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At the start of 2020, a team within Google Research was asked to explore new ideas for research projects that focused on accelerating climate mitigation. \u201cWe were looking into all kinds of big ideas, from cultivated meat to energy to air pollution,\u201d Dotan Emanuel, a software engineer on the team, says.<\/p>\n
At the dinner table one evening, Dotan shared some of those big ideas with his family \u2014 and the conversation soon pivoted to a frustration familiar to many of us: \u201cMy wife Osnat said, \u2018Why don\u2019t you do something about traffic lights? We stand at them for no good reason,\u2019\u201d he recalls.<\/p>\n
Road transportation is responsible for significant global and urban greenhouse gas emissions. It\u2019s especially problematic at city intersections where pollution can be 29 times higher than on open roads, and about half of these emissions come from traffic accelerating after stopping. With millions of traffic lights across the world, the scale of the problem was huge \u2014 and if Google could do something to address it, so was the opportunity.<\/p>\n
\u201cMy initial thought was that we can\u2019t do anything about traffic lights,\u201d Dotan says. \u201cBut when it comes to research, the most fascinating challenges lie in the unknown.\u201d<\/p>\n
With their curiosity sufficiently piqued, Dotan and his team dug into the mechanics of traffic engineering. They found that while some amount of stop-and-go traffic is unavoidable, a portion can be prevented by optimizing traffic light timing. To do that, cities traditionally needed to either install expensive hardware or run time-consuming manual vehicle counts, neither of which provide complete information on key parameters they need.<\/p>\n
\u201cWe quickly understood we have a strong advantage that cities could benefit from \u2014 over a decade of Google Maps driving trends from across the globe,\u201d Dotan says. \u201cAnd a few weeks later, we had a project proposal ready.\u201d<\/p>\n
That proposal was for Project Green Light, an initiative that uses AI to make recommendations for city engineers to optimize existing traffic lights and reduce stop-and-go emissions. After evaluating dozens of other great ideas, Green Light was chosen for its simplicity, scalability and potential for impact.<\/p>\n<\/div>\n