A New Smart Technology will Help Cities Drastically Reduce their Traffic Congestion

A New Smart Technology will Help Cities Drastically Reduce their Traffic Congestion

Rev, brake, honk, rev, brake. The pattern seems familiar to most of us. In 2015, American commuters spent more than 8 billion hours in traffic. If a robotics professor at Carnegie Mellon University has his way, that number could shrink.

Meet Stephen Smith, who has outfitted Pittsburgh with traffic signals that use artificial intelligence to react to traffic conditions in real time. These smart lights reduce travel time by 25 percent, braking by 30 percent and idling by more than 40 percent.

It began in Smith’s research lab at Carnegie Mellon. About six years ago, a local philanthropist with seed money wanted the university to address transportation in the Pittsburgh area. In 2012, Smith’s team installed a network of nine signals across the city.

“We’re fortunate that we have a really progressive thinking administration in the city. We have a great working relationship with the public works department there. They’ve been really helpful,” Smith said. “To be honest, they were a little hesitant to let us try at first, but with the backing of local foundations, they decided to give it a try. And then once they saw it was working, they became much more of a partner in the situation. The local administration here is really keen on putting technology to use and trying to become a model city of the future.”

Based on the positive results of the pilot, Smith obtained funding to expand the network. The smart signals now guide traffic at a network of 50 intersections in the east end of Pittsburgh.

In 2015, the company Rapid Flow Technologies spun out of Carnegie Mellon. The company, which develops intelligent transportation technology, expects to install its Surtrac traffic light system in about 150 more intersections in the next three years, covering about a third of Pittsburgh.

Read more at Paste Magazine.

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Smart Cities Solving Parking and Driving Challenges

Smart cities and cars are getting even smarter as technological disruption continues to shake up the transportation industry. By 2021, more than 380 million connected cars are expected to be on the road, as automakers plan to connect the majority of the vehicles they sell, according to research from BI Intelligence. This connectivity is leading to new solutions for urban planning applications, data analysis and problem-solving.

A pilot smart signals program in Pittsburgh lead by Surtrac reduced travel time by 25 percent and cut idling time by more than 40 percent. In addition to reducing emissions from idling, the program could also lead to lower demand for on-street parking and road expansion. Pittsburgh is also a test area for Uber’s self-driving cars, and the intelligent traffic signals will communicate with the autonomous vehicles for fluid traffic through intersections.

The next step is to equip cars to talk to traffic signals. The Surtrac Pittsburgh test includes short-range radios at 24 intersections around the city. Radio-equipped cars are expected to be on the market soon, and after-market products like Lear’s could be fitted to existing vehicles.

By expanding use cases for connected cars through parking apps and vehicle-to-infrastructure communication, smart cities are setting a new precedent for automakers, civil planners and citizens in urban areas.

Read more from Samsung Business Insights

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He’s Helping Pittsburgher Drivers Get The Green Light

About six years ago, Stephen Smith was stopped at a traffic light in East Liberty, driving home from Carnegie Mellon University. The robotics professor had been working over a tricky problem — how to make urban traffic flow more efficiently. Computer simulations showed his proposed system worked, but he needed a place to test it amidst aggressive drivers, slow buses and errant pedestrians.

And then he saw it: At the traffic light, mounted on a pole, was a camera.

Smith, 63, had no experience as a traffic engineer — he had spent his career working on technologies for automated warehouses, manufacturers and other uses. But he had been pulled into the Traffic21 Institute at CMU, initially funded by the Hillman Foundation in 2009 to make Pittsburgh a hub for intelligent transportation. The Hillman grant helped to pay for 12 projects, including real-time bus-arrival tracking with the Port Authority of Allegheny County, a parking app and vehicle sensors to detect road conditions.

Developing the adaptive traffic lights Smith had in mind was one of the more complicated projects. Conventional traffic-light systems are pretty straightforward. An engineer does a short study to assess traffic flows, builds a system of traffic phases and puts it online. Unless a police officer assumes command at the corner, the system is locked for average conditions.

But such systems can fall wildly short in non-average traffic, so Smith and his team installed computers that were capable of assessing traffic and adjusting on the fly at nine East Liberty intersections. If cameras saw a backlog of cars, computers could allow a green light to linger for a few extra seconds; if no one was turning left, computers skipped the left-arrow phase entirely.

