Urban traffic digital twin system development in unity.

Area of Science:

• Computer Science
• Urban Planning
• Simulation Modeling

Background:

• Urban traffic digital twin systems face challenges in data fusion, computational efficiency, and interactive decision-making.
• Existing systems struggle with large-scale real-time simulations and intuitive dynamic interaction.

Purpose of the Study:

• To develop a novel Unity-based digital twin system addressing key challenges in urban traffic simulation.
• To achieve high-fidelity multi-source data fusion, overcome computational bottlenecks, and enable intuitive dynamic interaction for decision-making.

Main Methods:

• A three-layer architecture integrating Building Information Modeling (BIM) and Geographic Information Systems (GIS) for 3D model generation.
• Data Acquisition Layer synchronizing traffic and weather APIs for real-time environmental simulation.
• Optimized 3-Degrees of Freedom (3-DoF) vehicle dynamics model with Graphics Processing Unit (GPU)-accelerated collision detection and adaptive Level of Detail (LOD).

Main Results:

• Sub-meter accuracy 3D models (RMSE ≤ 0.15m) generated via BIM/GIS fusion.
• 1,500-vehicle concurrent simulation at 60 Frames Per Second (FPS) using adaptive LOD.
• Reduced Central Processing Unit (CPU)/GPU utilization by 47%/48% and trajectory error < 0.23m (9.5%) compared to nonlinear models.

Conclusions:

• The developed digital twin system effectively addresses urban traffic simulation challenges.
• It provides a robust platform for smart traffic management, autonomous driving testing, and policy pre-evaluation.
• The system demonstrates significant improvements in efficiency and accuracy for real-time traffic modeling.