Category Archives: Traffic and Safety

Highway Death Toll Messages May Cause More Crashes

This article was originally published in Catalyst, May 2022.

Displaying the highway death toll on message boards is a common awareness campaign, but new research from the University of Toronto and University of Minnesota indicates this tactic may actually lead to more crashes.

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COVID-19 Travel Reductions: Lessons for Relieving Traffic Congestion

As the COVID-19 pandemic restrictions in 2020 kept people at home, reduced travel and, therefore, traffic congestion were to be expected. But how much of an impact did the restrictions have on traffic congestion? After analyzing changes in traffic levels due to the COVID-19 pandemic travel restrictions, researchers identified how incremental changes in vehicle miles traveled impact regional congestion. These results will inform efforts by MnDOT and its partners on the outcomes of reduced travel demand.

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New Project: Assessment of Pedestrian Safety and Driver Behavior Near Automated Vehicles

With the number of automated vehicles increasing on our roadways it is important to understand their potential impacts and how other road users will interact with them. In the future, there will be a more pronounced shared levels-of-automation transportation network, with fully manual, partially automated, and fully automated vehicles sharing the same Minnesota roads. While planners and engineers have a reasonable idea of how humans drive around other humans, what is not as well-known is human driving behavior around automated vehicles.

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Making Freeway Travel Times in the Twin Cities Area More Reliable

Providing consistent freeway travel times for Twin Cities area drivers requires careful traffic management and well-planned freeway projects. To effectively respond to incidents and identify the most needed renovations, MnDOT traffic managers need to know precisely where, when and why congestion is happening.

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New Technology and Existing Equipment Improve Statewide Vehicle Classification Counting Process

In a recent study, researchers leveraged previous MnDOT research and existing traffic monitoring infrastructure to refine inductive loop signature technology that counts and classifies vehicles. Positive results have given MnDOT a feasible and cost-effective way to collect vehicle classification data throughout the state for planning and decision-making.

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Model Helps Predict Likelihood of Farm Vehicle Crashes on Public Roads

This article was originally published in Catalyst, January 2022.

A U of M study of farm vehicle safety on rural roads identified factors—such as crop type and number of vehicles operated—that can help predict the likelihood of a farm’s vehicles being involved in a crash on a public road.

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Effect of Real-Time Winter Road Condition Messages on Driver Behavior

To help make roads as safe as possible in winter, MnDOT uses dynamic message signs (DMS) to display weather advisories to drivers. Using DMS to display real-time road condition information could further enhance safety by potentially resulting in reduced driving speeds and safer following distances. Roadside pavement sensors can provide real-time road condition data for these warning messages, alerting drivers to conditions ahead.

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How Did COVID-19 Affect Driver Safety?

The COVID-19 pandemic resulted in fewer drivers on Minnesota’s roads in 2020 than in the previous year. Emptier roadways seem like they should be safer, but many states measured increases in speeding. For example, California issued twice as many speeding tickets, Iowa reported a 65% increase in driving 25 mph or more over the speed limit, and Ohio experienced the highest number of traffic fatalities since 2007. Clearly, some drivers were taking advantage of empty streets to speed. The pandemic also strained police forces, resulting in less enforcement.

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Affordable Lane-Departure Warning System is on the Road to Market Readiness

This article was originally published in Catalyst, November 2021.

With the improvements made to their lane-departure warning system, U of M researchers are one step closer to preventing highway crashes and deaths. In a recent project, the research team enhanced its lane-departure warning system, which uses standard GPS data rather than expensive cameras or maps—moving toward an affordable, market-ready product to warn drivers about dangerous lane drift due to drowsiness or inattention.

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