These traffic lights use AI to always turn green for cyclists

If you ride along a bike path in the U.K. city of Leeds and approach a street, the traffic light can automatically turn green for you—or stay green if you’re already midway across.

The city is one of a growing number testing technology that uses sensors, anonymous data, and AI to make it easier to cross streets. Made by a company called VivaCity (known as Viva in the U.S.), the sensors can detect cyclists and pedestrians from more than 200 feet away. In some cases, someone on a bike might not need to stop at the corner. Pedestrians can keep walking without breaking their stride. (Cities can choose to program traffic signals to give cyclists either a shorter wait or full priority.)

Traditionally, most traffic signals force people who aren’t in cars to push a “beg” button and wait—or risk their life to cross while the light’s still red. If automated sensors exist, they’re typically just for cars.

“At the moment, a lot of traffic signals don’t detect cyclists,” says Matt Shaw, head of product at VivaCity. “If they’re really basic, they operate on a fixed time schedule, so it will just rotate 30 seconds at a time. Or they might have vehicle detection, so they know if a car’s approaching, but they don’t know if a cyclist is.” Wires embedded in the pavement can detect metal, but often miss bikes.

VivaCity’s technology also analyzes direction, so the automatic walk sign isn’t triggered if a pedestrian is just passing by without intending to cross. It also counts the number of people waiting, so cities can choose to use a formula to change the light faster if more people are waiting. Most traffic controllers now “have no idea if it’s one pedestrian or a hundred,” says Shaw. “If you’re in New York City and somebody pushes the button, you’ve got no sense of how many people are waiting.”

Unlike standard traffic signals, Viva’s system also knows if someone in a wheelchair or an elderly person with a walker is still crossing. “Being able to know if a pedestrian’s still on the road, and hold the green light for them, is pretty important,” he says. (The data collection focuses on privacy; after the AI analyzes the video feed, it deletes it, leaving only the number of people and the path that they’re taking, not their identity. The data can’t be used for enforcement.)

In Leeds, the city hasn’t yet gone as far as giving cyclists and pedestrians full priority at major intersections. But at certain crossings where bike paths or sidewalks meet a road, the sensors already prioritize people walking or biking. The tech is one piece of a bigger strategy to become “a city where you don’t need a car,” as the city puts it. That also includes improving bus service and building a better network of bike routes and bike parking. Making streets easier to cross—and shrinking the time that cyclists or pedestrians wait—helps make it a little more likely that people will want to walk or bike.

Some cities are using the underlying data without yet connecting to traffic controllers. In New York City, for example, the Department of Transportation has been using the sensors at some intersections to track trends over time, from the number of bikes or scooters to how fast they’re traveling and the paths that people take to cross the street.

The technology can also track near misses, which lets cities flag dangerous intersections and design interventions, such as changing the timing of signals or banning turns on red at intersections where cyclists have repeated close calls with turning vehicles.

“You can’t solve the problem if you don’t understand where people are cycling,” Shaw says.

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