More than 2,500 intersections in the Tar Heel State will become part of a one-year pilot project led by the North Carolina Department of Transportation (NCDOT) using technology from Flow Labs to better understand how traffic is moving in real time.
“Using Flow Labs’ analytics tools, we’re evaluating travel patterns to identify which of our 400-plus signal systems need retiming, helping reduce delays and improve traffic flow,” said Aaron Moody, assistant director of communications at the NCDOT, in an email. “The platform supports data-informed decisions while maintaining direct oversight and interpretation by our engineering staff."
Flow Labs technology does not require complicated hardware and software deployments, but instead uses “probe data” — the data coming from connected vehicles, or even digital devices in the vehicles — to provide various metrics related to speed or traffic delays.
“It’s the same type of technology that powers the information that flows through Google Maps, or your GPS devices,” explained Jatish Patel, CEO of Flow Labs, adding that the company takes this data and converts it into insights for “mission-critical infrastructure, like traffic signals.”
“They [Flow Labs] aggregate probe data into signals' performance measures for individual intersections and corridors, but there is no additional technology, hardware or software deployed at the individual intersections,” Moody said.
Flow Labs uses machine learning to process the data “to provide them [NCDOT] with accurate and timely insights into signal performance,” Patel said.
Understanding how thousands of traffic signals are performing means NCDOT must analyze millions of journeys every day.
“And one of their biggest challenges is their ability to see what’s happening,” Patel said, noting that large amounts of data, if not thoroughly analyzed, can go unused.
“What our technology does is it gives them information from vehicles on the road that allows them to understand what a typical road user experiences at the intersection,” Patel said.
“And to see that all in one place allows them to be more proactive, to identify issues, as they start," he added, "not when they’ve impacted thousands of road users over multiple months,” he added.
The technology can be used to optimize signals, providing engineers with improved signal timing plans based on the agencies' preferences and traffic management strategies, as well as offering predictive information related to how well traffic management plans will perform.
“The data helps our engineers identify underperforming corridors, prioritize adjustments and document improvements with before-and-after comparisons,” Moody said. “It also supports early detection of potential issues, allowing for timely fixes that minimize disruptions for travelers.”
