National Institute for Transportation and Communities

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...

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...

• Download the Final Report (PDF)
• Download the Project Brief (PDF)

What if your bicycle could warn you that a car is coming from a side street you can't see? Or let you know that your front tire is getting a little low, or that you're approaching a pothole that wasn't there yesterday? A NITC research project led by John MacArthur of Portland State University explores how connected vehicle (CV) technologies could encourage an increase in bicycling. As CV technology moves forward in the rest of the transportation system—with buses and connected streetcars requesting early green lights from the traffic signals, and cars chatting with each other...

Automobile traffic congestion in urban areas comes with significant economic and social costs for everyone. According to the 2015 Urban Mobility Report, the total additional cost of congestion was $160 billion. As more people move to metropolitan areas, the problems only intensify. The latest NITC report offers a new approach to urban traffic signal control based on network consensus control theory which is computationally efficient, responsive to local congestion, and at the same time has the potential for congestion management at the network level.

Traffic signals represent a significant bottleneck. As...