Google Finds AI-powered Answer to Traffic Light Frustration
How many times have you been stuck at some traffic lights for no good reason?
It is estimated that drivers spend about eight minutes each day waiting at red lights.
At city intersections, pollution can be 29 times higher than on open roads — about half of these emissions come from traffic accelerating after stopping.
There are millions of traffic lights around the world, so reducing the amount of times they stop traffic could have a big impact on road emissions.
Google’s Project Green Light is an initiative that uses AI and Google Maps data to make recommendations to optimise existing traffic lights.
Kate Brandt, Chief Sustainability Officer at Google, says: “We believe that fighting climate change is an important collective challenge and for three decades, we have been using technology to accelerate meaningful action.
“While we recognise that digital technology alone will not solve the climate crisis, we can already see the tremendous potential that it holds to help accelerate action on sustainability and climate while simultaneously empowering economic growth.”
Stop-and-go traffic emissions
According to the United Nations, the transport sector as a whole contributes about 25% of all energy related greenhouse gas emissions.
As well as this, outdoor air pollution is estimated to cause more than 3.2 million premature deaths per year around the world.
Stop-and-go traffic increases commuting time, fuel consumption and pollutant emissions dramatically. In areas like city centres that experience prolonged traffic, reducing traffic light stops safely could make a significant difference.
Google’s Project Green Light research
The Project Green Light team found that while some amount of stop-and-go traffic is unavoidable, a portion can be prevented by optimising the timing of traffic lights.
Traditionally to do this, cities need to install expensive software or run time-consuming manual vehicle counts.
Neither of these methods provide complete information on some of the key parameters needed.
Dotan Emanuel, a Software Engineer at Google, says: “We quickly understood we have a strong advantage that cities could benefit from — over a decade of Google Maps driving trends from across the globe.”
How Project Green Light works
Google uses driving trends from Google Maps and AI to model traffic patterns and build intelligent recommendations for city traffic engineers.
These recommendations can be implemented in as little as five minutes using existing infrastructure.
Alon Harris, Senior Climate AI Program Manager at Google, adds: “In order to achieve a positive climate impact, we want to be able to deploy high-quality Green Light recommendations to many cities globally and scale fast.
“We purposely set up everything to be simple and lightweight — cities don’t need to invest in any dedicated software or hardware integrations.
“We just share our recommendations with the city and then they evaluate them and take action.”
The recommendations work to optimise adjacent intersections to create waves of green lights.
Tests so far show it has the potential to reduce stops by 30% and greenhouse gas emissions by 10%.
The project is already live in cities including Abu Dhabi, Kolkata, Seattle, Manchester and Hamburg.
Alon explains: “We offer each city dedicated reports with tangible impact metrics, such as how many stops drivers saved at an intersection over time.
“We think that’s going to be a real incentive to not just implement the first recommendations, but also bring Green Light to more intersections.”
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