Google's Project Green Light uses AI to change traffic lights to get a 30% decrease in red light stops.
"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 recommendations for city traffic engineers to optimize traffic flow. Early numbers indicate a potential for up to 30% reduction in stops and 10% reduction in greenhouse gas emissions. By optimizing each intersection, and coordinating between adjacent intersections, we can create waves of green lights and help cities further reduce stop-and-go traffic. Green Light is now live in 70 intersections in 12 cities, 4 continents, from Haifa, Israel to Bangalore, India to Hamburg, Germany -- and in these intersections we are able to save fuel and lower emissions for up to 30M car rides monthly."
"Building on our decades-long effort to map cities across the world, we can infer existing traffic light parameters including: cycle length, transition time, green split (i.e. right-of-way time and order), coordination and sensor operation (actuation)."
"We create a model to understand how traffic flows through the intersection. This helps us understand typical traffic patterns including patterns of starting and stopping, average wait times at a traffic light, coordination between adjacent intersections (or lack thereof), and how traffic light plans change throughout the day."
"Using AI, we identify possible adjustments to traffic light timing. We share these adjustments as actionable recommendations with the city. The city's traffic engineers review the recommendations, approve them, and they can easily implement them in as little as 5 minutes, using the city's existing policies and tools."
Project Green Light's work to reduce urban emissions using AI
