Category Archives: Traffic and Safety

New Project: Red Light Running Warning System

Red-light violations at traffic signals are a major contributor to crashes and fatalities. Right-angle type crashes typically account for the most serious of these collisions, and most of them are caused by vehicles running red lights. This research will explore technology that could be used to warn drivers when they are about to run a red light.

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Evaluating Weather’s Effects on the Accuracy of Automated Vehicles

Fully automated vehicles may not be market-ready yet, but one day, they expect to provide a variety of benefits like reduced emissions and greater safety and transportation equity. These vehicles and the complex combination of underlying technologies that power them are continually being tested and improved to ensure the vehicles will meet the highest standards of safety and performance. 

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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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