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Photo of traffic lights.
Photo by Vit Brunner

Making Traffic Smarter

An intelligent transportation system could reduce wait times at traffic lights in Toronto by more than half

Build a better traffic light and the world may not exactly beat a path to your door, but at least it will get there with fewer delays.

As Ontario’s Liberal government gears up to find ways to pay for $50 billion in new transit service for Greater Toronto, a U of T civil engineering team says it has a key piece of the solution to the region’s crippling gridlock: cutting-edge computer technology designed to optimize the performance of traffic signals at the city’s most frustrating intersections.

According to detailed computer simulations done with City of Toronto traffic data collected at 59 downtown locations in 2009, the deployment of a U of T-designed “intelligent transportation system” (ITS) could reduce wait times at intersections by 40 to 70 per cent. Vehicle emissions would drop as a result by as much as 30 per cent. And “the benefits are immediate once the system is turned on,” says civil engineering professor Baher Abdulhai, director of the Toronto ITS Centre.

The U of T system, known as MARLIN-ATSC, relies on game theory, artificial intelligence algorithms and in-road sensors that allow traffic signal controllers to “learn” how to adapt to local traffic patterns – with the goal of dynamically setting green light-red light intervals to reduce queues as they arise. Abdulhai likens the process of making a traffic light smarter to the way a baby learns how to walk.

Other approaches to traffic-signal control require massive computing power. The U of T system, based on the PhD thesis of Samah El-Tantawy, gets around this obstacle by delivering improvements without a cumbersome centralized system. “The system is most useful, simply, where the congestion is,” says Abdulhai. “The simulation shows us with good precision which intersections benefit the most – and how much benefit to expect. This process helps prioritize investment by picking the best candidate intersections, or groups of intersections, to start with.”

Abdulhai’s team is working with the university’s Innovations and Partnerships Office to commercialize MARLIN, and has “strong interest” from a U.S. partner. Gridlock in Greater Toronto is said to cost the region about $6 billion a year. Increasingly, “congestion management” tools such as MARLIN are being seen as the third leg of a traffic-control stool that includes more road and transit infrastructure (where warranted) and measures to reduce “demand,” such as congestion-based road tolls.

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