Artificial Intelligence May Make Traffic Congestion a Thing of the Past

Progress in Pittsburgh
For AI to do its potential magic, the first thing that’s needed is data. Lots of it. So several startups are connecting hundreds of sensors at traffic lights to understand why congestion is happening and learn how to manage it in real time.

For instance, Rapid Flow Technologies, which began as a Carnegie Mellon University research project, is testing its Surtrac traffic-management system in the East Liberty neighborhood in Pittsburgh.

Straddling a major arterial route and home to a Target store, the neighborhood has long been an area of heavy congestion as commuters, shoppers and local residents clog the roads.

“Traffic patterns changed so much over the course of the day that [the traffic signals] didn’t really work all that well” in keeping traffic moving, says Greg Barlow, a Rapid Flow co-founder…

“What if we want to really emphasize person throughput rather than vehicle throughput?” says Karina Ricks, Pittsburgh’s director of mobility and infrastructure. “What if we were able to tell the signal that not only is there a 30-person bus, but there is a 30-person bus with one person in it—the driver—or a 30-person bus with 40 people in it? That can get into the algorithm” to get the most people to their destinations as quickly as possible. The city is working toward this goal with Rapid Flow.