The system helped reduce travel time through those intersections by an average of 25 percent, according to studies conducted by Traffic21, which turned the system on and off at different times of day.

“It’s not because you’re driving faster but because you’re stopping less and not stopping for as long,” Smith says. The system now includes 50 lights, running from Penn Avenue at Bakery Square into Oakland on Baum Boulevard.

Smith subsequently spun off a company, Rapid Flow Technologies, from CMU and licensed the technology he and his research group created, dubbed “Surtrac.” The company is receiving part of a recent $10.9 million federal grant to add another 150 lights to the system, including some Downtown.

“We’re trying to see what we can get out of the tech in the short term,” Smith says. Eventually, he envisons consumer vehicles outfitted with radios to transmit their locations, as well as potential routes, to traffic lights. Armed with both, an adaptive traffic system would make the flow even more efficient, he says.

With the rise of automated vehicles, Smith thinks the need for smart traffic systems will only grow. “A lot of people claim either rightly or wrongly that we will see less vehicles on the road. I’m not so sure I believe that; there will be less need for parking. But congestion is not going to go away — more and more people are moving to the city.”

See more at Pittsburgh Magazine.

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Gridlock Guy: Technology may soon catch up with traffic signals

When I was 12 years old and in the car with my mom stuck at a red light, we had to wait for the light to turn green even though there wasn’t any traffic coming the other direction. Now, when I’m stuck at a red light waiting for the light to turn green even though there isn’t any traffic coming in the other direction I still have to wait for the light to turn green.

My point is, even though technology has changed just about every aspect of our lives, there has been very little in the way of advances when it comes to traffic signals. Thankfully, that might all change soon.

There is a company called Rapid Flow Technologies developing a system called Surtrac than could change traffic signals forever. The system uses artificial intelligence to help improve traffic flow. According to the company “Surtrac optimizes the performance of signals for the traffic that is actually on the road, improving traffic flow for both urban grids and corridors and leading to less waiting, reduced congestion, shorter trips, less pollution, and happier drivers.”

Here in Atlanta, most traffic signals are timed with data on traffic flow that could be days, months or even years old. The Surtac system uses real time that improves traffic flow immediately.

More from the Atlanta Journal-Constitution.

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Pittsburgh’s AI Traffic Signals Will Make Driving Less Boring

Idling in rush-hour traffic can be mind numbing. It also carries other costs. Traffic congestion costs the U.S. economy $121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide emissions, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added.

The big reason is that today’s traffic signals are dumb. Smith is developing smart artificial-intelligence-fueled traffic signals that adapt to changing traffic conditions on the fly. His startup Surtrac is commercializing the technology.

In pilot tests in Pittsburgh, the smart traffic management system has gotten impressive results. It reduced travel time by 25 percent and idling time by over 40 percent. That means less time spent staring out the windshield and more time working, being with your family, or doing anything else. I’m a Pittsburgh resident who has witnessed the city’s rapidly-evolving urban landscape. And I can attest to the mostly frustration-free driving that has resulted from this system despite the city’s growing population.

Read more at IEEE Spectrum.


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Five surprising ways AI could be a part of our lives by 2030

Artificial intelligence (AI) has gradually become an integral part of modern life, from Siri and Spotify’s personalized features on our phones to automatic fraud alerts from our banks whenever a transaction appears suspicious. Defined simply, a computer with AI is able to respond to its environment by learning on its own—without humans providing specific instructions. A new report from Stanford University in Palo Alto, California, outlines how AI could become more integrated into people’s lives by 2030, and recommends how best to regulate it and make sure its benefits are shared equally.

Here are five examples—some from this report—of AI technology that could become a part of our lives by 2030.

Smart traffic lights

Many people know the frustration of waiting at red lights while no traffic is moving through the intersection. Modern traffic lights typically run on a fixed schedule, with police officers occasionally intervening during special events and emergencies. So-called smart traffic lights are already able to use cameras and road sensors to adjust their timing minute by minute to handle traffic and pedestrians faster and more safely. By collecting data and making decisions independent of human guidance, such lights harness AI to adapt to the randomness of traffic. Easing traffic congestion in this way would not simply reduce commuting stress, but it would also cut down on air pollution from idling cars. Carnegie Mellon University is already testing smart traffic lights in Pittsburgh, Pennsylvania, which are also being tested in Los Angeles, California, and Bellevue, Washington. By 2030, they will likely be on your corner.

