Driving out risk: A taxonomy of factors influencing perceived safety in automated vehicles and the role of knowledge-based variation

Despite ongoing technological advancements, public acceptance of automated vehicles (AVs) remains limited, with perceived safety (PSAV) emerging as a pivotal determinant of trust and adoption. While prior research has identified factors such as cybersecurity, legal accountability, and functional performance as influential, these elements are often examined in isolation and without a unifying framework. Furthermore, the role of individuals' Knowledge Levels of AVs (KLAV) in shaping the salience of safety concerns remains underexplored. This study addresses these gaps through a qualitative investigation involving 66 interviews with members of the public and AV experts in the United Kingdom. We develop an empirically grounded taxonomy of PSAV comprising thirteen factors, organized into three overarching categories: Technological Safety, Psychological Safety, and Social Safety. Our findings suggest that perceptions of safety are not uniform but vary with participants’ KLAV, which is associated with differences in how safety concerns are interpreted and prioritized. The study advances theoretical understanding by reconceptualizing PSAV as a multidimensional and knowledge-sensitive construct. Practically, the taxonomy and KLAV-based insights offer actionable guidance for AV research, public engagement, and anticipatory governance, supporting more inclusive and socially responsive pathways for AV deployment. • Develops a new taxonomy of perceived safety in automated vehicles (AVs). • Identifies 13 key factors grouped under technological, psychological, and social safety. • Shows how public safety concerns differ by knowledge levels of AVs (KLAV). • Reveals that PSAV is a multidimensional and knowledge-sensitive phenomenon. • Provides practical insights for AV policy, design, and anticipatory governance.