In order to make sure bicyclists' needs are considered when improving a transportation system, planners and engineers need to know how many people are biking, and where. 

Traditional bicycle counters can provide data for limited sections of the bike network, often these counters are installed at important locations like trails or bridges. While limited in location, they count everyone who bikes by. Meanwhile, GPS & mobile data cover the entire transportation network, but that data only represents those travelers who are using smartphones or GPS. Combining the traditional location-based data sources with this new, crowdsourced data could offer better accuracy than any could provide alone. 

"Knowing how many people are bicycling on a street is really important for a number of reasons. As just a few examples, bicycle volumes give you a way to understand safety data and determine crash rates. They provide insight into where and how bicycle trips are taking place, which can help plan for new or improved facilities," said Nathan McNeil of Portland State University.

Supported by a pooled fund grant administered by the National Institute for Transportation and Communities (NITC), Dr. Sirisha Kothuri of Portland State University led a research project aimed at fusing traditional and...

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Dr. Joey Iuliano of the University of Arizona, a 2020 NITC dissertation fellow who earned his Ph.D. in 2021, has published a journal article in the March 2022 issue of Cogent Social Sciences: Where and how Tucsonans ride and implications for cycling infrastructure

Drawing from cycling ethnographic work, Dr. Iuliano used video recordings of three groups of cyclists (commuter, recreational, and athletic) in Tucson, AZ, to contextualize their movements and interactions with the built environment, drivers, and other cyclists. Cycling can be utilitarian for commuters and a social, leisure, and athletic activity for recreational and athletic riders. Depending on their reason for riding, cyclists utilize infrastructure to suit their needs and protect themselves from drivers. Confidence levels also influence where and how people ride. For example:

  • Commuters rode defensively and sought out less-trafficked facilities.
  • Recreational riders rode solo on paths and in groups on open roads.
  • Athletic riders claimed space from drivers by riding in packs while being mindful of group safety.

Video ethnography helps improve the understanding of the different reasons for cycling and those experiences. With this information, planners can provide more accurate maps and overcome pushback from some cyclists by designing...

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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,...

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We're proud to announce the publication of a new NITC dissertation: "Pedal the Old Pueblo: A Naturalistic Study on Bicycling in Tucson, AZ," by Joey Iuliano of the University of Arizona, Tucson.

"There are many different reasons to ride a bike – commuting, recreational riding, and athletic pursuits are a few. This dissertation work highlights the need to understand how different types of cyclists interact with the built environment and their experiences with other road users. Utilizing video cameras helps fill in this gap by capturing their lived experiences throughout the course of a ride. Coupling this footage with larger datasets, such as annual bicycle counts or Strava, can show planners where there are issues with safety and infrastructure design, how many others may be experiencing those issues, and helps with targeted improvements," Iuliano said. 

City investments in bicycle infrastructure can improve residents' health and wellness, lower pollution, fight climate change, and reduce congestion. While transportation geography and planning have long focused on looking at how vehicles, goods, and services move across a region, there is a growing body of research focused on the movement of people through a city.

Iuliano's dissertation uses both the City of Tucson and Pima County, Arizona – a region of low-density development, traditionally focused on the car and now...

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Led by Dr. Stephen Fickas of the University of Oregon (UO),  transportation researchers are working to give bicyclists smoother rides by allowing them to communicate with traffic signals via a mobile app. 

The latest report to come out of this multi-project research effort introduces machine-learning algorithms to work with their mobile app FastTrack. Developed and tested in earlier phases of the project, the app allows cyclists to passively communicate with traffic signals along a busy bike corridor in Eugene, Oregon. Researchers hope to eventually make their app available in other cities.

"The overall goal is to give bicyclists a safer and more efficient use of a city’s signaled intersections. The current project attempts to use two deep-learning algorithms, LSTM and 1D CNN, to tackle time-series forecasting. The goal is to predict the next phase of an upcoming, actuated traffic signal given a history of its prior phases in time-series format. We're encouraged by the results," Fickas said.

Their latest work builds on two prior projects, also funded by the National Institute for Transportation a Communities: in which Fickas and his team successfully built and deployed a hardware and software product called ‘Bike Connect’ which allowed people on bikes to give hands-free advance...

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Rethinking Streets for Physical Distancing, the third in our "Rethinking Streets" book series, has been released. The book offers 25 case studies from a broad swath of U.S. cities with a handful of international examples of streets that were redesigned to better accommodate people during the COVID-19 pandemic. Rethinking Streets is a design guidebook series produced by NITC researchers at the University of Oregon, led by Marc Schlossberg. The three books are:

These full-color design guides have proven popular with planners and...

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A national non-motorized count data archive, BikePed Portal provides a centralized standard count database for public agencies, researchers, educators, and other curious members of the public to view and download bicycle and pedestrian count data. It includes automated and manual counts from across the country, and supports screenline and turning movement counts.

BikePed Portal was established in 2015 by Transportation Research and Education Center (TREC) researchers at Portland State University through a pooled fund grant administered by the National Institute for Transportation and Communities (NITC). Other project partners include the Federal Highway Administration, Oregon Department of Transportation, Metro, Lane Council of Governments, Central Lane MPO, Bend MPO, Mid Willamette Valley Council of Governments, Rogue Valley Council of Governments, City of Boulder, City of Austin, Cycle Oregon, and Oregon Community Foundation.

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Street icons for bicycle and pedestrian
Photo by Cait McCusker
Nathan McNeil, Portland State University; Kristin Tufte, Portland State University

In the past decade bike and pedestrian count programs have sprung up all over the United States, gathering data to evaluate biking and walking infrastructure. However, these modes have not been studied with the quantitative rigor applied to motor vehicle travel. A research project funded by the National Institute for Transportation and Communities (NITC), led by Nathan McNeil of Portland State University (PSU), offers a method for monitoring the quality of this bike-ped count data.

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