A Prototypical Expert-Driven Approach Towards Capability-Based Monitoring of Automated Driving Systems
arxiv(2024)
摘要
Supervising the safe operation of automated vehicles is a key requirement in
order to unleash their full potential in future transportation systems. In
particular, previous publications have argued that SAE Level 4 vehicles should
be aware of their capabilities at runtime to make appropriate behavioral
decisions. In this paper, we present a framework that enables the
implementation of an online capability monitor. We derive a graphical system
model that captures the relationships between the quality of system elements
across different architectural views. In an expert-driven approach, we
parameterize Bayesian Networks based on this structure using Fuzzy Logic. Using
the online monitor, we infer the quality of the system's capabilities based on
technical measurements acquired at runtime. Our approach is demonstrated in the
context of the UNICAR.agil research project in an urban example scenario.
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