Google’s AI stoplight program leads to less stops, less emissions

It’s been two years since Google first debuted Project Green Light, a novel means of addressing the street-level pollution caused by vehicles idling at stop lights.


Green Light uses machine learning systems to comb through Maps data to calculate the amount of traffic congestion present at a given light, as well as the average wait times of vehicles stopped there.


When the program was first announced in 2021, it had only been pilot tested in four intersections in Israel in partnership with the Israel National Roads Company but Google had reportedly observed a “10 to 20 percent reduction in fuel and intersection delay time” during those tests. The pilot program has grown since then, spreading to a dozen partner cities around the world, including Rio de Janeiro, Brazil; Manchester, England and Jakarta, Indonesia.

“Today we’re happy to share that… we plan to scale to more cities in 2024,” Yael Maguire, Google VP of Geo Sustainability, told reporters during a pre-brief event last week. “Early numbers indicate a potential for us to see a 30 percent reduction in stops.


“Our AI recommendations work with existing infrastructure and traffic systems,” Maguire continued. “City engineers are able to monitor the impact and see results within weeks.” Maguire also noted that the Manchester test reportedly saw improvements to emission levels and air quality rise by as much as 18 percent. The company also touted the efficacy of its Maps routing in reducing emissions, with Maguire pointing out at it had “helped prevent more than 2.4 million metric tons of carbon emissions — the equivalent of taking about 500,000 fuel-based cars off the road for an entire year.”

Source: Google’s AI stoplight program is now calming traffic in a dozen cities worldwide

Robin Edgar

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