A Taxonomy for Architecting Safe Autonomous Unmanned Systems
Yixing Luo, Haiyan Zhao, Zhi Gang Jin · 2022
Autonomous Unmanned Systems (AUSs) emerge to replace human operators for better efficiency and effectiveness, especially in harsh and dangerous environments which frequently imply uncertainty. Safety has become one of the top concerns for AUS designs. To address AUS safety concerns systematically, we aim to establish a comprehensive taxonomy of AUS safety and provide a safety-by-design framework for architecting safer AUSs. We conduct a systematic literature review on 65 primary studies and analyze them from three perspectives: system and environment features, safety threats, and countermeasures. We adopt feature models to organize the survey results and establish a taxonomy for AUSs safety issues. Based on the taxonomy, we figure out a reference architecture that integrates three control loops dealing with the uncertainty of operating environments, external threats and system deviations, respectively. Our survey reveals that AUS safety is still a formative field and presents a taxonomy for AUSs safety issues and a safe-by-design framework for architecting safer AUSs.