Urban planners may soon have a new way to measure traffic congestion. By capturing the different routes by which vehicles can travel between locations, researchers have developed a new computer algorithm that helps quantify regions of congestion in urban areas and suggests ways around them.
The study, published in the Journal of Physics: Complexity, used traffic speeds from taxis in New York City to demonstrate how road infrastructure and driver behavior can create complex road networks that differ among cities.
“Ride-hailing and ride-sharing services, and eventually autonomous vehicles, are disrupting traffic patterns in cities,” said Richard Sowers, a professor of mathematics and of industrial and enterprise systems engineering at the University of Illinois at Urbana-Champaign and lead author of the study. “We identified a need for a tool that could help urban planners understand how and why this happens.”
The team approached the issue by designing a computer algorithm to capture the topology – or relationship between the different routes between locations – of road networks.
Read more at University of Illinois at Urbana-Champaign, News Bureau
Image: Professor Richard Sowers, left, and recent graduate Daniel Carmody have developed a new computer algorithm that will help urban planners understand and measure traffic congestion and suggest alternative routes. (Credit: L. Brian Stauffer)