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  • Writer's pictureBig Data Ben

Google's AI is making traffic lights smarter

October 10, 2023

Have you ever been stuck at a red light for what seems like an eternity, while no cars are passing by on the other side? Have you ever wondered how much gas you are wasting and how much pollution you are causing by idling at a stop light? Well, Google has a solution for that. It's called Project Green Light, and it uses artificial intelligence (AI) to optimize the timing of traffic signals based on real-time data from Google Maps.

Project Green Light was launched in 2021 as a pilot program in four intersections in Israel, where it reduced fuel consumption and waiting time by 10 to 20 percent. Since then, it has expanded to 12 cities around the world, including Rio de Janeiro, Manchester, and Jakarta. Google says that its AI recommendations have cut as many as 30 percent of stops and 10 percent of emissions for 30 million cars a month. That's equivalent to taking about 500,000 cars off the road for a year!

How does it work? Google's AI analyzes data from Maps users to calculate the amount of traffic congestion and the average wait time at each intersection. It then trains a model that can adjust the traffic signal timing to reduce idle time and the number of times drivers have to brake and accelerate. The best part is that the AI works with existing infrastructure and traffic systems, so city engineers can easily implement it and monitor the results.

Google says that Project Green Light is part of its goal to help its partners reduce their carbon emissions by a gigaton by 2030. It also has other sustainability features, such as fuel-efficient routing in Maps, flight-routing suggestions to reduce contrails, and estimated emissions information for flights.

Google's AI is making traffic lights more efficient and less annoying for drivers, while also helping the environment. Isn't that amazing? If you want to learn more about Project Green Light and Google's other sustainability initiatives, you can check out the original article here:

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