[Editors] MIT: Mobile car sensor cuts commute times

[Jen Hirsch]

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MIT’s CarTel aims to reduce commute times, detect engine woes
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For Immediate Release
WEDNESDAY, OCT. 8, 2008

Contact: Jen Hirsch, MIT News Office
E: jfhirsch at mit.edu, T: 617-253-1682

Graphic Available


Dozens of cars in the Boston area are testing the latest generation  
of an MIT mobile-sensor network for traffic analysis that could help  
drivers cut their commuting time, alert them to potential engine  
problems and more.

In the CarTel project, Professor Hari Balakrishnan and Associate  
Professor Samuel Madden of MIT’s Department of Electrical Engineering  
and Computer Science use automobiles to monitor their environment by  
sending data from an onboard computer — which is about the size of a  
cell phone — to a web server where the data can be visualized and  
browsed. They do so via pre-existing WiFi networks passed during a trip.

The resulting data, accessible from the web or a cell phone, not only  
helps a driver track conditions specific to their own car, but when  
combined with everyone else’s can indicate historical and real-time  
traffic conditions at different times of the day. “Everybody’s data  
is contributing to collective views of what congestion looks like,”  
Madden said.

“Our goal,” Balakrishnan said, “is to make the data behind CarTel  
available to help you plan and organize your commute and drives. We  
want to minimize the amount of time spent in your car.”

For example, the current system, deployed since January on 50 Boston- 
area cars — including 40 taxis — tracks traffic by monitoring each  
vehicle’s speed at different points during a trip. Unlike other route- 
planning systems, “CarTel understands where traffic delays are and  
recommends routes to avoid them,” Madden said.

The system has already cut Balakrishnan’s commute to MIT by 25  
percent. It recommended a new route that, although a few miles longer  
than the approach suggested by some mapping web sites, is  
considerably faster in practice.

CarTel is also linked to a vehicle’s onboard diagnostics system  
(available in all cars sold since 1996), so a driver can check  
various parameters key to maintenance and be alerted to potential  
problems.

There are two principal research efforts behind the system. First,  
Balakrishnan, Madden and Jacob Eriksson (now at the University of  
Illinois, Chicago) developed a way to connect to WiFi networks that  
is 35 times faster than other systems. “It can take about 15 seconds  
to connect using a regular system, so in a car you are already past  
the WiFi location by the time you get the signal,” Madden explained.  
QuickWiFi can connect in 360 milliseconds. “It’s the difference  
between whether you can use WiFi with a car or not.”

The majority of the work, however, is focused on managing the huge  
amounts of data key to the system. Depending on the sensors in use,  
CarTel can receive more than 600 data points a second. So the team  
has developed two generations of software “to synthesize all that  
data into interesting uses,” Madden said.

One such use is new algorithms for traffic-aware routing, or  
obtaining directions between two locations that take historical and  
current traffic conditions into account. Balakrishnan and Madden have  
developed these algorithms with graduate student Sejoon Lim and  
Professor Daniela Rus, both of the Department of Electrical  
Engineering and Computer Science.

“CarTel makes it easy to collect, process, deliver and visualize data  
from a collection of remote, mobile and intermittently connected  
nodes,” the researchers concluded in one of several technical  
articles and conference presentations on the work. Most recently,  
they described the research at the Association for Computing  
Machinery’s Conference on Mobile Computing and Networking (MobiCom)  
in September 2008.

This work is funded by the National Science Foundation and the T- 
Party Project, a joint research program between MIT and Quanta  
Computer Inc. For more information go to cartel.csail.mit.edu.

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By Elizabeth Thomson, MIT News Office