VRU Basic Service: A V2X Comprehensive Analysis in a VRU Large-Scale Scenario

Vehicle-to-Everything (V2X) communication enables the active integration of Vulnerable Road Users (VRUs) into wireless networks, allowing them to share their position and movement dynamics. In the European V2X system, this transmission is achieved through the VRU Awareness Message (VAM), a dedicated message type designed to support VRU connectivity. The development of VAMs relies on both simulation environments and field tests. However, no realistic multi-modal large-scale scenarios have been implemented for such evaluations. To investigate the impact of VAMs in a realistic setting, this study explores the use of a genetic algorithm (GA) to generate and improve a VRU scenario, thereby enhancing its realism. The scenario was generated using real VRU counts to create a dataset, which was then divided into two subsets—one for data optimization and parameter tuning, and the other for validation. The application of GA led to a 56% improvement in scenario realism. Additionally, the VAM triggering mechanisms and clustering behavior are examined within the proposed scenario. The VAM analysis revealed that clusters are primarily generated at bus and train stations, where high VRU densities are observed. However, such densities are less common in other areas of the city, raising questions about the appropriate triggering parameter values for the VAM and cluster creation conditions.