Can Google Make Stoplights Smarter?

An anonymous reader shares a report: Traffic along some of Seattle's stop-and-go streets is running a little smoother after Google tested out a new machine-learning system to optimize stoplight timing at five intersections. The company launched this test as part of its Green Light pilot program in 2023 in Seattle and a dozen other cities, including some notoriously congested places such as Rio de Janeiro, Brazil, and Kolkata, India. Across these test sites, local traffic engineers use Green Light's suggestions -- based on artificial intelligence and Google Maps data -- to adjust stoplight timing. Google intends for these changes to curb waiting at lights while increasing vehicle flow across busy throughways and intersections -- and, ultimately, to reduce greenhouse gases. "We have seen positive results," says Mariam Ali, a Seattle Department of Transportation spokesperson. Green Light has provided "specific, actionable recommendations," she adds, and it has identified bottlenecks (and confirmed known ones) within the traffic system. Managing the movement of vehicles through urban streets requires lots of time, money and consideration of factors such as pedestrian safety and truck routes. Google's foray into the field is one of many ongoing attempts to modernize traffic engineering by incorporating GPS app data, connected cars and artificial intelligence. Preliminary data suggest the system could reduce stops by up to 30 percent and emissions at intersections by up to 10 percent as a result of reduced idling, according to Google's 2024 Environmental Report. The company plans to expand to more cities soon. The newfangled stoplight system doesn't come close to replacing human decision-making in traffic engineering, however, and it may not be the sustainability solution Google claims it is.

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