  Recent reports from the World Health Organization highlight that Vulnerable
Road Users (VRUs) have been involved in over half of the road fatalities in
recent years, with occlusion risk - a scenario where VRUs are hidden from
drivers' view by obstacles like parked vehicles - being a critical contributing
factor. To address this, we present a novel algorithm that quantifies occlusion
risk based on the dynamics of both vehicles and VRUs. This algorithm has
undergone testing and evaluation using a real-world dataset from German
intersections. Additionally, we introduce the concept of Maximum Tracking Loss
(MTL), which measures the longest consecutive duration a VRU remains untracked
by any vehicle in a given scenario. Our study extends to examining the role of
the Collective Perception Service (CPS) in VRU safety. CPS enhances safety by
enabling vehicles to share sensor information, thereby potentially reducing
occlusion risks. Our analysis reveals that a 25% market penetration of
CPS-equipped vehicles can substantially diminish occlusion risks and
significantly curtail MTL. These findings demonstrate how various scenarios
pose different levels of risk to VRUs and how the deployment of Collective
Perception can markedly improve their safety. Furthermore, they underline the
efficacy of our proposed metrics to capture occlusion risk as a safety factor.
