Idling in rush-hour traffic can be mind-numbing. It also carries other costs. Traffic congestion costs the U.S. economy $121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added. The big reason is that today’s traffic signals are dumb. Smith is developing smart, AI-powered traffic signals that adapt to changing conditions on the fly. His startup, Surtrac, is commercializing the technology. In pilot tests in Pittsburgh, the smart traffic-management system produced impressive results: it reduced travel time by 25 percent and idling time by over 40 percent. That means less time staring out the windshield and more time working, being with family, or doing other things. I’m a Pittsburgh resident who has witnessed the city’s rapidly evolving urban landscape, and I can attest to the mostly frustration-free driving that has resulted from this system despite the city’s growing population. Researchers also estimate the system cuts emissions by 21 percent. It could also save cities the cost of road widening or eliminating street parking by boosting traffic throughput. Conventional traffic lights have preprogrammed timing that is updated every few years, but as traffic patterns evolve those systems can become outdated much more quickly. Surtrac relies on computerized traffic lights coordinating with each other. Radar sensors and cameras at each light detect traffic, and AI algorithms use that data to build a timing plan that moves all the vehicles it detects through the intersection as efficiently as possible, Smith says. The system also sends data to downstream intersections so they can plan ahead. Unlike other smart traffic-management systems, such as one used in Los Angeles, this one is decentralized, so each signal makes its own timing decisions. Smith’s team began implementing the system at nine intersections in Pittsburgh’s East Liberty neighborhood in 2012. The network now spans 50 intersections, with plans to expand citywide. The next step is to have traffic signals communicate with cars: short-range radios have already been installed at 24 intersections, and such systems are expected to be built into some cars in 2017, he said. Signals could then warn drivers about upcoming conditions or imminent light changes, increasing safety and reducing congestion. A vehicle-to-infrastructure communication system could prioritize certain vehicles: the CMU team is working with the Pittsburgh Port Authority to give priority to public buses. Pittsburgh, which is a test bed for Uber’s self-driving cars, also hosts Smith’s work on AI-enhanced traffic signals that communicate with autonomous vehicles, paving the way for fluid, efficient intersections. A startup named Surtrac has been upgrading traffic lights in Pittsburgh with artificial intelligence since 2012, starting with nine intersections in East Liberty and expanding to 50; the company plans to implement the network citywide and then take the technology to other cities. The AI-equipped lights use cameras and radar to collect traffic data, coordinate to move vehicles through intersections as quickly as possible, and operate in a decentralized way so each light controls its own intersection. Your commute could get shorter without you even noticing, thanks to traffic lights with artificial intelligence. Over the past couple of years, a startup named Surtrac has been upgrading traffic lights in Pittsburgh with AI. These lights collect data from cameras and radar about traffic volumes and coordinate by sending information about incoming vehicles to nearby signals, ensuring traffic passes through intersections as quickly as possible. This distributed approach reduces network load and makes the system easier to scale.

Surtrac plans to enable direct communication between the system and cars to notify drivers of traffic conditions and to prioritize certain types of traffic, such as emergency vehicles or buses. So far the AI network has reduced travel time by 25% and idling by 40%, and is estimated to cut emissions by 21%, according to Surtrac. There is no definitive timeline for deploying the system in other U.S. cities, but with self-driving cars approaching, rollout may come sooner rather than later. The AI system began with nine intersections in Pittsburgh's East Liberty neighborhood in 2012 and has quietly expanded to 50 intersections. The startup plans to implement its network across the whole city and then take the technology to other cities around the country. The technology uses a series of lights that employ artificial intelligence to move as many cars through each intersection as possible. The system is decentralized: each light is responsible for one intersection and coordinates by sending information on incoming cars to nearby lights. This reduces network load and makes the system easier to scale. Surtrac also plans to enable the system to communicate directly with cars, which could notify drivers of traffic conditions in advance and prioritize certain types of traffic, such as emergency vehicles or city buses. So far, the AI network has reduced travel time for drivers by 25 percent and time spent idling in traffic by 40 percent.