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

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...

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OTREC research from Portland State University has developed a new method of travel demand modeling for pedestrian trips.

Transportation professionals use travel demand modeling to forecast how many people will be using a given portion of the transportation infrastructure. This is typically done using a four-step process, the first step of which relies upon a basic unit known as a transportation analysis zone, or TAZ.

A TAZ is a relatively coarse unit of space that can vary in size depending on planners’ needs; typically it encompasses somewhere around 3,000 residents.

Planners started using TAZs in the 1950s, on mainframe computers with limited capabilities, for guidance in making highway investment decisions. As transportation modeling practice has evolved, computers are capable of processing more data and models are being increasingly relied upon to answer more complex questions. 

Despite growing investment in infrastructure that supports active forms of travel, existing modeling tools often poorly represent the nuances of the pedestrian environment. The project’s principal investigator, Kelly Clifton of Portland State University, explores ways to improve upon the modeling tools currently in existence.

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OTREC research associate John MacArthur, in partnership with Drive Oregon, has been awarded a grant from Metro.

The grant is part of a $2.1 million effort by Metro to improve air quality and community health.

With the Metro grant, Drive Oregon and MacArthur plan to conduct a study of consumer perception and use of electric bicycles, pedal-bikes that provide extra propulsion from a rechargeable battery.

The idea is to see whether having the use of an e-bike will persuade non-bicycle-commuters to use a bike for the “first and last mile” of their daily commute; for example, to get from their workplace to the nearest MAX light rail station.

The e-bikes provided in the study will be foldable for convenient carrying onto the train. Ultimately, the partners of this study hope to increase the percentage of people who commute by bicycle and light rail, thus contributing to overall community health by reducing automobile emissions.

30 e-bikes will be loaned to 180 employees of Kaiser Permanente, at three designated work locations. Each participant will have the free use of an e-bike for one month, bookended by surveys about their expectations and perceptions of the experience.

MacArthur is conducting some overlapping research into e-bike use in a...

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When policymakers look to meet cycling goals by investing in new bicycle routes, they have little research to help them determine whether cyclists will actually use them. As a result, bicycle facilities aren’t considered equally with motor vehicle infrastructure.

That’s changing, thanks in part to OTREC research. An OTREC-funded study, the first to gather large-scale data that reveal cyclists’ actual route preference, is being published in a scientific journal (Transportation Research Part A). The findings have already been incorporated into the regional travel demand model used to make transportation investment decisions across the Portland region.

In the study, Portland State University researchers Joseph Broach, Jennifer Dill and John Gliebe (Gliebe is now with RSG Inc.) outfitted cyclists with GPS units to record which routes they chose and model the choices to reveal preferences. Previous studies have relied on stated preference surveys or less reliable methods of determining cyclists’ actual routes. The data gathering was supported by a grant from the Robert Wood Johnson Foundation through its national...

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In transportation funding decisions, you don’t count until you’re counted. That fact can lead to cyclists and pedestrians, often overlooked in traffic counts, getting less than their share of transportation money. OTREC hosted a conference Sept. 15 to address that problem.

“Without the data, you have an incomplete picture of how the (transportation) system is being used,” said OTREC researcher Chris Monsere, the conference organizer. “And it’s easier to make the case for resources if you know how the system is being used.”

The conference, called the “Bike and Pedestrian Program Information Exchange & Technology Transfer Summit Meeting,” brought together officials from local and state transportation agencies and consultants to share features of the best counting programs and technology. The forum helped bridge a gap between people who count motor vehicles and those who count bicycle and pedestrian traffic.  

“We wanted to raise a little awareness of both sides of the equation,” Monsere said. “There are things both can learn from the other.” <All presentations available  for download at the end of this article>

Nonmotorized counting programs often get large numbers of motivated people involved quickly and have a strong network for distributing results of counts. Motorized counts tend to be more systematic and uniform.

The motorized traffic counts have a jump on their non-motorized counterparts, Monsere said. That’s largely a result of...

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