As the advancing autonomy of vehicles requires increasing assistance from the surrounding infrastructure, it becomes clear that the potential for cyberattacks necessitates a sophisticated implementation of resilience, capable of detecting and responding to both internal and external threats. Therefore, threat analysis and risk assessment, including careful modelling of resilience, are essential to prepare against cybersecurity risks. In this context, we extend our method of an automatic discovery of cost-ranked cyberattack scenarios by monitoring/fallback mechanisms. We then demonstrate that this extension allows an analysis of a realistic resilient model of cybersecurity aspects of a level 2 autonomous connected vehicle