University of Michigan

An Application-Agnostic Investigation of Location-Based Services Data Quality: Using Synthetic Data and Empirical Benchmarking

Over the past decade, the widespread adoption and use of mobile services and devices have enabled the large‑scale, passive collection of human location data. The most widely available of these, termed location‑based services (LBS) data, are largely GPS enabled location “pings” collected from third party smartphone applications. These data have already proven to be useful […]

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Investigating Travel Survey Representativeness: Who’s Missing and What Can We Do?

The core source of data for transportation planning and forecasting comes from household travel surveys. Travel surveys are used to obtain insight into the behavioral decisions of travelers; for example: (1) trip purposes such as work or shopping; (2) means/mode of transport such as car, walk, bus, etc.; (3) travel time; and (4) time of

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Michigan Mobility Metrics (M3): An Outcome-Focused, Multi-Year Survey Deployment and Data Collection Effort

Transportation modes, technologies, and the broader context within which people travel have evolved rapidly over the last decade. Examples of such changes include the introduction of: new/emerging modes like ridesharing and micromobility, electric and automated vehicle technologies, information and communication devices; and the increase in remote and hybrid work due to COVID-19. It is critical

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Travel Behavior Data (TBD) Hub

In an era characterized by transformative shifts in demographics, lifestyles, work patterns, technological advances, societal values, and climate and environmental conditions, decision-makers are now confronted with ever-increasing, multifaceted uncertainties. The TBD National Center has launched a flagship initiative, called the TBD Hub, to provide transportation decision-makers information and deep insights about the state of the

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