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sites.research.google uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more. Using Google AI to reduce traffic emissions Road transportation is responsible for a significant amount of global and urban greenhouse gas emissions. It is especially problematic at city intersections where pollution can be 29 times higher than on open roads. At intersections, half of these emissions come from traffic accelerating after stopping. While some amount of stop-and-go traffic is unavoidable, part of it is preventable through the optimization of traffic light timing configurations. To improve traffic light timing, cities need to either install costly hardware or run manual vehicle counts; both of these solutions are expensive and don’t provide all the necessary information. Green Light uses AI and Google Maps driving trends, with one of the strongest understandings of global road networks, to model traffic patterns and build intelligent recomm
Green Light - Green Light Skip to main content Green Light About Green Light How it works Bring Green Light to your city FAQs Publications Green Light Using Google AI to reduce traffic emissions Blog Media Express interest play silent looping video pause silent looping video unmute video mute video Green Light optimizes traffic lights to reduce vehicle emissions in cities, helping mitigate climate change and improving urban mobility Road transportation is responsible for a significant amount of global and urban greenhouse gas emissions. It is especially problematic at city intersections where
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