Showcase highlights transportation safety research
Greg Winfree, USDOT Assistant Secretary of Transportation for Research and Technology, opened the Roadway Safety Showcase: Safety Innovations for Today and Tomorrow, a one-day event highlighting the latest work by researchers from the Roadway Safety Institute (RSI). The May 21 showcase was held in St. Paul in conjunction with the University of Minnesota’s (U of M) Center for Transportation Studies annual Transportation Research Conference.
RSI’s goal is to prevent crashes that reduce fatalities and life-changing injuries—which fits well with the USDOT’s vision for the future of transportation safety, according to Winfree.
“The first 50 years of transportation safety focused on occupants surviving crashes,” Winfree said. “The next 50 years will be about avoiding those crashes altogether.”
Showcase attendees learned how RSI researchers are developing solutions for some of today’s most pressing safety problems. Researchers shared updates on projects related to tribal nation road safety, connected vehicle technology, bicycle and pedestrian safety, wrong-way driving, automated speed enforcement, alcohol-related hot-spot analysis, a decision-support system for older drivers, and commercial vehicle driver safety.
The event featured researchers from three U of M campuses and other RSI member institutions that included the University of Illinois at Urbana-Champaign (UIUC) and University of Akron.
One of the event’s featured sessions focused on railroad grade crossing safety. More than 200 people lose their lives at railroad crossings in the United States each year, and railroad incidents involving hazardous material pose significant threats to safety, public health, and the environment. Although the number of crashes has been declining in recent decades, the result of a vehicle–train collision is often catastrophic.
Three RSI researchers from UIUC described how they are working to improve safety at and around railroad grade crossings through a three-part project. Their work includes developing modeling techniques that provide a better understanding of crash occurrence, contributor factors, and crash prediction at rail crossings; predicting train arrival times to facilitate emergency response management and alert drivers at unsignalized crossings; and strategically allocating emergency responders and resources in the event of a rail incident, even across jurisdictional boundaries.