August 25, 2011
Smartphone App Could Help Drivers With Fuel Efficiency
MIT and Princeton University researchers have developed a system that uses a network of smartphones mounted on car dashboards that will help drivers obtain better fuel efficiency.
The system uses smartphones to collect information about traffic signals and tell drivers when slowing down could help them avoid waiting at lights.
Emmanouil Koukoumidis, a visiting researcher at MIT who led the project, said cars are responsible for 28 percent of the energy consumption and 32 percent of the carbon dioxide emissions in the U.S.
“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 said in a press release.
The system is intended to capitalize on a growing trend in which drivers install brackets on their dashboards so they can use their smartphone as a GPS navigator. The smartphone system relies on images taken by the devices' cameras.
According to Koukoumidis, the computing infrastructure that underlies the system could be adapted to a wide range of applications.
The researchers tested their SignalGuru device in Cambridge and Singapore because of how the traffic light systems work in those areas.
The system in Cambridge, where traffic lights are on fixed schedules, was able to predict when lights would change with an error of only two-thirds of a second.
In Singapore, where the duration of lights varies continuously according to fluctuations in traffic flow, SignalGuru's error increased to slightly more than a second.
“The good news for the U.S.,” Koukoumidis says, “is that most signals in the U.S. are dummy signals” – signals with fixed schedules.
He said that even an accuracy of two and half seconds “could very well help you avoid stopping at an intersection.”
The researchers modeled the effect of instructing drivers to accelerate in order to catch lights before they change, but “we think that this application is not a safe thing to have,” Koukoumidis said in a press release.
The test version developed by the researchers displayed the optical speed for avoiding a full stop at the next light. However, Koukoumidis said the commercial version would use audio prompts instead.
He envisions the system could also be used in conjunction with existing routing software.
“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,” Marco Gruteser, an associate professor of electrical and computer engineering in the Wireless information Network Laboratory at Rutgers University, said in a press release.
“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.”
Gruteser said one obstacle for the commercial system 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.”
Image 2: Where previous experimental traffic-light advisory systems used GPS data or data from traffic sensors, SignalGuru uses visual data from cellphone cameras. Graphic: Christine Daniloff
On the Net:
- Princeton University
- Read the Report (PDF)
- The LSP Group
- Computer Science and Artificial Intelligence Laboratory
- Department of Electrical Engineering and Computer Science