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An Ontology-based Method to Identify Triggering Conditions for Perception Insufficiency of Autonomous Vehicles

—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 com-prehensive 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.