A fusion safety and security analysis framework for intelligent and connected vehicles

面向智能互联车辆的融合安全分析框架

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Abstract

Driven by advancements in emerging technologies and data-driven innovations, the global automotive industry is focusing on intelligent and connected vehicles (ICVs), which involve complex electronic systems and vast data interactions. Safety concerns have expanded beyond traditional safety measures to include functional safety, safety of the intended functionality (SOTIF), and cybersecurity. Despite their interconnected nature, current methods often address these domains separately, risking incomplete safety assessments. This paper introduces a fusion safety analysis method that evaluates the three domains collectively. By identifying safety attributes and mapping unsafe behaviors to hazardous scenarios, it quantitatively assesses integrated safety risks. An illustrative case study on adaptive cruise control (ACC) highlights the method's effectiveness, stressing the importance of addressing multi-dimensional safety issues to enhance ICVs safety.

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