The dashboard view of an app that's designed to catch green lights.

Cities have been timing traffic lights for years so that drivers can catch as many green lights as possible to cut down on commuting time. The idea is also to save gas and cut emissions by reducing idle time at red lights.

Now automakers and app developers are using software to try to perfect the idea by calculating the ideal speed to catch a green light and telling drivers how long before a red light turns to green.

Consumer Reports wanted to see how well these app-based systems work, so we tested them in real time in New York City, White Plains, N.Y., and Salt Lake City. We found they didn’t always provide accurate information.

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“These systems were sometimes accurate, but sometimes remarkably wrong,” says Kelly Funkhouser, head of connected and automated vehicles at CR. “They sometimes said the light was green when it was actually red, and vice versa.”

Those results show the limitations of using software to predict when traffic lights will change. That’s mainly because today’s vehicles and traffic lights aren’t yet equipped to communicate directly with each other. The apps instead use sophisticated algorithms, historical data, and information from local traffic control centers to predict whether a light will be red or green. But they aren’t sophisticated enough to help drivers sail through a sea of green lights, CR found.

Drivers who want a smoother commute may be better off ignoring apps and following some tried-and-true strategies, such as paying attention to traffic flow, obeying speed limits, and avoiding hard braking and acceleration.

“It’s much easier to just pay attention to the road,” Funkhouser says, “and not get distracted by the unreliable information on the dashboard.”

How It Works

Traffic light prediction software doesn’t connect directly to traffic lights. Instead, third parties collect traffic light data from local government agencies, analyze it to predict when lights will change, then send that information to drivers over a 4G cellular network. It’s all meant to happen in real time as you drive down the road.

The information shows up on a driver’s dashboard or smartphone display as a recommended speed to keep in order to make the next green light. (It’s never more than the speed limit.) It also shows a countdown timer that tells the driver how long they have before a light changes to red or green.

Currently, these systems are available only in certain areas where local government agencies have agreed to share traffic light data with third parties. And even in those cities it isn’t active at every intersection.

CR tested two systems: Audi’s Traffic Light Information (TLI), which is built into certain 2017 and newer Audi vehicles equipped with Audi Connect (it covers more than 10,000 intersections in more than 30 cities), and a stand-alone smartphone app called EnLighten (it covers about 12,000 intersections in the U.S., although the company tells CR it plans a major expansion soon). 

Audi TLI countdown timer
A countdown timer in an Audi Q8 with Traffic Light Information.

What We Saw

We tested EnLighten using Android and iPhones in Salt Lake City, UT, and TLI in 2019 Audi Q8 and Q3 SUVs in New York City and White Plans, NY in January and last summer. We fixed cameras inside vehicle interiors that could record the app’s display screen, the vehicle’s speedometer, and the traffic lights from the windshield. We also put a time stamp on the video so we could check the accuracy of any countdown timers. Then we reviewed the videos.

Our testers found that both systems were inaccurate in much the same way. Each would occasionally predict that a light would turn red long before it changed or would display no information at all. When our testers were stopped at red lights, sometimes the countdown timers changed their estimates multiple times or didn’t show an estimate at all. Sometimes the red-light timer would complete its countdown, but the light would remain red for much longer.

CR found that predictions were more accurate in places where lights operate on fixed intervals and most intersections have two streets converging at right angles, as opposed to areas where streets have a more complex design. 

Englighten app traffic light prediction
Three views from the EnLighten app: a speed recommendation, a countdown timer, and an error message.

What Went Wrong

Anticipating how traffic lights run can be tricky, Funkhouser says. Because lights don’t communicate directly with cars, any unexpected change—a pedestrian requesting a walk light, a car in a turn lane triggering a green arrow—can throw off a prediction.

“Any given intersection might already have 10 or 20 potential light phases, or timing sequences,” she says. “Adding these unexpected changes just makes it that much more difficult to predict when the light is going to change.”

According to Pom Malhotra, director of connected services at Audi of America, TLI will display signal information only if the car is 95 percent confident in a prediction. If predictions for specific lights are frequently incorrect, they will no longer be displayed, Malhotra says. This in part explains why we occasionally encountered lights with a no-light-change prediction generated by the app. Additionally, TLI analyzes whether the driver has a turn signal on, how fast the car is traveling, and how close the car is to an intersection in order to make a more accurate prediction.

Connected Signals, the company behind EnLighten, told CR that it's planning an update that will drastically expand coverage to many more major roadways. The company says the update will also be able to predict the state of multiple lights on a single road as opposed to just the next signal, so drivers will know what speed to travel to catch multiple green lights in a row. (CR will test this update as soon as it becomes available.)

Ultimately, Malhotra says that services like TLI can help drivers, but they’re no substitute for paying attention. “We’re not offering a safety service,” he says. “You have to liken it to a routing algorithm in a navigation system. It helps you, it gives you convenience, it gives you some confidence, but at the end of the day you are ultimately responsible.”  

How a traffic control center views an intersection.