FusionSis: Analysis and Evaluation Framework for Fusion Safety State of Connected and Automated Vehicles Under Cyber Attacks

As connected and autonomous vehicles (CAVs) become more integrated into complex networks and systems, which introduce both safety and security concerns. To address these challenges, it is crucial to develop a fusion safety approach that combines cybersecurity, functional safety, and the safety of the intended functionality. One of the key difficulties in this approach is the diversity of cyber attacks and their potential impact on CAVs. However, evaluating and analyzing the fusion safety in practical environments remains challenging. To address this, we present a simulation framework designed to assess CAV resilience against cyber attacks while maintaining safety operation. The framework can simulates vehicle’s status both in physical and cyber field. A diverse cyber attacks with various driving scenarios are supported. Based on framework’s current capability, we propose eight fusion safety evaluation metrics to measure CAV performance under attack conditions. These metrics encompass aspects of functional safety, data security and driving comfortableness. Three demonstration scenarios show the effectiveness of the proposed framework in assessing the fusion safety state of CAVs, contributing to the development of more secure and resilient fusion safety applications.