Data Fusion

Integrating Transportation Data to Address Representation and Measurement Limitations in Travel Behavior and Demand Analysis

Expanding transportation data availability is creating new opportunities for a richer, potentially more representative, and broader data landscape to support the measurement and modeling of evolving travel behaviors and outcomes. This project addresses the need for clearer guidance on when, where, and how multiple data sources can be integrated to overcome common data limitations in

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Towards Building-Level Modeling: Human-Driven Agentic Workflows for Multi-Source Data Synthesis

Travel demand modeling is limited by the aggregation problem: data are often synthesized at census-tract or traffic-zone scales that obscure building-level mobility patterns. This project develops a human-directed agentic workflow in which a transportation planner orchestrates specialized artificial intelligence agents that discover, evaluate, and integrate open geospatial data from sources such as OpenStreetMap, building footprint

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