National Institute for Transportation and Communities

In a big step forward for nonmotorized planning, a dashboard with bike data from the Washington, D.C. metro area is coming to BikePed Portal. Previously, a planner looking to see the latest biking numbers for the nation's capital would have to look at info from several jurisdictions, including Arlington County, the City of Alexandria, the District Department of Transportation, Fairfax County, Montgomery County, and the National Park Service, which manages counters on several trails and natural areas in the greater metro area.

Now, with funding from a National Park Service (NPS) Cooperative Ecosystem Studies Unit (CESU), a unique program that facilitates partnerships between federal and non-federal entities and research institutions, Virginia Tech and the University of North Carolina Highway Safety Research Center (HSRC) are teaming up with data specialists at Portland State University (PSU) to create a new dashboard that will allow users to see all the D.C. bike data together in one place.

Housed at PSU's Transportation Research and Education Center (TREC), BikePed Portal...

In recent years, shared electric scooters (e-scooters) have taken cities around the world by storm. But how are people using this new mode of transportation? Seeking to understand the potential impacts of e-scooters on land use, infrastructure and sustainability goals, researchers have some new interesting data to share on e-scooter users, exploring the interplay between demographics, behaviors and trip purposes.

Funded by the National Institute for Transportation and Communities (NITC) and led by Kristina Currans and Nicole Iroz-Elardo of the University of Arizona and Reid Ewing of the University of Utah, the study combines a user survey with on-the-ground observations to characterize the use and safety of e-scooters. The research team also included students Dong-ah Choi,...

While it’s generally accepted that dense, mixed-use development promotes active travel, researchers don’t have a consensus on exactly how, and to what degree, land use determines people’s travel patterns.

NITC’s latest report, Active Travel Behavior and Spatial-Temporal Land Use Mixing, provides some clarity on the topic.

NITC fellow Steven Gehrke focused his dissertation research on transportation-land use interaction, and sees land use mix as a multidimensional construct.

“We can refocus—away from increasing density—and think more about how we configure land uses,” Gehrke said.

According to Gehrke’s research, more density does not necessarily equal more walking. Rather, the complementarity, composition, and configuration of land use types is essential for cultivating walkability.

Gehrke, who graduates this spring with a Ph.D. in civil and environmental engineering from Portland State University, conducted three empirical studies under his dissertation grant. The first focused on improving measurements of land use mix, introducing a land use mix measurement of the composition and configuration of local land use types.

The second study looked at other smart growth principles, like employment concentration and pedestrian-...

A new NITC project has developed a robust pedestrian demand estimation tool, the first of its kind in the country.

• See the research here: Development of a Pedestrian Demand Estimation Tool

Using the tool, planners can predict pedestrian trips with spatial acuity.

The research was completed in partnership with Oregon Metro, and will allow Metro to allocate infrastructure based on pedestrian demand in the Portland, Oregon metropolitan area.

In a previous project completed last year as part of the same partnership, the lead investigator, Kelly Clifton, developed a way to collect data about the pedestrian environment on a small, neighborhood scale that made sense for walk trips. For more about how that works, click here to read our news coverage of that project. 

Following the initial project, the next step was to take that micro-level pedestrian data and use it to predict destination choice. For every walk trip generated by the model in the first project, this tool matches it to a likely destination based on traveler characteristics and environmental attributes.

Patrick Singleton, a graduate student researcher at Portland...