With its initiative, Project Green Light, Google is leveraging artificial intelligence and vast amounts of Maps driving data to improve traffic flow in cities. Launched in 2020, the project aims to reduce emissions by optimizing the timing of traffic lights.
Project Green Light uses data from Google Maps to develop an AI model that analyzes traffic patterns at intersections. This model examines factors such as stop-and-go movements, average wait times, and coordination between adjacent intersections. Based on this analysis, the model suggests improvements, such as adjusting red light durations during off-peak hours or better syncing adjacent traffic lights.
The recommendations generated by Project Green Light are shared with cities, which can then decide how to implement them using their existing traffic light systems. Importantly, Project Green Light does not operate as a live system. It does not monitor drivers in real time or adjust traffic lights on the fly. Google emphasizes that Maps users do not receive priority at intersections.
The project relies on aggregated, anonymous data to benefit all road users. Project Green Light is active at 70 intersections across 12 cities, impacting 30 million car rides each month.
The initiative promises to improve traffic flow and reduce emissions. It may expand to more cities, including those in Canada, in the future.