It’s an urban driver’s dream — hitting green, upon green, upon green.

In a town plagued by congestion, Toronto motorists may find more joy in those emerald traffic signal streams than in anything else on the city’s roadways.

But red, it seems, is the far more dominant colour along Toronto’s major commuting routes.

Take a recent westbound trip along Lake Shore Blvd. E. from Woodbine Ave. to Yonge St, a video camera pointed out the windshield.

It was the tail end of rush hour, heading to work in the rain along the four- and six-lane artery. And the chronometer on the recorded video told the tale of this herky-jerky trip.

Of the 14 lights involved in the seven-kilometre journey, six were red upon arrival. Of the 17.5 minutes it took to make the trip — approximately eight minutes and 40 seconds were consumed by braking, or stopping, for traffic signals. And that was a good day.

“Stupid *&#$@ lights!”

But what if you could actually teach those stupid lights a lesson? Literally.

What if you could significantly shorten the delays you face on those fitful rides to work?

Baher Abdulhai, head of the University of Toronto’s Intelligent Transportation Centre, says he and his team can do just that.

Abdulhai’s group has developed a system that would use small, artificial-intelligence-based computers to improve an intersection’s throughput efficiency as much as 60 per cent.

“On average on (simulated) tests in downtown Toronto, we found reductions in queuing delays at intersections of about 40 per cent overall,” Abdulhai says.

In a week that saw Toronto council approve a plan to retime 1,000 of the city’s signals over the next three years, traffic lights have produced headlines along with the usual headaches.

Having completed signal retiming studies along several major arteries last year, including Bloor, Richmond and Adelaide streets, city traffic managers saw delay reductions along those routes of 14 to 33 per cent.

But Abdulhai says the ongoing city project — which will begin this year with 270 signals along Kingston Rd., Weston Rd., Keele St., Parkside Dr. and Lawrence Ave. East and West — can do little to improve traffic flow in the long term.

He says, simply, that traffic flows are fickle, ever-changing beasts that will always defy the expensive studies that inform signal timing strategies.

Abdulhai doesn’t dismiss the utility of retiming lights, especially in areas that have gone unaltered for years. But he says money spent on the project — an estimated $3.5 million — could offset the costs of a system that would improve delay times permanently.

Some are not convinced of the system’s merits, even before it’s been deployed anywhere.

Over at city hall, the key customer for his technology, top transportation officials are questioning the delay reduction estimates that Abdulhai has claimed in his pitches to their department.

“From the (delay reduction) numbers they have often thrown out in meetings, I have concerns about the magnitude of the impact that they (are claiming),” says Toronto transportation chief Stephen Buckle, who questions the 60 and 40 per cent reduction figures.

Buckley also says there are a handful of similar signal systems being shopped around now and that the city will look at each, likely in a competitive bidding format.

He says the system would get no leverage because of its Toronto origins and that city procurement rules may forbid a sole-sourced partnership.

Traffic patterns

Abdulhai says his technology, which uses cameras and “learning” computer chip technology, is agile enough to react to any shifts in traffic patterns and tune signal timing accordingly, over time and entire arterial networks.

Known as the MARLIN-ATSC, for Multi-agent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers, the system assumes this reality:

In a city laid out largely in a straight compass grid, where east-west and north-south streets and arteries cross paths at 2,300 lighted intersections, long ribbons of green lights are not possible, or even desirable.

If, Abdulhai says, you had a predominant traffic flow, travelling in one direction along an arterial road, then such green waves are easily set up.

“You say intersection two, start your green after intersection one with an offset of 20 seconds or so for traffic to travel that distance, and intersection three start your green 60 seconds later,” he says.

“Now that’s a very sensible solution, works like a charm if you have a single artery and one predominant traffic direction.”

“It was a breakthrough 20 years ago, similar to the fact that 20 years ago having a cellphone in your hand the size of your arm was a breakthrough.” Baher Abdulhai referring to the SCOOT traffic light system used in some Toronto intersections

But traffic in Toronto is hardly ever that simple.

First off, vehicle volumes on many of the city’s busiest streets long ago clogged at red line levels in both directions and for much of the day.

“And if you make one direction perfect, the other direction, they’re dead,” Abdulhai says.

More critically, however, attempts to synchronize traffic lights on an east-west artery would have to virtually ignore the green-light longings of intersecting, north-south motorists travelling on roads that are often equally burdened, Abdulhai says.

