National Institute for Transportation and Communities

NITC researchers have tested a method of collecting transportation behavior data using a smartphone app, with promising results.

The process could save transit agencies “hundreds of thousands of dollars,” says lead researcher Christopher Bone, and give them access to comprehensive, real-time data about their ridership, all without compromising passengers’ privacy.

Christopher Bone, Marc Schlossberg, Ken Kato, Jacob Bartruff and Seth Kenbeek of the University of Oregon designed a custom mobile application, which allows passengers to volunteer information about their travel habits, and recruited passengers to use it in a test case.

Their report, “Crowdsourcing the Collection of Transportation Behavior Data,” was released this month.

Download it here.

Participants were asked to use the app for three weeks on Lane Transit District’s EmX bus line located in the Eugene-Springfield area in western Oregon. Researchers placed sensors on the buses and at stops to detect when someone using the app was boarding. When a user came within range of a sensor, they...

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...

A NITC research project from Portland State University introduces a method of cleaning up land use data, for use in improved transportation models.

Transportation and land use are closely interdependent. Considerable work is underway, in Oregon and elsewhere, to develop models that integrate the two.

Planners creating these models often spend the bulk of their time preparing data on the various land uses. Many times the data, gathered from diverse sources, is incomplete and requires the planner to find missing information to fill in the gaps.

In fields outside of transportation, there have been considerable advances in techniques to do this. Data-mining and machine-learning techniques have been developed, for example, to systematically detect fraud in credit data, reconcile medical records and clean up information on the web.

In the transportation modeling community, by contrast, most efforts to tackle the problem are tied to a specific model system and a chosen study area. Few have produced reusable tools for processing land use data.

Liming Wang, lead investigator of the project Continuous Data Integration for Land Use and Transportation Planning and Modeling, offers such reusable...

OTREC turned its education efforts on a decidedly younger crowd March 13: sixth graders. A class from Rochester, N.Y., visited Portland on a trip geared toward improving bicycling in their own community.

The students, from Genesee Community Charter School, visited the OTREC offices to learn about active transportation research methods. They took part in group exercises designed to get them thinking about the planning and engineering challenges of transportation systems set up to serve multiple transportation modes.

The highlight of the day came when the students took to Portland’s streets — OTREC’s living laboratory — to conduct research of their own. Armed with bicycle-counter tubes and infrared detectors, students counted cyclists and pedestrians passing on the Broadway cycle track on Portland State University’s campus.

Other students verified the technology with manual counters.

Students moved on to their next stop on a four-day tour of Portland with a better sense of what kind of data researchers collect and how they can use those data to inform policy. Given their experience — the students already have influenced their city on policy ranging from Erie Canal re-watering to an urban art corridor to skate parks — they stand a good chance of using Portland’s lessons to build a bike-friendly Rochester.