Research on 3D Visualization Design of Intelligent Transportation SandTable Empowered by Time Dimension

Abstract

As a pivotal carrier bridging traffic theory and engineering practice, the rationality of design and completeness of data representation for traffic sand tables directly underpin the accuracy of scene restoration and the reliability of experimental outcomes. To address the inherent limitations of traditional intelligent traffic sand tables—including the "2D planarization and spatiotemporal information fragmentation" of trajectory data, as well as the lack of standardized design workflows and insufficient virtual-physical mapping adaptability in physical sand tables—this study centers on the core design innovation of "integrating the time dimension into 3D modeling". Guided by the systematic, practical, and visual thinking of industrial design, an "x-y-t" spatiotemporal three-dimensional coordinate system is constructed to enable the design and construction of a high-precision physical sand table. The research achieves spatiotemporal dynamic visualization of trajectory data through deep integration of the time axis and spatial axes. Adopting a full-lifecycle approach encompassing demand analysis, design, implementation, verification, and optimization, it plans the sand table’s structural layout, equipment integration, human-computer interaction, and functional adaptation. Perception units such as V2X communication, millimeter-wave radar, and UWB positioning are integrated to establish a precise mapping relationship between digital models and the physical sand table. Experimental validation demonstrates that this design enhances the efficiency of spatiotemporal correlation recognition for trajectory data by 42%, with a digital-physical trajectory matching accuracy of 1.93 mm and a time synchronization error of ≤22 ms. It thus establishes a novel design paradigm for intelligent traffic sand tables characterized by "spatiotemporal integrated expression - high-precision physical design - precise virtual-physical mapping", offering innovative insights and practical solutions for the application of industrial design in the intelligent transportation domain.