Intelligent Transportation Systems (ITS) need traffic data to run smoothly. At intersections, where there is the greatest potential for conflicts between road users, being able to reliably and intelligently monitor the different modes of traffic is crucial.

The Federal Highway Administration (FHWA) estimates that more than 50 percent of the combined total of fatal and injury crashes occur at or near intersections. For pedestrians the intersection is a particularly dangerous place: the City of Portland, Oregon identified that two-thirds of all crashes involving a pedestrian happen at intersections. And when darkness comes earlier in fall and winter, crashes increase dramatically. So knowing what's going on in low-visibility conditions is essential for mobility and safety of all road users.

Some agencies use cameras to monitor traffic modes, but cameras are limited in rainy, dark or foggy conditions. Some cities use radar instead of cameras, which works better in low-visibility but typically can't provide as rich a picture of what's going on. Conventional radar gives movement and position data for all...

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How can we use a variety of data-driven speed management strategies to make transportation safer and more efficient for all modes–whether you’re driving, walking or taking transit?

The project was led by Yao Jan Wu, director of the Smart Transportation Lab at the University of Arizona. Co-investigators were Xianfeng Terry Yang of the University of Utah, who researches traffic operations and modeling along with connected automated vehicles, and Sirisha Kothuri of Portland State University, whose research has focused on improving signal timing to better serve pedestrians. Join them on Sept 15, 2021 for a free webinar to learn more.

"We want to improve mobility for all users, be it pedestrians, vehicle drivers or transit riders, and there are different strategies to do this. How do we harness data to drive us to these strategies?" Kothuri said.

Funded by the National Institute for Transportation and Communities (NITC), this multi-university collaboration addressed the question from three angles:

  • Wu and his students in Arizona looked at the impact of speed management strategies on conventional roadways...
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A new NITC report offers a multimodal framework for transportation impact analysis – a welcome tool for professionals in many cities seeking more detailed data about non-drivers.

Improving Trip Generation Methods for Livable Communities, a research project headed by Kelly Clifton of Portland State University and Nico Larco of the University of Oregon, is the latest effort in an ongoing collaboration to create more open sourced, widely available data about non-motorized road users.

Over the last decades, cities have become more invested in fostering the conditions to support walking, biking and public transit.

The land development process presents a unique challenge.

Prior to a zoning change or new development, someone has to determine what its impact on the transportation system will be, and whether upgrades will be necessary to accommodate travelers to the new destination. Trip generation is the first step in the conventional transportation forecasting process.

Current trip generation methods used by engineers across the country tend to focus on motorized modes.

Without reliable trip generation rates for anyone but drivers, the transportation impact is difficult to predict. Certain land uses will draw far more walkers,...

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A study showing surprisingly high numbers of pedestrians using a congested suburban intersection draws national attention as its researchers present their findings at the annual meeting of the Transportation Research Board Jan. 11-15 in Washington, D.C. The number of pedestrians was recorded, not with a specialized counting machine, but using the technology that was already in place at the intersection.

Knowing how many travelers use a transportation system is important for a number of reasons. Engineers and planners need to be able to estimate travel demand, and to do so they typically count the vehicles. Annual average daily traffic (AADT) counts have been collected for decades in the United States. 

In recent years the demand has increased for non-motorized counts. For a...

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NITC researchers have created a design manual to aid traffic engineers, transportation planners, elected officials, businesses and community stakeholders in re-envisioning their streets.
 
Traditionally, road design in the U.S. has been based on the simple principle of moving as many cars as possible.
 
The ...
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OTREC at Portland State University welcomed Eva Heinen of the University of Groningen, The Netherlands, for a special seminar June 18. Around 40 people attended the presentation, held at the Intelligent Transportation Systems Laboratory and titled “Cycling in the Netherlands and Multi-Modality.”

Eva Heinen is assistant professor of infrastructure planning and mobility at the Department of Spatial Planning and Environment, Faculty of Spatial Sciences, University of Groningen. She earned a Ph.D. from Delft University of Technology in 2011 focusing on bicycle commuting.

Many people in Groningen and The Netherlands as a whole combine transit and bicycling for trips. A typical configuration involves cycling from home to a train station and then renting another bicycle to reach the final destination, Heinen said.

Few people take bicycles on transit, Heinen said, and buses don’t offer bike racks or other accommodations. Folding bikes, whose compact size allows for portability, are one exception, Heinen said. Electric-assist bikes are also popular, particularly with older people.

Heinen has published many papers on cycling in international and national journals and has a large international network in cycling. She spent three months at the University of California in Davis as a visiting scholar. She is a member of the editorial board of Rooilijn, a Dutch journal for science and policy in spatial planning; a member of the Bicycle Committee; co-chair of the...

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PRESENTATION ARCHIVE

OVERVIEW

Intelligent transportation systems (ITS) change our communities by improving the safety and convenience of people’s daily mobility. The system relies on multimodal traffic monitoring, that needs to provide reliable, efficient and detailed traffic information for traffic safety and planning. How to reliably and intelligently monitor intersection traffic with multimodal information is one of the most critical topics in intelligent transportation research.

In multimodal traffic monitoring, we gather traffic statistics for distinct transportation modes, such as pedestrians, cars and bicycles, in order to analyze and improve people’s daily mobility in terms of safety and convenience.

In this study, we use a high-resolution millimeter-wave (mmWave) radar sensor to obtain a relatively richer radar point cloud representation for a traffic monitoring scenario. Based...

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