Travel time reliability – or the consistency and dependability of travel times from day to day, and at different times of day – is a key metric that significantly affects people’s travel behavior. Since businesses rely heavily on transportation systems, an unreliable transportation network can also impact the economic competitiveness of urban areas. As such, reliable travel times are important for transportation agencies to promote economic stability within a community. Having accurate methods to evaluate reliability is important for both transportation practitioners and researchers.

A new report from Portland State University offers an improved method for determining the confidence interval of travel time reliability metrics. Researchers Avinash Unnikrishnan, Subhash Kochar and Miguel Figliozzi of PSU’s Maseeh College of Engineering and Computer Science used a highway corridor in Portland, Oregon as a case study to evaluate their method, and found that it compared favorably with other methods of evaluating the confidence interval of travel time reliability metrics.

"Traffic engineers can apply this method to come up with a range of estimates for the unknown true travel time reliability metric. The travel time reliability metrics calculated by traffic engineers and transportation planners will have variability due to factors such as road...

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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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Are e-scooters just the first sign of a shared-mobility revolution? If they are, then researchers at the University of Arizona intend to make sure that the emerging transportation system has functional models on par with other modes of transportation. In 2018, approximately 100 U.S. cities had already launched shared e-scooter programs, accounting for 38.5 million trips. However, the models to manage e-scooter sharing are only recently being developed. In a project funded by the National Institute for Transportation and Communities (NITC) and led by Dr. Jianqiang Cheng, the research team set out to develop data-driven, decision-making models for shared-mobility system design and operation in Tucson, Arizona.

"The decision making process for e-scooter companies is complex. One of the first questions is where to locate the scooters – In the transportation network, where do e-scooters need to be placed to meet demand? The second question is how to distribute them. It gets more complicated when you introduce different electric charging methods, so that some scooters are being collected by paid contractors and others are being charged by customers, through incentives," Cheng said.

As the researchers see it, the main benefits of shared mobility are threefold:

  1. ...
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Led by Xiaoyue Cathy Liu of the University of Utah (UU) and funded by the National Institute for Transportation and Communities, researchers have created a web-based modeling tool (see GitHub repository built for the Utah Transit Authority) that enables U.S. transit providers to explore the impacts of changing over their systems to electric buses*. The researchers ran the model for TriMet in Portland, OR as well, with TriMet results and analysis presented in the final report (PDF).

"The interactive visualization platform lets users explore various electric bus deployment budget scenarios, so that transit agencies can plan the most cost-effective way to transition their fleet from diesel to electric buses – while prioritizing disadvantaged populations," Liu said.

The research team, at University of Utah, Portland State University (PSU), and University of California, Riverside, set out to answer three questions: 

  1. What costs and benefits are associated...
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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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Cyclist stands next to the Hawthorne Bridge Bicycle Counter

Authored by Tammy Lee, Transportation Data Manager, Portland State University

For a deeper dive into bicycle volume data, watch the May 8 seminar with Tammy Lee and Kristin Tufte: Creating And Using A Publicly Available Multimodal Transportation Data Archive. Also, check out her earlier blog post on motor vehicle traffic volumes.

The weather these past few weeks has been beautiful: sunny, not too hot, not too cold, cherry trees blossoming… the ideal biking weather marred by a less than ideal pandemic.

Are social distancing measures affecting bike trips in Portland, OR? Maybe. Personally? Yes.

First, let’s get a few things out of the way before we provide summary observations:

  • Analyzing bike data is not as “easy” as evaluating vehicle traffic data: the infrastructure for monitoring bike (and pedestrian) data isn’t anywhere close to how vehicle traffic is monitored. There just aren’t many bicycle count detectors. So if one detector stops working then what little data that was available in the first place became that much littler.

  • ...
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a visualization of trips entering and exiting Salt Lake City
Nikola Markovic, University of Utah

The University of Utah has a new data visualization service to offer to state DOTs and other agencies. Using Small Starts funding from the National Institute for Transportation and Communities (NITC), researcher Nikola Markovic and his team have developed a suite of visual analysis tools to demonstrate how GPS trajectory data can help accurately model and analyze mobility trends. These data are typically purchased from...

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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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A screenshot from the STAT tool shows a map with embedded Tweets by location
Xiaoyue (Cathy) Liu, University of Utah; Ran Wei, University of California, Riverside; Aaron Golub and Liming Wang, Portland State University

With today's profusion of open data sources and real-time feeds, transit agencies have an unparalleled opportunity to leverage large amounts of data to improve transit service. Thanks to NITC researchers,...

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