“That’s where you loose it completely,” he says.

Absent even the possibility of extended green-light waves, transportation managers in Toronto and most major cities have muddled along with a combination of aging and ancient technologies that produce the fits-and-starts traffic flows that frustrate us so.

But as traffic congestion worsens, threatening both economic — its costs are estimated at $5 billion a year — and environmental catastrophes, muddling doesn’t cut it anymore, Abdulhai says.

Getting traffic signalling as correct and efficient as possible, he says, presents the best hope for alleviating worsening gridlock.

Other, obvious solutions — widening intersections, traffic-depressing tolls, or staggered work hours — are often physically impossible, prohibitively expensive or politically toxic.

So while combinations of such steps would help, it’s largely up to the lights to grease the network, Abdulhai says.

Here, Buckley again takes issue, saying accidents, road closures, lanes lost everywhere to condominium construction, these play as much a role as lights in traffic slowdowns.

“There’s a whole host of causes of congestion in downtown and signals are (only) one piece of it,” he says.

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“We’re in discussions about new technologies to improve things, (but) I wouldn’t necessarily say we can commit to one software package,” he says.

The underpinning theory behind the U of T system is that traffic light delays, not the number of reds, need to be reduced.

“If you can pass through two or three intersections and you’re stopped at a fourth one for a long time, then you haven’t done much,” Abdulhai says.

Minimize delays

But how do you get traffic lights to cut the time it takes you to get to or from work, while still producing rafts of reds to impede that journey?

You teach them.

“You have to think of ways to make traffic lights smart enough so that they work individually to minimize delays at their location, but also work in groups that can minimize delays across a network of intersections.”

Abdulhai believes his team has produced such a prodigy.

The technology would augment a lighting network in Toronto that is only minimally responsive to changing traffic conditions, he says.

The vast majority of lighted intersections in the city — about 1,900 — are controlled by traffic signals that use preset timers to switch through their red, yellow and green repertoires.

“These are the oldest types of traffic lights. And their timings are determined by historical traffic flows,” Abdulhai says.

“The issue with that is that historical traffic flows never repeat. You have fluctuations all the time and changes in traffic volumes. The only reason we have them is we don’t have money to replace them”

A responsive step up from this obsolescence is the intersections — some 338 — that are signalled now by lights using a British system known as SCOOT.

But this system itself is now 15 to 20 years old, prone to breakdowns and only marginally capable of cutting delays, Abdulhai says.

Installed along many major city arteries, SCOOT uses sensors embedded in the approaching roadways that send traffic volume information to a central management centre, where a large computer decides whether to lengthen or shorten greens by a few seconds.

Aside from the obvious inadequacy of its options, Scoot is prone to technical problems as its sensors wear out or are covered by snow and its central office communication signals breaks down, Abdulhai says.

“It was a breakthrough 20 years ago, similar to the fact that 20 years ago having a cellphone in your hand the size of your arm was a breakthrough,” he says.

“Today things have advanced very much. You have a computer in your pocket that does what a mainframe used to do.”

That powerful, pocket computer idea is the basic technological concept that the MARLIN system would employ.

The system would install smart-chip technology directly into the signal control cabinets at selected intersections.

The system would use artificial intelligence programming — implanted on a smart-phone-sized chip — that would allow each intersection to “learn” its optimal green light timings based on the shifting traffic patterns it sees through cameras trained on its approaching roadways.

It would also employ game theory, which would force those individual intersections to sacrifice their own optimal actions to the greater good, “talking” with other MARLIN signals to co-ordinate reds and greens — upstream, downstream and around corners, across relevant grid segments.

All MARLIN intersections would offer sufficient pedestrian crossing opportunities, with minimum green times built into the programming’s algorithms.

If a street required 30 seconds to cross on foot, for example, MARLIN would offer that as a minimum, with options to hold or terminate the green made on a second-by-second basis after that time phase.

At some point, most of the MARLIN intersections will fall into a co-ordinated, default pattern. But each will continue to observe and learn as daily or long-term volumes change, altering their timing accordingly.

The MARLIN system, which has been simulated on some 60 downtown Toronto intersections, would cost between $20,000 and $40,000 per location to install.

Abdulhai says the city could benefit with just 10 downtown initially.

But better enforcement of lane and intersection violations and the city’s retiming program can improve things in the immediate future, the city’s Buckley says.

Still, he says the city is exploring adaptive signal systems like MARLIN and could well be testing one or more over the next few years.

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