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Cellphone data 'may help pinpoint source of traffic congestion'

Washington, Fri, 21 Dec 2012 ANI

Washington, December 21 (ANI): In a new study, researchers have shown that the adoption of alternatives, like public transportation and carpooling to have fewer cars on the road and prevent traffic tie-ups, by a small percentage of people across a metropolitan area might not be very effective.

However, if the same number of people, but from a carefully selected segment of the driving population, chooses not to drive at rush hour, this could reduce congestion significantly.

The study by researchers at MIT, Central South University in China, the University of California at Berkeley and the Austrian Institute of Technology demonstrates that cancelling or delaying the trips of 1 percent of all drivers across a road network would reduce delays caused by congestion by only about 3 percent.

But cancelling the trips of 1 percent of drivers from carefully selected neighbourhoods would reduce the extra travel time for all other drivers in a metropolitan area by as much as 18 percent.

"This has an analogy in many other flows in networks," lead researcher Marta Gonzalez from MIT said.

"Being able to detect and then release the congestion in the most affected arteries improves the functioning of the entire coronary system," Gonzalez said.

The study, designed by Gonzalez and former MIT postdoc Pu Wang, now a professor at Central South University, is the first large-scale traffic study to track travel using anonymous cellphone data rather than survey data or information obtained from U.S. Census Bureau travel diaries.

Both of these are prone to error because of the time lag between gathering and releasing data and the reliance on self-reporting.

Gonzalez and Wang used three weeks of cellphone data to obtain information about anonymous drivers' routes and the estimated traffic volume and speed on those routes.

They inferred a driver's home neighbourhood from the regularity of the route travelled and from the locations of cell towers that handled calls made between 9 p.m. and 6 a.m.

They combined this with information about population densities and the location and capacity of roads in the networks of two metropolitan areas - Boston and San Francisco - to determine which neighbourhoods are the largest sources of drivers on each road segment, and which roads these drivers use to connect from home to highways and other major roadways.

In the Boston area, they found that cancelling 1 percent of trips by select drivers in the Massachusetts municipalities of Everett, Marlborough, Lawrence, Lowell and Waltham would cut all drivers' additional commuting time caused by traffic congestion by 18 percent.

In the San Francisco area, canceling trips by drivers from Dublin, Hayward, San Jose, San Rafael and parts of San Ramon would cut 14 percent from the travel time of other drivers.

"These percentages are averages based on a one-hour commute with additional minutes caused by congestion," Wang said.

"The drivers stuck in the roads with worst congestion would see the greatest percentage of time savings, because the selective strategy can more efficiently decrease the traffic flows in congested roads,' Wang said.

To validate the study's methodology, Alexandre Bayen, an associate professor of systems engineering at Berkeley, and graduate student Timothy Hunter compared Gonzalez and Wang's estimations of travel time based on cellphone data with their own data obtained from GPS sensors in taxis in the San Francisco area.

Using GPS data, Bayen and Hunter computed taxis' speed based on travel time from one location to another; from that speed of travel, they then determined congestion levels. Their findings agreed with those of Gonzalez and Wang.

Because the new methodology requires only three types of data - population density, topological information about a road network, and cellphone data - it can be used for almost any urban area.

"In many cities in the developing world, traffic congestion is a major problem and travel surveys don't exist," Gonzalez said.

"So the detailed methodology we developed for using cellphone data to accurately characterize road network use could help traffic managers control congestion and allow planners to create road networks that fit a population's needs," Gonzalez added.

The study has been published in the journal Scientific Reports. (ANI)

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