By using artificial intelligence to analyze Google Maps data, the company can provide recommendations to optimize traffic light management at intersections. The Green Light project, as it is called, has already enabled several cities to reduce waiting at traffic lights and the resulting pollution.
There is no point reminding us that cars pollute. Efforts have been made for years to reduce its impact on the environment, both at the technical and regulatory levels. For its part, Google has unveiled several measures to help save the planet. At the automotive level, the firm is attacking via its Green Light project to a particular element of road traffic: traffic lights. Which report ? It’s very simple: the more time you spend stopped at a red light, the longer the vehicle releases harmful gases. According to a study, pollution at city intersections is 29 times higher than on a non-stop road.
This is where theartificial intelligence comes into play. Google has created a model that analyzes the vast amount of data from Maps, its navigation application. The intersections are reproduced by imagining an optimal interaction between the different lights that make them up, while taking into account the average traffic, the structure of the intersections, etc. This results in concrete recommendations that cities can obtain for minimize waiting at red lightsand so reduce pollution.
Google analyzes Maps data with AI and optimizes traffic light management
It’s a win/win system where motorists save time on their journeys while unknowingly contributing to the environment. Google ensured that the implementation of the suggestions in the management software used by the cities was simple and free. The Green Light project is already being tested in 12 cities around the world : Abu Dhabi, Bali, Bangalore, Budapest, Haifa, Hamburg, Hyderabad, Jakarta, Kolkata, Manchester, Rio de Janeiro and Seattle.
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After modifying the behavior of the traffic lights 70 intersections in total, polluting emissions have decreased. The first estimates speak of a drop of 10%And 30% time saved for drivers. Google specifies that each interested city can register on a waiting list if it wishes to participate in the project.