CNA Wins First Phase of U.S. Department of Transportation Intersection Safety Challenge
A submission by CNA's Center for Data Management and Analytics was selected earlier this week to advance to the next round of the U.S. Department of Transportation (DOT) Intersection Safety Challenge. The competition encourages the development of new and emerging technologies that identify and address unsafe conditions involving vehicles and vulnerable road users at intersections. CNA's entry was developed in partnership with RIIS, a small business that specializes in mobile and machine learning applications.
CNA's proposal is called the Safe Warnings for Intersections Forecasting Tool, or SWIFT. The tool builds upon the award-winning CNA-RIIS First Responder Awareness Monitoring during Emergencies (FRAME) prototype, a situational awareness application for the first responder community. In real time, SWIFT will detect and identify intersection users and predict unsafe conditions. To do this, it will ingest, process, and effectively display Internet of Things data from sources such as existing intersection infrastructure, using AI, and machine learning classification techniques. SWIFT will support the DOT's vision of zero fatalities across the nation's transportation system.
"We are honored to have been chosen as one of 15 prize winners from a pool of 120 innovative plans submitted by researchers and practitioners from universities, state and local agencies, private sector developers, and other organizations," said Shaelynn Hales, director of CNA's Center for Data Management and Analytics. "We are looking forward to the next phase of this challenge."
The concept development team under her leadership included CNA scientists and engineers Rebekah Yang, Addam Jordan, Jeff Daily, Matt Prebble, and Trent Berger, as well as RIIS President Godfrey Nolan.
Each of the 15 winning teams in Stage 1A will receive a prize of $100,000 and an invitation to participate in the system assessment and virtual testing phase. The teams are now expected to develop, train, and improve algorithms for the detection, localization, and classification of vulnerable road users and vehicles using DOT-supplied sensor data collected at a controlled test roadway intersection.
CNA is a nonprofit research and analysis organization dedicated to the safety and security of the nation. It operates the Center for Naval Analyses—the federally funded research and development center (FFRDC) of the Department of the Navy—as well as the Institute for Public Research. CNA develops actionable solutions to complex problems of national importance. With nearly 700 scientists, analysts, and professional staff, CNA takes a real-world approach to gathering data. Its unique Field Program places analysts on aircraft carriers and military bases, in squad rooms and crisis centers, working side by side with operators and decision-makers around the world. CNA supports naval operations, fleet readiness, and strategic competition. Its non-defense research portfolio includes criminal justice, homeland security, and data management.
Note to writers and editors: CNA is not an acronym and is correctly referenced as "CNA, a research organization in Arlington, VA."