  The autonomous vehicle (AV) is a safety-critical system relying on complex
sensors and algorithms. The AV may confront risk conditions if these sensors
and algorithms misunderstand the environment and situation, even though all
components are fault-free. The ISO 21448 defined the safety of the intended
functionality (SOTIF), aiming to enhance the AV's safety by specifying AV's
development and validation process. As required in the ISO 21448, the
triggering conditions, which may lead to the vehicle's functional
insufficiencies, should be analyzed and verified. However, there is not yet a
method to realize a comprehensive and systematic identification of triggering
conditions so far. This paper proposed an analysis framework of triggering
conditions for the perception system based on the propagation chain of events
model, which consists of triggering source, influenced perception stage, and
triggering effect. According to the analysis framework, ontologies of
triggering source and perception stage were constructed, and the relationships
between concepts in ontologies are defined. According to these ontologies,
triggering conditions can be generated comprehensively and systematically. The
proposed method was applied on an L3 autonomous vehicle, and 20 from 87
triggering conditions identified were tested in the field, among which eight
triggering conditions triggered risky behaviors of the vehicle.
