Last month, CTS debuted two videos about the many contributions U of M researchers have made—and are still making—in traffic operations and pavement design.
The videos are one of the ways CTS is marking 30 years of transportation innovation. Our goal is to show how research progresses over time—from curiosity to discovery to innovation. The videos also show how U of M research meets the practical needs of Minnesotans in the Twin Cities metro and throughout the state.
Freeways and highways aren’t the only urban roads with traffic congestion, even though traffic management strategies have been largely directed toward improving traffic ﬂows there. So, U of M researchers have taken to city streets to reduce congestion in an innovative—albeit roundabout—way.
“There’s been a lot of research focused on controlling congestion on major highways and freeways, but there’s relatively less when it comes to looking at controlling traffic on urban arterials,” says Ted Morris, a research engineer with the Department of Computer Science. “It’s a very different picture when you get into urban arterials and the traffic behaviors going on there, because of the dynamics of route choice, pedestrian interactions, and other factors.”
Morris is part of a research team that aims to create a framework for testing and evaluating new urban traffic sensing and control strategies for arterial networks. The goal is to balance safety and efficiency for all users—especially in places where new types of urban transportation facilities are planned in the next few years
A new report from the Accessibility Observatory estimates the accessibility to jobs by auto in the 50 largest (by population) metropolitan areas in the United States. The report also estimates the impact of traffic congestion on access to jobs in the same areas.
The report—Access Across America: Auto 2015—presents detailed accessibility and congestion impact values for each metropolitan area as well as block-level maps that illustrate the spatial patterns of accessibility within each area. It also includes a census tract-level map that shows accessibility patterns at a national scale. The report is part of the Access Across America study, which began in 2013.
Researchers at the U of M’s HumanFIRST Laboratory are helping to make it faster and easier for Minnesota law enforcement officers to log the data they collect at the scene of a crash.
Nichole Morris, principal researcher at the HumanFIRST Lab, and her team redesigned the electronic crash report interface used by Minnesota law enforcement officers to improve the accuracy, reliability, and meaningfulness of crash data. Although at first glance these data appear to serve simply drivers and insurance companies, the information is highly valued because it is used by state and federal agencies, as well as researchers, to analyze and evaluate crashes, trends, and potential countermeasures.
Giving people more options to bike or walk to their destinations has been a high priority for transportation planners in recent years. But as the number of pedestrians and bicyclists using the transportation system increases, so does the potential for serious—or even deadly—crashes involving these high-risk road users.
“To best prevent bicycle and pedestrian crashes, transportation planners need a better idea of how many people are using nonmotorized transportation and what their exposure to risk is,” says Greg Lindsey, a professor in the University of Minnesota’s Humphrey School of Public Affairs and researcher at the Roadway Safety Institute.
Tagged with: bicycling
, Center for Transportation Studies
, transportation research
, University of Minnesota
Posted in Bicycling
, Land use
, Public transit
, Traffic data
, Traffic operations
, Transportation research
, Travel Behavior
Imagine a world without traffic jams, car crashes, or highway pileups. A future where smartphones are no longer a distraction from safe driving, but rather a safety tool. A future where it’s easier for everyone to get where they need to be, whether they’re driving, busing, biking, or hoofing it.
This future may happen sooner than later, thanks to advancements from researchers in the U’s College of Science and Engineering (CSE). These researchers are helping to make our commutes smoother, our vehicles smarter, and our destinations more accessible.
Transportation agencies need travel behavior data to plan changes to their networks, systems, and policies. A new smartphone application developed by a U of M research team makes it easier and less costly to collect this important information and provides richer, more accurate data than traditional methods.
The Daynamica open-source app provides an efficient approach for collecting and processing data for driving, walking, biking or taking transit. It combines smartphone GPS sensing with statistical and machine-learning techniques to detect, identify, and summarize daily activity and travel episodes. The app then allows users to view and annotate information at their convenience.