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20242026
most citedRAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model

11 citations · 11 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.HC2026

A revised framework for the assessment of psychological safety in autonomous vehicles

Yandika Sirgabsou, Benjamin Hardin, François Leblanc +5

Despite recent technological progress in the development of autonomous vehicles (AVs), their societal acceptability remains a subject of debate as recent research findings point to…

cs.HC2026

Engineering Psychological Safety in Autonomous Vehicles: A Systems-Theoretic Framework for Psychological Safety in Autonomous Vehicles and its Validation in Real-World Scenarios

Yandika Sirgabsou, Benjamin Hardin, François Leblanc +5

Despite rapid technological advances, the societal acceptability of autonomous vehicles (AVs) remains limited by psychological barriers that extend beyond traditional concerns of p…

cs.HC2026

What Can Eye Gaze Teach Us About Real-World Cycling? Insights From the Oxford RobotCycle Project

Benjamin Hardin, Efimia Panagiotaki, Daniele De Martini +1

Although much is known about the physical danger of cycling situations, less is understood about the perceived danger of cycling. Furthermore, perception of danger may be filtered…

cs.HC2026

Sociotechnical Challenges of Machine Learning in Healthcare and Social Welfare

Tyler Reinmund, Lars Kunze, Marina Jirotka

Sociotechnical challenges of machine learning in healthcare and social welfare are mismatches between how a machine learning tool functions and the structure of care practices. Whi…

cs.HC2025

A risk model and analysis method for the psychological safety of human and autonomous vehicles interaction

Yandika Sirgabsou, Benjamin Hardin, François Leblanc +5

The rapid advancement of artificial intelligence and autonomous driving technologies has significantly propelled the development of autonomous vehicles (AVs). However, psychologica…

cs.HC2024

A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers

Daniel Omeiza, Raunak Bhattacharyya, Marina Jirotka +2

Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (suc…