Ensuring the safety of vulnerable road users (VRUs), including pedestrians, cyclists, electric scooter riders, and motorcyclists, remains a major challenge for advanced driver assistance systems (ADAS) and connected and automated vehicles (CAV) technologies. Real-world VRU tests are expensive and sometimes cannot capture or repeat rare and hazardous events. In this paper, we present a lightweight, configurable simulation framework that follows European New Car Assessment Program (Euro NCAP) VRU testing protocols. A rule-based finite-state machine (FSM) is developed as a motion planner to provide vehicle automation during the VRU interaction. We also integrate ego-vehicle perception and idealized Vehicle-to-Everything (V2X) awareness to demonstrate safety margins in different scenarios. This work provides an extensible platform for rapid and repeatable VRU safety validation, paving the way for broader case-study deployment in diverse, user-defined settings, which will be essential for building a more VRU-friendly and sustainable intelligent transportation system.
@article{arxiv.2510.19097,
title = {A Configurable Simulation Framework for Safety Assessment of Vulnerable Road Users},
author = {Zhitong He and Yaobin Chen and Brian King and Lingxi Li},
journal= {arXiv preprint arXiv:2510.19097},
year = {2025}
}
Comments
This work has been accepted by the 2025 International Conference on Cyber-physical Social Intelligence (CPSI 2025)