Development of a Scenario-Guided, VR-Ready Ambulance Model for EMT Training Using Reality Capture Methods

Abstract

Emergency Medical Services (EMS) personnel require exceptional spatial awareness and rapid decision-making within the confined environment of an ambulance. While Virtual Reality (VR) offers a safe alternative to traditional training, the lack of high-fidelity, regionally accurate, and VR-optimized 3D ambulance models limits its application. This study presents a scenario-driven methodology for developing a VR-ready 3D ambulance environment prototype tailored for Emergency Medical Technician (EMT) training. Utilizing reality-capture techniques, terrestrial laser scanning was performed to accurately document the interior of a standard Hungarian ambulance simulator. The resulting point cloud underwent systematic processing, manual retopology, PBR shading, and the implementation of a custom dual-rigging animation system to optimize complex mechanical movements—such as stretcher operations—for standalone VR platforms. The workflow successfully reduced the vertex count to 25,373 while maintaining millimeter-level spatial fidelity. Technical evaluation confirmed that geometrical, functional, and material objectives were fulfilled, whereas pedagogical implementation remains incomplete. Structural accuracy and animation readiness were verified through preliminary inspection within Blender’s VR viewport inspector. However, interactive game-engine integration remains future work, and educational effectiveness has not yet been tested with EMT learners. Overall, this workflow delivers a 3D asset foundation that establishes the necessary technical basis for subsequent software implementation and clinical evaluation.