 2,050 annotated events from 35 drivers, featuring synchronized visual, localization, motion, and LiDAR data, alongside free-text explanations from the drivers themselves. NARRATE aims to enable the development of more domain-aware explanation models for autonomous vehicles by providing action labels, scenario-context labels, and situational awareness annotations. AI

IMPACT This dataset could lead to more understandable and trustworthy AI driving systems by focusing on human-centered explanations.

RANK_REASON The cluster contains a research paper detailing a new dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset NARRATE aims to improve AI driving explanations

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ashkan Yousefi Zadeh, Zishuo Zhu, Xiaomeng Li, Andry Rakotonirainy, Sebastien Glaser, Ronald Schroeter, Patricia Delhomme, Zahra Mehraban ·

    NARRATE: A Multimodal Real-World Australian Driving Dataset for Human-Centred Explanations in Automated Driving

    arXiv:2608.14767v1 Announce Type: cross Abstract: Automated vehicles must explain their decisions in ways that passengers can understand, monitor, and trust. Existing language-annotated driving datasets are mostly observer-written, post-hoc, simulation-based, or generated from se…