  According to the World Health Organization, the involvement of Vulnerable
Road Users (VRUs) in traffic accidents remains a significant concern, with VRUs
accounting for over half of traffic fatalities. The increase of automation and
connectivity levels of vehicles has still an uncertain impact on VRU safety. By
deploying the Collective Perception Service (CPS), vehicles can include
information about VRUs in Vehicle-to-Everything (V2X) messages, thus raising
the general perception of the environment. Although an increased awareness is
considered positive, one could argue that the awareness ratio, the metric used
to measure perception, is only implicitly connected to the VRUs' safety. This
paper introduces a tailored metric, the Risk Factor (RF), to measure the risk
level for the interactions between Connected Automated Vehicles (CAVs) and
VRUs. By evaluating the RF, we assess the impact of V2X communication on VRU
risk mitigation. Our results show that high V2X penetration rates can reduce
mean risk, quantified by our proposed metric, by up to 44%. Although the median
risk value shows a significant decrease, suggesting a reduction in overall
risk, the distribution of risk values reveals that CPS's mitigation
effectiveness is overestimated, which is indicated by the divergence between RF
and awareness ratio. Additionally, by analyzing a real-world traffic dataset,
we pinpoint high-risk locations within a scenario, identifying areas near
intersections and behind parked cars as especially dangerous. Our methodology
can be ported and applied to other scenarios in order to identify high-risk
areas. We value the proposed RF as an insightful metric for quantifying VRU
safety in a highly automated and connected environment.
