  Advancements in autonomous vehicle (AV) technologies necessitate precise
estimation of perceived risk to enhance user comfort, acceptance and trust.
This paper introduces a novel AV-Occupant Risk (AVOR) model designed for
perceived risk estimation during AV cut-in scenarios. An empirical study is
conducted with 18 participants with realistic cut-in scenarios. Two factors
were investigated: scenario risk and scene population. 76% of subjective risk
responses indicate an increase in perceived risk at cut-in initiation. The
existing perceived risk model did not capture this critical phenomenon. Our
AVOR model demonstrated a significant improvement in estimating perceived risk
during the early stages of cut-ins, especially for the high-risk scenario,
enhancing modelling accuracy by up to 54%. The concept of the AVOR model can
quantify perceived risk in other diverse driving contexts characterized by
dynamic uncertainties, enhancing the reliability and human-centred focus of AV
systems.
