Can Smartphones Increase Fuel Efficiency?

Posted on September 6, 2011 by LCT Magazine

A research team from MIT and Princeton University, led by Emmanouil Koukoumidis, has created a system that uses dashboard-mounted smartphones to collect information about traffic signals and tell drivers when slowing down could help them avoid waiting at lights. In tests conducted in Cambridge, Mass., the system helped drivers cut fuel consumption by 20% because it reduced to the need to idle at a red light and accelerate from a standstill.
                               

 

The system, dubbed SignalGuru, not only predicts the amount of time (in seconds) until an oncoming light will turn green or red, it also suggests the optimal speed for catching a light (see screenshot above). This may mean driving at a steady speed to cruise through an intersection before a light turns red, or slowing down before reaching an intersection to allow time for the light to turn green. Both options allow for more efficient driving than the usual stop-and-start. On average, SignalGuru comes within 0.66 seconds for pre-timed[1] traffic signals and within 2.45 seconds for traffic-adaptive[2] traffic signals.

 
“The good news for the U.S.,” Koukoumidis said, “is that most signals in the U.S. are dummy signals” — signals with fixed schedules. But even an accuracy of two-and-a-half seconds could help you avoid stopping at an intersection. The predictions for variable signals would improve as more cars were outfitted with the system and collected more data.
 
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 probably would use audio prompts instead, Koukoumidis said. Koukoumidis envisions that the system also could be used in conjunction with existing routing software. Rather than recommending that a car slows down to avoid a red light, it might suggest ducking down a side street.
 
SignalGuru relies on images captured by the smartphones’ cameras. The system’s computing infrastructure could be adapted to a wide range of applications, Koukoumidis said. For example, the camera could capture information about prices at different gas stations or the availability of parking spaces in urban areas.
 
While this technology is still in its initial development phases, it could complement existing fuel-efficiency tech to help chauffeurs practice more efficient driving and save on fuel costs.
 
Source: MIT News Office
-- Michael Campos, LCT assistant editor

 1. Traffic lights on a fixed schedule.
 2. Traffic lights whose duration varies continuously according to fluctuations in traffic flow.
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