Impact of connected and autonomous vehicles on road network resilience in Belgium

The advent of Connected and Automated Vehicles (CAVs) has ushered in substantial changes in the transportation sector, particularly impacting the resilience of road networks. CAVs can exchange real-time information about road conditions, allowing them to bypass congestion and optimise their routes, thereby enhancing network resilience through dynamic rerouting. Additionally, these vehicles significantly affect road capacity, further bolstering the overall resilience of the network. As a result, it is essential to assess the impact of CAVs on road network resilience comprehensively. However, to the best of the authors' knowledge, there is a notable gap in research that thoroughly evaluates the resilience of large-scale road networks, taking into account all dimensions of resilience, such as redundancy, robustness, and recovery speed. This paper aims to fill this gap by assessing the influence of CAVs on the resilience of a large-scale road network in Belgium. Utilising a simulation-based approach, the study quantifies the network's resilience triangle, addressing all facets of network resilience. The findings reveal that the integration of CAVs can markedly improve network resilience under various scenarios, with improvements ranging from 4.4% at a 10% penetration rate to 59.9% at full penetration. These insights are valuable for researchers and policymakers focused on the implementation of autonomous vehicles.