Road transport is responsible for 25% of global carbon dioxide emissions from fuel consumption, according to data from the Organization for Economic Cooperation and Development (OECD). A large amount of greenhouse gases are emitted at city intersections, where pollution can be up to 29 times greater than on open roads, according to information published by Google on its blog.
The technology giant claims that approximately half of the emissions at intersections and traffic lights come from vehicles stopping and starting. For this reason, it is considered a priority to optimize traffic lights through the well-known green waves to give greater fluidity to traffic and thus reduce the emission of polluting substances into the atmosphere.
Google Research has taken the lead in a project called Green Light to help improve transportation in cities and, consequently, reduce the carbon footprint in large urban conurbations. The Silicon Valley company uses artificial intelligence to optimize traffic lights at intersections, providing its support to those responsible for urban mobility.
Thanks to this tool, engineers can make improvements to existing infrastructure to reduce the number of vehicle stops at red lights.
Optimizing traffic flow at junctions and coordinating adjacent intersections to create green waves allows cities to improve traffic flow and reduce stop-and-go emissions at traffic lights. According to data analyzed by Google, at the 70 intersections in 12 cities where the green wave has already been launched with the help of artificial intelligence, emissions have been reduced by up to 30% during stops and up to 10% during intersections.
“In the cities where the Green Light project is being applied, emissions can be reduced and fuel saved in a total of 30 million journeys each day,” Google points out on its blog.
Seattle and Rio de Janeiro are the only two cities in North and South America where the Green Light project is already applied. This program is also present in 10 other European and Asian cities: Manchester, Hamburg, Budapest, Haifa, Abu Dhabi, Bangalore, Hyderabad, Calcutta, Bali and Jakarta.
Before the use of AI, the task of accessing reliable data to optimize traffic light synchronization represented a complex and costly challenge for a large number of urban traffic engineers. As a result, numerous intersections continued to operate with outdated configurations.
However, the Green Light project has emerged as a catalyst for change, introducing innovative solutions supported by artificial intelligence. Using Google Maps to model intersections and traffic flow, the technology leader has built an AI-based model of each intersection. Aspects such as intersection structure, traffic patterns (start and stop) and schedules have been taken into account to identify possible adjustments to traffic light synchronization.
After Google Research’s system has collected and processed this data, it uses AI algorithms to detect potential improvements in traffic light timing. Once this work is completed, the company shares the resulting recommendations with the city’s traffic authorities, who have the option to implement them if they so choose.
