Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems
A new diffusion-based framework balances high-fidelity human mobility synthesis with robust privacy preservation.
Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. However, due to privacy concerns, the availability of large-scale public trajectory data remains limited, posing challenges for dow...
ArXiv CS.LG
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By decomposing movement into coarse milestones and fine-grained segments, this model better simulates complex human mobility patterns that traditional methods miss. This breakthrough improves the reliability of synthetic urban data while simultaneously enhancing privacy protections by reducing re-identification risks.
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