Research on road parametric modeling and dynamic lightweighting methods driven by BIM-GIS integration

Yan Cao, Xinyi Liu, Rui Huang, Menglan Zhu, Zhu Wang and Peng Xu

PLOS ONE, 2026, vol. 21, issue 1, 1-28

Abstract: Addressing the challenges of inflexibility and low modeling efficiency in the forward design of road building information modeling (BIM), as well as the performance bottlenecks within integrated BIM-GIS environments, this study proposes a novel integration-driven method for parametric modeling and dynamic lightweight processing of roads (PMDL). The proposed approach integrates terrain-adaptive algorithms with lightweight rendering techniques, thereby enabling rapid design iteration and dynamic optimization. Based on this method, a parametric system for 3D road model features is constructed according to the spatial topological relationships between the road and the terrain. Shape grammar is employed to drive the road pavement modeling process, ensuring both design flexibility and modeling efficiency. For complex terrain conditions, a threshold-triggered dynamic modeling mechanism is designed. Through terrain elevation analysis, the undulation of road sections is automatically identified. Algorithms are developed for continuous road pavement generation, Grid-based segmentation of the slopes, dynamic calculation of pier heights, and automatic tunnel generation, enabling the adaptive creation of roads, bridges, tunnels, and slopes. Finally, quadric error metrics (QEM) mesh simplification, level of detail (LOD), and view frustum culling are applied to optimize the loading efficiency and rendering performance of 3D models on the OpenSceneGraphEarth (OSGEarth) platform. This achieves a stable frame rate above 50 FPS for large-scale scenes, effectively resolving rendering lag issues in large-scale scenarios. Experiments show that compared to traditional oblique photography modeling (OPM) and differential elements method (DiEM), this method significantly improves modeling speed, accuracy, and data scheduling efficiency, providing efficient technical support for intelligent design, dynamic updating, and multi-scale visualization of digital twin roads.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0340062

DOI: 10.1371/journal.pone.0340062

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