Project Green Light: Google Uses AI To Tackle Traffic Congestion, Aims To Reduce Carbon Emissions

Google claims that Project Green Light can decrease stop-and-go traffic by up to 30 per cent and reduce emissions at intersections by up to 10 per cent.

According to Google, Project Green Light operates by deducing various traffic light parameters such as cycle length, transition times, green split, and sensor functionality.

Source : Unsplash/Jens Herrndorff

Google for a long time has been working on projects that are meant to help with the betterment of mankind. Recently, Google Research has been running a project that seeks to reduce the duration individuals spend waiting at traffic lights, particularly at urban intersections. According to reports, this project known as 'Project Green Light' is expected to harness traffic engineering and couple it with artificial intelligence (AI) to not only improve traffic flow but also tackle congestion and reduce fuel consumption. This initiative has been taken in light of climate change.

As per reports this project has been running in several cities globally and it is backed by the information provided by Google Maps. 

Google's Project Green Light Explained

In a blog post, Google disclosed that Project Green Light, an initiative from Google Research, aims to enhance sustainability. The project targets road transportation, a significant source of global greenhouse gas emissions, particularly from stop-and-go traffic. Developed by Google's researchers, the AI model behind this project utilises driving data from Google Maps.

The project's team noted that while completely eliminating stop-and-go traffic isn't feasible, cities can mitigate it in two primary ways: by installing costly hardware or by conducting manual vehicle counts. However, Google asserts that these methods fall short of providing comprehensive data on certain parameters.

This is where Project Green Light steps in. It is designed to assist city traffic engineers in optimising traffic flow by analysing traffic patterns and offering recommendations through an extensive dashboard. The project aims to identify potential improvements, such as reducing the duration of red lights during low-traffic periods or synchronising unsynced intersections. Chosen for its simplicity, scalability, and potential impact, this initiative stood out among various explored ideas.

Google claims that this project can decrease stop-and-go traffic by up to 30 per cent and reduce emissions at intersections by up to 10 per cent.

How Will Google's Project Green Light Function

According to Google, Project Green Light operates by deducing various traffic light parameters such as cycle length, transition times, green split, and sensor functionality. The system then constructs a model to interpret traffic behaviours, including average wait times, stop-and-go intervals, and the changes in traffic light patterns throughout the day.

Once these parameters are analysed, the AI model identifies potential enhancements and adjustments that could be made. These actionable recommendations are forwarded to city officials for traffic engineers to review. Google Research asserts that their suggestions can be implemented using the existing infrastructure in as little as five minutes.

The team then tracks the amount of time drivers save at traffic lights and evaluates the environmental impact of these changes using industry-standard models, subsequently sharing the findings with the collaborating city.

Google reports that Project Green Light is currently deployed in over a dozen cities worldwide, including Bengaluru, Boston, Rio de Janeiro, and Seattle. It is said to be reducing fuel consumption and emissions for up to 30 million car trips each month.