Google has developed an AI-powered initiative called Project Green Light to reduce stop-and-go traffic and cut down on fuel emissions. Using Google Maps’ driving trends, Green Light analyses traffic flow and identifies opportunities to optimise traffic light timing.

Cities can implement these recommendations quickly and easily, without investing in new hardware or software. Currently live in over 70 intersections, Green Light has the potential to reduce stops by up to 30% and lower emissions at intersections by up to 10%. The team aims to scale Green Light to hundreds of cities and tens of thousands of intersections in the coming years.

At the start of 2020, a team within Google Research was asked to explore new ideas for research projects that focused on accelerating climate mitigation.

Road transportation is responsible for significant global and urban greenhouse gas emissions. It’s especially problematic at city intersections where pollution can be 29 times higher than on open roads, and about half of these emissions come from traffic accelerating after stopping.

The team dug into the mechanics of traffic engineering. They found that while some amount of stop-and-go traffic is unavoidable, a portion can be prevented by optimising traffic light timing. To do that, cities traditionally needed to either install expensive hardware or run time-consuming manual vehicle counts, neither of which provide complete information on key parameters they need.

The team developed a proposal, Project Green Light, to use AI to make recommendations for city engineers to optimise existing traffic lights and reduce stop-and-go emissions.

The Green Light team used Google Maps’ driving trends to create an AI model that measures how traffic flows through an intersection, including patterns of starting and stopping, average wait times at a traffic light, and coordination between adjacent intersections. The model identifies possible improvements, like shaving off several seconds from a red traffic light during off-peak hours or an opportunity to coordinate between intersections that are not yet synced. The city’s engineers then review those recommendations and can implement them in as little as five minutes, using their city’s existing infrastructure.

Since their first pilot in 2021, the team has tested more and more intersections, developed more accurate predictions and took Green Light on the road to more than a dozen cities across the world, including Rio de Janeiro, Seattle, Bengaluru, and most recently, Boston. The team also developed a comprehensive dashboard to easily share recommendations and analytics with partner cities, while continuing to monitor for any new needed changes.

The Green Light dashboard provides city-specific actionable recommendations and supporting trends. After a recommendation has been implemented, the dashboard shows an impact analysis report.

Today, Green Light is live in over 70 intersections, helping to save fuel and lower emissions for up to 30 million car rides monthly. Early numbers indicate the potential to reduce stops by up to 30% and reduce emissions at intersections by up to 10%.

The team is working to scale Green Light to hundreds of cities and tens of thousands of intersections in the next few years.

“In order to achieve a positive climate impact, we want to be able to deploy high-quality Green Light recommendations to many cities globally and scale fast. So we purposely set up everything to be simple and lightweight — cities don’t need to invest in any dedicated software or hardware integrations,” said Green Light Program Manager Alon Harris. “We just share our recommendations with the city, and then they evaluate them and take action.”