Read more from Science.

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Pittsburgh’s Smart City proposal combines data, energy and transportation

Pittsburgh’s application for the $50 million Smart City Challenge grant calls for a series of transportation spines, traffic signals that give priority to transit and freight vehicles, and an “electric avenue” between Downtown and Hazelwood for driverless vehicles charged at solar power stations.

A key element of the Pittsburgh proposal would be a ”smart spine system” on six streets that feed into the Golden Triangle: Penn, Liberty, Fifth, Forbes and Second avenues, and Bigelow Boulevard.

The system would use the Western Pennsylvania Regional Data Center, a collaborative led by Pittsburgh and Allegheny County and operated by the University of Pittsburgh, to collect location data from various sources along those spines. The sources would include personal, public transit, government and freight-hauling vehicles; street and traffic lights; and social media.

That information would be used to monitor traffic and control traffic lights on those streets, a much larger version of the Surtrac signal control system developed by Carnegie Mellon University and used in East Liberty and Larimer. As part of the system, traffic lights would use sensors to identify transit and freight vehicles and allow them to move through the signals quicker.

That eventually would be expanded throughout the city to all traffic signals.

Read more from the Pittsburgh Post-Gazette.

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Emergence as Regional Tech Hub Reflected in Pittsburgh’s Smart City Challenge Bid

Pittsburgh, meanwhile, has strong existing ties with local universities when it comes to transportation. At Carnegie Mellon, researchers affiliated with the Traffic21 Institute, and an initiative known as Metro21, work on technology that has already been tested in the city.

One of the proposals in Pittsburgh’s Smart City Challenge application calls for wider deployment of a traffic signal control system that came out of Traffic21, known as Surtrac. It uses machine learning algorithms to optimize when traffic lights change to red or green and has already been installed at a number of intersections in Pittsburgh.

At intersections where the system is in place, vehicle wait times have gone down by 40 percent and emissions have declined by 21 percent, according to Stan Caldwell, executive director at Traffic21. Wider deployment could lead to further improvements, Caldwell noted.

Read more from Route 50.

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Green Lights All the Way

It’s green lights all the way baby in parts of Pittsburgh due to the implementation of a decentralized traffic system overseen by a Carnegie Mellon robotics professor.

The adaptive traffic control signal system from Surtrac uses a combination of traffic theory and artificial intelligence to follow traffic flow on a real-time basis.

The signals at intersections are controlled by a camera and computer system that watches the traffic coming from every direction, said Stephen F. Smith, research professor and director of the Intelligent Coordination and Logistics Laboratory in the Robotics Institute at Carnegie Mellon.

“It sets a phase system for green lights, and sends the information to other intersections,” said Smith, who recently presented his findings at the 9th University Transportation Center Spotlight Conference in Washington, D.C. organized by the Transportation Research Board.

The system has been installed at 50 intersections in Pittsburgh’s East End neighborhood. Since it began in 2012, the project has cut travel time by 24 percent and waiting time by 42 percent, according to office of the Pittsburgh mayor.

That efficiency has led to a 21 percent reduction in emissions, said Smith who leads Rapid Flow Technologies, a Carnegie Mellon spin off. The university owns a piece of Rapid Flow as it seeks to commercialize Surtrac.

Read more at Driverless Transportation

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Pittsburgh’s Smart Traffic Lights are Taking a Bite Out of Vehicle Pollution

Smith is only half joking when he insists this practice of “squeezing one guy through” helps traffic flow better. But traffic flow is something he knows a lot about. A professor in Carnegie Mellon University’s robotics department, he’s the guy behind the roll-out of an experimental adaptive traffic signal system meant to heal traffic congestion in the city’s busy East End.

“It operates totally decentralized, so each intersection watches the traffic that’s coming in all directions,” Smith says. “And then in real time, it builds a plan so that all the vehicles it sees move through the intersection in the most efficient way possible.”

That means a computer algorithm essentially figures out how long to leave the green lights green and the red lights red in order to maximize traffic flow in all directions. Steve’s lights are also all talking to each other, so neighboring signals can coordinate their pattern of green and red to keep the flow going for blocks at at time. As proof, Steve drives through the East Liberty test zone near the intersection of Penn Avenue and Centre Ave and makes it through five lights in a row. Once outside the reach of his smart lights— right on cue—his river of green abruptly turns red.

Hear more from the Allegheny Front

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