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This article appeared originally in the Department of Civil and Environmental Engineering's 2018 alumni magazine, Civil Remarks. Find more stories at go.umd.edu/civilremarks

Experts at the Maryland Transportation Institute (MTI) have received $1.5 million from the Federal Highway Administration (FHWA) to chart the nation’s travel demand and develop products for predicting future changes. Funded through FHWA’s Exploratory Advanced Research Program, the three-year project will culminate in public domain origin-destination tables that shine a light on how travelers move between and within metropolitan areas.

As the name suggests, origin-destination tables—better known as OD tables—reveal how many trips travelers take between any origin and destination pair.

Transportation planners have long used these to understand travel demand. But MTI experts will propel the method to new heights by creating OD tables for trips between and within the nation’s more than 300 metropolitan statistical areas using comprehensive location data from mobile devices.

“This project will revolutionize the way we collect, analyze, and predict travel behavior and demand,”

MTI Director and Herbert Rabin Distinguished Professor Lei Zhang said. Zhang, along with Ph.D. student Sepehr Ghader and others, will also tap into 2017 location data provided by companies like AirSage, INRIX, and StreetLight Data to develop innovative methods to fill information gaps in traveler demographics, travel modes, trip purposes, and more.

The OD tables will serve as the foundation of a microsimulation model that officials could use to predict future national travel demand and determine how well a proposed project will meet that demand before investing in it.

Throughout the project, the MTI team will work closely with partners at the University of Maryland Center for Geospatial Information Science, the Maryland State Highway Administration, the Baltimore Metropolitan Council, and a number of data providers.



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State, university officials celebrate launch of newly formed, cross-discipline transportation institute
Tapping into the Largest Transportation Big Data Archive Is Easier than Ever

November 9, 2018


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