Parse Traffic Congestion Through Gadgets

How many losses due to traffic congestion in big cities? "Americans spend 4.2 billion hours on the highway and burn gasoline wasted 2.8 billion gallons or as much as U.S. $ 87 billion," it was written by a 2007 study.

Chairman of the Infrastructure Partnership and Knowledge Center, Harun al-Rashid, said the 2012 traffic congestion in Jakarta, causing losses of up to Rp. 12.8 trillion (or approx U.S. $ 1.333 billion). He predicted in 2020, the losses could reach Rp. 65 trillion (or approx U.S. $ 6.77 billion). This does not include the loss of time, fuel, and health costs.

Traffic congestion has become one of the diseases in the world's major cities. This condition will get worse because of the amount of the earth's population living in urban areas rose, to reach 5 billion people. Though relatively small increase road network.

Traffic congestion in the world's major cities. (Picture from: http://www.motortrend.com/)

Researchers from the Massachusetts Institute of Technology (MIT) conducted a study on strategies to overcome traffic congestion in urban areas using smart phone applications. The focus of the research carried out by analyzing the pattern of use of the road in the City of San Francisco Bay and Boston, USA.

They use the phone information of more than 1 million users for three weeks. Of this anonymous information, researchers can map where the driver concentrated on the main two cities. Based on the analysis, the researchers showed that certain areas in the city is the "gathering place" of the driver. Concentrations in some locations that causes major congestion.

"Only 1 percent canceling trips in the region can drastically reduce the travel time of other motorists," said Martha Gonzalez, a complex systems expert at the Massachusetts Institute of Technology last week.

Tracing driver sources in the Boston area via the road usage network. Red and yellow denote the most congested roads. (Picture from: http://www.livescience.com/)

In the Boston area, the center of the concentration of the riders in the area of ​​Massachusetts Everett, Marlborough, Lawrence, Lowell, and Waltham. According to Marta, with a 1 percent canceling a trip in that direction, traffic congestion will be reduced by 18 percent.

In the city of San Francisco, is hilly and located on the edge of the Pacific Ocean, central concentration of riders in Dublin, Hayward, San Jose, San Rafael, and part of San Ramon. Traffic congestion will be reduced by 14 percent if a trip to the region minus 1 percent.

According to Gonzalez, if we are able to detect and releasing congestion on arterial roads of the most severe coronary system functions as a whole will increase. She prescribed the city government to encourage motorists not to pile up in some areas.

For example, encouraging the use of public transportation, car-pooling, or provide flexible hours for employees to work from home. Mobile applications that connect people who use the same path to help them coordinate car-pooling.

The researchers do not need the full GPS information of all travel. Therefore, many people have a pattern of repeated trips. These data, said Gonzalez, enough to make statistical estimates were good, although not everyone uses the phone all the time. According to him, a good sample and analysis of long observation time, we can calculate the trend of the use of the road. Gonzalez explained that mobile phone-based research strategies could be implemented in other major cities in the world. *** [LIVESCIENCE | UNTUNG WIDYANTO | KORAN TEMPO 4095]

Traffic Prediction Sensor

IBM's Smarter Traveler traffic prediction 
tool. (Picture from: http://www.hellocotton.com/)

The Computer company IBM is colaborating with the California Department of Transportation (Caltrans) and the University of California, Berkeley, examined driving patterns on the highway. They use real-time data from sensors embedded in the road traffic to predict what happens in the near future.

This prediction is then combined with individual route profiles. According to John Day, program manager of IBM Smarter Traveler, this analytical engine that ingests large amounts of sensor data, and track historical trends of motor vehicle travel. Real-time data were then matched with the historical trend. "When I saw this pattern, we will know what will happen 20 minutes later, or 40 minutes later," said John Day.

Traffic news on television and radio had only to report traffic that has passed. They are, says John Day, do not tell how traffic conditions half an hour to come. Currently, devices that can predict traffic conditions newly installed in the San Francisco Bay. IBM is still developing this tool, including making use of the software to predict the fuel and other energy. *** [UWD | HELLOCOTTON | KORAN TEMPO 4095]

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