The emergence of Connected and Automated Vehicles (CAVs) has brought about significant transformations in the transportation industry, leading to noteworthy effects on various aspects, including the resilience of road networks. CAVs have the ability to receive and transmit real-time information about road conditions, enabling them to avoid congestion caused by disruptions and optimize their routes to enhance the network's resilience through rerouting. Moreover, these vehicles also have a considerable impact on road capacity, which contributes to strengthening the overall resilience of the network. Consequently, it is crucial to evaluate the influence of CAVs on the resilience of road networks. However, to the best knowledge of the authors, there is currently a lack of studies that comprehensively assess the resilience of large-scale road networks, considering all dimensions of resilience, such as redundancy, robustness, and recovery speed. Therefore, this paper aims to evaluate the impact of CAVs on the resilience of a large-scale road network in Belgium. The study contributes to the existing literature by employing a simulation-based method to quantify the resilience triangle of the network, encompassing all dimensions of network resilience. The findings of this research can provide valuable insights to researchers and policymakers involved in the deployment of autonomous vehicles.