Аңдатпа
The object of the study was a modular large-scale urban VR system designed for real-time standalone execution. The study addressed the absence of an engineering asset based on modular design and rule-based geometric reduction for developing large-scale urban virtual reality (VR) environments that preserve navigation-relevant realism under standalone real-time performance constraints. Existing study primarily focused on small-scale scenes or treated realism as a global aesthetic property without systematic resource allocation strategies for city-scale environments. To solve this problem, a rule-based geometric reduction asset grounded in selective realism was developed and experimentally validated. Architectural objects were classified by spatial and functional significance (Classes A-C), and interior accessibility levels were introduced to regulate geometric complexity. A modular urban prototype comprising more than thirty architectural assets was implemented on a unified metric grid. Geometric reduction decreased vertex count from 49,114 to 4,033 and polygon count from 89,840 to 5,615, representing more than a fifteenfold complexity reduction while preserving object hierarchy. Experimental validation (n = 20) demonstrated high perceived spatial clarity (5.9/7), low navigation error rate (1.3 errors), mean completion time of 4.8 ± 1.2 minutes, and 18% average route deviation. The framework proved applicable to standalone VR education scenarios under strict rendering constraints