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

Term Start:

June 1, 2026

Term End:

May 31, 2027

Budget:

$148,409

Keywords:

Data Fusion, Travel Behavior, Travel Demand

Thrust Area(s):

Data Collection Mechanisms, Data Modeling and Analytic Tools

University Lead:

University of Michigan

Researcher(s):

Atiyya Shaw

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 travel behavior and demand research. The proposed work will develop an accessible taxonomy and application framework organized by stage of analysis – survey design, data preparation, analysis and modeling, validation, and calibration – and by the specific limitation being addressed: insufficient sample size, lack of population representativeness, unobserved key variables, and measurement error. By linking data limitations to appropriate integration strategies and transportation applications, this work will help move the field beyond isolated, ad hoc uses of data fusion toward a more systematic and transferable practice. The expected outcome is practical guidance that supports more credible, representative, and policy-relevant travel behavior and demand analysis in an increasingly complex data environment.

Project scope

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