The project Google Green Light is an initiative aimed at optimizing and improving the efficiency of urban traffic through use of artificial intelligence and machine learning. The central idea is to reduce waiting time at traffic lights and, as a consequence, reduce vehicle congestion and polluting gas emissions.
Green Light uses real-time data obtained from various sensors and traffic cameras installed in the city. In part, it is the same data that serves Google Maps. They are processed by advanced algorithms that analyze traffic patterns and predict the best sequence of traffic light changes to speed up traffic flow. This way, drivers experience fewer delays and more fluid circulation.
One of the most notable benefits of the project is its ability to dynamically adapt to different traffic conditions, such as accidents, special events, or changes in vehicle volume during different times of the day. This allows a more flexible and efficient traffic management compared to traditional pre-programmed traffic light systems.
The Green Light project not only improves the driving experience, but also contributes to a significant reduction of the carbon footprint of cities. Early figures indicate a potential reduction of up to 30% in shutdowns, resulting in a 10% reduction in greenhouse gas emissions.
