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How Google is Using AI to Combat Stop-and-Go Traffic and Reduce Emissions

18.12.2024 06:07 AM
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How Google is Using AI to Combat Stop-and-Go Traffic and Reduce Emissions
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In early 2020, a team within Google Research was tasked with brainstorming innovative ways to accelerate climate mitigation. Among various ambitious ideas, a simple observation at the dinner table sparked a groundbreaking project. Dotan Emanuel, a software engineer on the team, recalls his wife’s suggestion: “Why don’t you do something about traffic lights? We stand at them for no good reason.”
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How Google is Using AI to Combat Stop-and-Go Traffic and Reduce Emissions
the problem: traffic and its environmental impact
road transportation is a major contributor to global greenhouse gas emissions, with city intersections being hotspots for pollution. emissions at intersections can be up to 29 times higher than on open roads, with half of this pollution stemming from vehicles accelerating after stopping. with millions of traffic lights worldwide, optimizing their functionality presented an enormous opportunity to tackle emissions.

the solution: project green light
dotan and his team dived into traffic engineering and discovered that while some stop-and-go traffic is inevitable, much of it could be reduced by optimizing traffic light timing. traditional approaches, such as installing expensive hardware or conducting manual vehicle counts, fall short in providing comprehensive data.


how project green light works
using google maps data, the ai model analyzes traffic patterns at intersections, including stop-and-go movements, average wait times, and the coordination between nearby traffic lights. based on these insights, the model makes actionable recommendations, such as:

adjusting red light durations during off-peak hours.
synchronizing adjacent traffic lights to improve flow.
city engineers can review and implement these recommendations within minutes, utilizing their existing infrastructure.

scalable, cost-effective, and impactful
one of the project’s strengths lies in its simplicity. cities don’t need to invest in additional hardware or software. google provides recommendations via an easy-to-use dashboard, along with impact metrics, such as reduced stops and fuel savings.

“we purposely set up everything to be lightweight and scalable,” says program manager alon harris.

results and expansion
since its first pilot in 2021, project green light has expanded to more than 70 intersections across cities like rio de janeiro, seattle, bengaluru, and boston. early results are promising:

up to 30% fewer stops at intersections.
up to 10% reduction in emissions at traffic lights.
benefits extend to 30 million car rides monthly.
looking ahead, the team aims to scale the project to hundreds of cities and tens of thousands of intersections in the coming years.

beyond traffic: a better driving experience
beyond environmental benefits, project green light brings joy to drivers by creating smoother commutes. dotan reflects, “you know when you drive through a sequence of five green lights, and it feels like your lucky day? we want to make that feeling more common to more people around the world.”

with project green light, google is proving that small, data-driven changes can have a significant impact — making cities greener, driving more efficient, and commutes a little happier.





 
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