Quebec City has implemented Google’s AI technology to synchronize traffic lights, aiming to enhance traffic flow, minimize congestion, and decrease greenhouse gas emissions.
Google Canada revealed that Quebec City is leading the way in this initiative by collaborating with the tech giant’s Green Light project, a first-of-its-kind partnership in the country.
The Green Light project leverages AI to analyze traffic patterns sourced from Google Maps and merges this information with data on the locations of traffic signals within the city.
Laurence Therrien, the public affairs manager at Google Canada, explained, “The Green Light project utilizes Google Maps driving trends and AI to analyze a city’s traffic flow, providing precise recommendations for optimizing specific intersections swiftly by city engineers.”
She emphasized that AI data acts as a supplementary tool and does not replace the expertise of engineers. “The aggregated data from Google Maps offers a more efficient and accurate insight into a city’s traffic compared to manual methods or existing systems,” she added.
Currently operational in approximately 20 cities worldwide, the Green Light project has shown promising results. Google’s analysis across these cities indicates a potential reduction of up to 30% in frequent stops and starts, along with a 10% decrease in CO2 emissions at urban intersections.
The primary goal of Google’s AI technology is to streamline vehicle traffic efficiently, prompting questions about its impact on encouraging more car usage over active or public transportation. However, Therrien emphasized that smoother car traffic also benefits bus traffic, thereby promoting public transportation as a more efficient choice.
Quebec City has already seen positive outcomes from the Green Light project, with adjustments made to the timing of traffic lights at 11 intersections. Mayor Bruno Marchand’s administration reported favorable initial results, stating that the project has optimized the road network swiftly and effectively, enhancing traffic flow and overall efficiency.
An illustrative case highlighted by the city involved the AI model identifying inefficiencies at an intersection during evening rush hour. By recommending a 15-second reduction in the delay between lights, traffic flow on the northbound route significantly improved, demonstrating the AI’s ability to suggest simple yet impactful adjustments based on data-driven insights.
The Green Light project is offered free of charge to cities interested in implementing this innovative solution.
