The City of Toronto has given Rogers Communications Inc. the green light to set up cameras and sensors at five downtown intersections that will track the movement of vehicles, pedestrians and cyclists with the aim of alleviating gridlock.
Rogers says the 5G-driven artificial intelligence system will capture real-time data about traffic volumes, speeds and congestion levels at the intersections as part of the city’s congestion management plan, which council approved last fall.
On Thursday, councillors gave the city the go-ahead to launch “transportation innovation projects” that use “both pre-commercial and early-market technologies.”
That paves the way for the city to launch the pilot in partnership with Rogers. The company will install the cameras and sensors along University Avenue at Adelaide, King, Wellington and Front streets as well as York Street and Bremner Boulevard.
The pilot will begin with an initial months-long phase focusing on data collection, after which the city will use the AI software to determine what improvements could be made to help ease congestion at the intersections. It said the technology would eventually be able to analyze and manage traffic in real-time, including through AI-powered traffic signal adjustments.
“I think we’ve all kind of had that experience where you’re sitting at a traffic light and there’s no cars coming in the other direction,” said Neel Dayal, head of innovation and partnerships for Rogers.
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“The idea here is that situation really shouldn’t occur. By having a good bird’s eye view of what’s happening in the intersection, you can dynamically change the lights to ensure that there’s no cars sitting, idling, or pedestrians or cyclists in that matter.”
The city has previously alluded to its intention to pursue such pilots within its congestion management plan.
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Transportation Services general manager Barbara Gray said in a report to the infrastructure and environment committee last month that the city would work “with the local telecommunications companies to create a virtual testbed whereby technologies can be physically implemented in the field but tested in a safe, secure cloud computing environment.”
Dayal said the technology is able to detect and classify various “objects,” including pedestrians, cyclists, buses or cars, and optimize light changes for both safety and traffic flow.
“You can improve both the traffic, but also ensure that there’s safe passage for vulnerable road users,” he said.
This is the first time Rogers is deploying the technology in a major urban environment.
In 2022, it conducted a two-week test of the system as part of a research partnership at the University of British Columbia’s Vancouver campus, where it similarly installed its traffic sensors and cameras at five intersections.
The company said the UBC pilot helped reduce vehicle delays by 182 hours and pedestrian delays by 93 hours on campus, while also slashing 2.8 tonnes of carbon emissions during the trial.
The technology remains deployed at the campus, said Dayal, noting he was curious to see if the results from the upcoming Toronto study would differ given the much higher volume of road users in the city’s downtown core.
“What we learned (at UBC) was the combination of using video and radar actually gave us the … understanding what’s actually happening at the intersection,” he said.
“We know that the city is very focused on extending different modes of transportation, including walking and cycling and so we want to make sure that the roads are safe for those types of users.”
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