Quebec City Launches AI Traffic Management with Google

Published Date : 20/08/2025 

Quebec City has become the first Canadian municipality to partner with Google's Green Light project, leveraging artificial intelligence to optimize traffic flow, reduce congestion, and lower greenhouse gas emissions. 

Quebec City has started synchronizing traffic lights with the use of Google’s artificial intelligence, technology the city says will improve traffic flow, reduce congestion, and lower greenhouse gas emissions.

According to Google Canada, Quebec City is the first municipality in the country to partner with the web giant’s Green Light project, which the company offers free of charge to cities. “The Green Light project uses driving trends from Google Maps and artificial intelligence to map a city’s traffic patterns and then make specific recommendations for specific intersections that can be implemented very quickly by city engineers,” said Laurence Therrien, public affairs manager at Google Canada.

She noted that the AI model does not replace the work of engineers but serves as an additional tool. “The aggregated and anonymized trends from Google Maps really give a much faster and more reliable overview of a city’s traffic than if it had to be done manually or with existing systems,” Therrien said.

Including Quebec City, the Green Light project is being used in 19 cities on four continents. Google has analyzed traffic data in these cities and said the project has “demonstrated the potential to reduce frequent stops and starts by up to 30 per cent and estimated carbon dioxide emissions at urban intersections by 10 per cent.”

Therrien says it’s “not necessarily” true that people will flock to cars if a city’s traffic flow improves. “If car traffic flows more smoothly, so does bus traffic,” she said. “So it encourages public transportation, which is much more efficient than if traffic lights are not automated.”

In Quebec City, the project has already made it possible to adjust the timing of traffic lights at 11 intersections, and the initial results are positive, according to Mayor Bruno Marchand. “An innovative project like Green Light allows us to quickly and effectively optimize our road network, thereby improving traffic flow and efficiency,” said Marchand in a news release on Monday.

The release noted that during the evening rush hour, traffic lights were “slightly out of sync” near a busy intersection, causing delays and traffic jams. “Using the Green Light AI model, Google proposed reducing the gap between the lights by 15 seconds to align them (with the other intersection),” leading to smoother and better co-ordinated travel. This example shows how AI “can complement the work of municipal experts by proposing simple, effective, and data-driven adjustments,” the city noted. 

Frequently Asked Questions (FAQS): 

Q: What is the Green Light project by Google?

A: The Green Light project by Google uses driving trends from Google Maps and artificial intelligence to map a city’s traffic patterns and make specific recommendations for traffic light synchronization at intersections.

Q: How does the AI model help in traffic management?

A: The AI model provides a faster and more reliable overview of a city’s traffic patterns, allowing city engineers to make data-driven adjustments to traffic lights, improving traffic flow and reducing congestion.

Q: What are the benefits of the Green Light project?

A: The project has the potential to reduce frequent stops and starts by up to 30 per cent and estimated carbon dioxide emissions at urban intersections by 10 per cent, leading to smoother traffic flow and more efficient public transportation.

Q: How is Quebec City implementing the Green Light project?

A: Quebec City has already adjusted the timing of traffic lights at 11 intersections using the Green Light AI model, with initial results showing positive improvements in traffic flow and efficiency.

Q: Does the AI model replace the work of city engineers?

A: No, the AI model does not replace the work of city engineers. Instead, it serves as an additional tool to complement their efforts by providing data-driven recommendations for traffic light adjustments. 

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