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Discovering How People Come and Go: Inferring Queue Dynamics and System-Level Time Series Data

Description: This technology is a two-stage data-driven methodology that analyzes queue dynamics by leveraging time series data to infer arrival and service patterns. It utilizes a non-parametric screening stage followed by parametric estimation, enabling accurate analysis without needing detailed event-level data. Validated through simulations and...

Published: 12/16/2025 | Inventor(s): Emily Zhu, Hafila Max Morais

Keywords(s): Data Analytics, Queue Theory

Category(s): Data/AI, Transportation