手机信息有助精确分析交通瘫痪的源头

In most cities, traffic growth has outpaced road capacity, leading to increased congestion¹（拥挤）, particularly during the morning and evening commutes². In 2007, congestion on U.S. roads was responsible for 4.2 billion hours of additional travel time, as well as 2.8 billion gallons of fuel consumption and an accompanying increase in air pollution. One way to prevent traffic tie-ups is to have fewer cars on the road by encouraging alternatives such as public transportation, carpooling（合伙用车）, flex³ time（弹性时间） and working from home. But a new study -- by researchers at MIT, Central South University in China, the University of California at Berkeley and the Austrian Institute of Technology -- incorporates data from drivers' cellphones to show that the adoption⁴ of these alternatives by a small percentage of people across a metropolitan⁵ 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, published in the Dec. 20 issue of the journal Scientific Reports, demonstrates that canceling 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 canceling the trips of 1 percent of drivers from carefully selected neighborhoods 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," says lead research Marta González, the Gilbert W. Winslow Career Development Assistant Professor in MIT's Department of Civil and Environmental Engineering. "Being able to detect and then release the congestion in the most affected⁶ arteries⁷ improves the functioning of the entire coronary system."

 

The study, designed by González and former MIT postdoc Pu Wang, now a professor at Central South University, is the first large-scale traffic study to track travel using anonymous⁸ cellphone data rather than survey data or information obtained from U.S. Census⁹ Bureau travel diaries. Both of these are prone¹⁰ to error because of the time lag between gathering¹¹ and releasing data and the reliance on self-reporting.

 

González 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 neighborhood from the regularity¹² of the route traveled 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 densities¹³ and the location and capacity of roads in the networks of two metropolitan areas -- Boston and San Francisco -- to determine which neighborhoods 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.

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