SF-LIFE is a new large-scale simulated multi-modal trajectory dataset for the San Francisco Bay Area generated via agent-based simulation combined with GTFS transit and OSM network data.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Presents an end-to-end system using LLM agents to add behavioral anomalies to simulated trajectories, then applies map routing and noise to generate realistic annotated anomaly datasets for mobility research.
citing papers explorer
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SF-LIFE: A Large-Scale Simulated Movement Dataset for the San Francisco Bay Area
SF-LIFE is a new large-scale simulated multi-modal trajectory dataset for the San Francisco Bay Area generated via agent-based simulation combined with GTFS transit and OSM network data.
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Mobility Anomaly Generation using LLM-Driven Behavior with Kinematic Constraints
Presents an end-to-end system using LLM agents to add behavioral anomalies to simulated trajectories, then applies map routing and noise to generate realistic annotated anomaly datasets for mobility research.