TREC research addresses complex transportation problems by drawing on multiple disciplines, including engineering, planning, economics and design, from across the Portland State University campus. Use the search box at right to search for a specific project.
Research Highlights
Key Enhancements to the WFRC/MAG Four-Step Travel Demand Model
Reid Ewing Shima Hamidi
Conventional four-step travel demand modeling is overdue for a major update. The latest NITC report from the University of Utah offers planners better predictive accuracy through an improved model, allowing for much greater sensitivity to new variables that affect travel behavior. Specifically, it accounts for varying rates of vehicle ownership, intrazonal travel, and multimodal mode choices.
Used by nearly all metropolitan planning organizations (MPOs), state departments of transportation,…
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Green Waves, Machine Learning, and Predictive Analytics: Making Streets Better for People on Bikes
Stephen Fickas Marc Schlossberg
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…
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