• Where previous experimental traffic-light advisory systems used GPS data or data from traffic sensors, SignalGuru uses visual data from cellphone cameras.

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Increasing fuel efficiency with a smartphone

A network of dashboard-mounted phones can collect data on traffic lights and tell drivers how to avoid inefficient stopping and starting.

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In July, at the Association for Computing Machinery’s MobiSys conference, researchers from MIT and Princeton University took the best-paper award for a system that uses a network of smartphones mounted on car dashboards to collect information about traffic signals and tell drivers when slowing down could help them avoid waiting at lights. By reducing the need to idle and accelerate from a standstill, the system saves gas: In tests conducted in Cambridge, Mass., it helped drivers cut fuel consumption by 20 percent.

Cars are responsible for 28 percent of the energy consumption and 32 percent of the carbon dioxide emissions in the United States, says Emmanouil Koukoumidis, a visiting researcher at MIT who led the project. “If you can save even a small percentage of that, then you can have a large effect on the energy that the U.S. consumes,” Koukoumidis says.

The system is intended to capitalize on a growing trend, in which drivers install brackets on their dashboards so that they can use their smartphone as a GPS navigator while driving. But unlike previous in-car cellphone applications, the new system, dubbed SignalGuru, relies on images captured by the phones’ cameras. According to Koukoumidis, the computing infrastructure that underlies the system could be adapted to a wide range of applications: The camera could, for instance, capture information about prices at different gas stations, about the locations and rates of progress of city buses, or about the availability of parking spaces in urban areas, all of which could be useful to commuters.

Fixed or flexible?

Koukoumidis is a student of Li-Shiuan Peh, an associate professor in the Department of Electrical Engineering and Computer Science who came to MIT from Princeton in fall 2009. Koukoumidis came with her, and together they launched the SignalGuru project as part of the Singapore-MIT Alliance for Research and Technology’s Future Urban Mobility program. Koukoumidis’s other thesis advisor, Princeton’s Margaret Martonosi, is the third author on the MobiSys paper.

In addition to testing SignalGuru in Cambridge, where traffic lights are on fixed schedules, the researchers also tested it in Singapore, where the duration of lights varies continuously according to fluctuations in traffic flow. In Cambridge, the system was able to predict when lights would change with an error of only two-thirds of a second. In suburban Singapore, the error increased to slightly more than a second, and at one particular light in densely populated central Singapore, it went up to more than two seconds. “The good news for the U.S.,” Koukoumidis says, “is that most signals in the U.S. are dummy signals” — signals with fixed schedules. But even an accuracy of two and half seconds, Koukoumidis says, “could very well help you avoid stopping at an intersection.” Moreover, he points out, the predictions for variable signals would improve as more cars were outfitted with the system, collecting more data.

Theory into practice

In addition to designing an application that instructs drivers when to slow down, the researchers also modeled the effect of instructing them to speed up to catch lights. But "we think that this application is not a safe thing to have," Koukoumidis says. The version of the application that the researchers used in their tests graphically displays the optimal speed for avoiding a full stop at the next light, but a commercial version, Koukoumidis says, would probably use audio prompts instead.

Koukoumidis envisions that the system could also be used in conjunction with existing routing software. Rather than recommending, for instance, that a car slow to a crawl to avoid a red light, it might suggest ducking down a side street.

“SignalGuru is a great example of how mobile phones can be used to offer new transportation services, and in particular services that had traditionally been thought to require vehicle-to-vehicle communication systems,” says Marco Gruteser, an associate professor of electrical and computer engineering in the Wireless information Network Laboratory at Rutgers University. “There is a much more infrastructure-oriented approach where transmitters are built into traffic lights and receivers are built into cars, so there’s a much higher technology investment needed.”

One obstacle to commercial deployment of the system, Gruteser says, could be “finding a way to get the participation numbers required for this type of crowd-sourcing solution. There’s a lot of people who have to use the system to provide fresh sensing data.” Additional traffic-related applications, of the type that Koukoumidis is investigating, could be one way to drive participation, Gruteser says, but they won’t emerge overnight. “The processing algorithms would be a little more complex,” Gruteser says.

Topics: Automobiles, iPhone, Android, smartphones, Networks, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and electronics, Green-light optimal-speed advisory, Traffic management


If this project can be modified further, it will contribute to alleviate those disgusting traffic jams.
See - http://www.youtube.com/watch?v=lwHfibl1AoI for town in England that did just that. And of course use of traffic islands and halt / yield signs instead of traffic lights that control flow in simple dynamic fashion. How many times have you stopped at a red light when no vehicles were coming in another direction?
Lots of road intersections in China has timer fixed to the traffic lights. Saves cell phone battery and makes sure even those without smart phones can see it. I guess we can synchronize the timer with the traffic signal generator so as to achieve even better accuracy. Another separate concern is that whether this approach will result in more people speeding through yellow lights, and increase the risk of accidents
Getting a short term rental company like Zipcar to adopt them would be a good way to get a significant start in adoption numbers. They have a built in interest in lowering their fuel costs. Same would be true for taxi companies and local delivery fleets (UPS, Fedex, etc.).
These gimmicks will only get you so far; a push toward alternative fuels and a real public transportation infrastructure for the US is what's needed. -JK
Eliminating illegally posted stop signs and traffic lights especially the ones that are not coordinated, unnecessary speed bumps, humps and roundabouts, 'neckdowns' and curb extensions and all the speed traps designed to generate revenue or to appease residents would be far more effective than than...
It is helpful in increasing fuel efficiency. Apart, from this it may increase accidents because users will use to drive more fast.
I work for the city of Eindhoven in The Netherlands. Can you tell more about the Signal Guru app? We are looking for an app that through 'critical mass' of bicycle riders in a certain range of the traffic light could give preference or extra green for them. It's similar as for public transport having preference at cross roads by transmitting a signal to a traffic light. If this App could suit us in any way, I'd like to hear from you. Kindest regards Henk Kok strategic advisor for the city of Eindhoven +31622464857
Strongly agree to the point.
Hi, I have been doing exactly this, by sight and judgment for some years with a view to reduce pollution, save fuel and it also saves on wear and tear of the brakes and gives me and the passengers a much smoother ride. It works quite well. At a guess, I get it right 80% of the time, but sometimes I get 'flashed' and hooted at and it is clearly annoying and bemusing for some other drivers. Perhaps a sign on the back of the car would help. I know it's anal and obsessive, but I now know the timings of all the lights on my frequent routes, although they do seem to change at different times of the day. It works worst when there is a long way to go to the lights and they have just gone red. This software would be really useful and save me alot of mental effort, so please can you send it to me ?
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