A risk model and analysis method for the psychological safety of human and autonomous vehicles interaction
Yandika Sirgabsou, Benjamin Hardin, Fran\c{c}ois Leblanc, Efi Raili, Pericle Salvini, David Jackson, Marina Jirotka, and Lars Kunze

TL;DR
This paper develops a comprehensive framework for assessing psychological safety in autonomous vehicles, emphasizing trust and perceived risk, and introduces a risk model and analysis method to improve user acceptance and safety.
Contribution
It proposes a novel definition, a risk assessment model, and an adapted system-theoretic analysis method specifically for psychological safety in AVs.
Findings
Introduced PsySIL classification for AV psychological risks
Developed a risk model for identifying psychological hazards
Applied the framework to a family scenario demonstrating its utility
Abstract
The rapid advancement of artificial intelligence and autonomous driving technologies has significantly propelled the development of autonomous vehicles (AVs). However, psychological barriers continue to impede widespread AV adoption, despite technological progress. This paper addresses the critical yet often overlooked aspect of psychological safety in AV design and operation. While traditional safety standards focus primarily on physical safety, this paper emphasizes the psychological implications that arise from human interactions with autonomous vehicles, highlighting the importance of trust and perceived risk as significant factors influencing user acceptance. The paper makes a methodological proposal, a framework for addressing AVs psychological safety consisting of three key contributions. First, it introduces a definition of psychological safety in AVs context. Secondly, it…
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Taxonomy
TopicsHuman-Automation Interaction and Safety · Technology and Human Factors in Education and Health
