Multisensor Data Fusion Optimizes Traffic Flow & Intersection Safety, Delivering Cost & Time Savings Support CleanTechnica's work through a Substack subscription, on Patreon, or on Stripe. Help us produce all of the high-quality, original content we publish week after week despite the challenges of content-scraping AI, antisocial media, inflation, and other hurdles. Digital-Twin Framework Provides Real-Time Visibility Into Traffic Conditions We have all been there: stopped at a red light at an empty intersection or narrowly avoiding a collision after a driver runs a red light. Researchers at the National Laboratory of the Rockies (NLR) are working to reduce such risks by improving how intersections “see” and respond to real-time traffic conditions. Their approach combines infrastructure-based cooperative perception, multisensor data fusion, and data-driven analytics to enhance safety and operational efficiency at signalized intersections — reducing delays, saving time, and lowering transportation costs. The need for these improvements is significant. Traffic crashes and congestion impose major costs in the United States, with more than 40,000 fatalities and approximately $300 billion in economic losses each year. Intersections account for a disproportionate share of the problem, contributing to nearly one-quarter of all traffic fatalities and half of all traffic injuries. More efficient signal operations could also generate substantial savings. According to the Federal Highway Administration, optimizing signal timing can reduce delays by 15%–40% and fuel consumption by up to 10%, depending on conditions. “A substantial share of crashes and excess fuel consumption are associated with intersections,” said Stan Young, an NLR advanced mobility specialist. “It’s a persistent challenge that, until recently, was difficult to solve.” A Digital Twin of Intersection Activity At the center of this effort is IPC-Fusion, an open-source toolkit — now available for licensing — that integrates data from sensors mounted on traffic lights and nearby buildings, along with connected-vehicle