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The Battalion

The Student News Site of Texas A&M University - College Station

The Battalion

The Student News Site of Texas A&M University - College Station

The Battalion

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Gridlock science

It’s 5 p.m. It’s been a long day for students and employees, and now they are just trying to get home. Traffic, however, is at a standstill. Drivers get nearer to the bottleneck, yet discover that there is no car wreck, no construction — nothing to cause the slowdown at all. Sound familiar?
Texas A&M nuclear engineering professor Paul Nelson hopes to use his expertise in kinetic equations to end the frustration experienced during just such days of unexplained traffic delays.
Nelson uses kinetic equations in the classroom to describe how atomic particles interact with each other on a molecular level in a nuclear reactor. He has used these same formulas to create a model of how traffic flows in the real world.
“Vehicles move in response to their drivers,” Nelson said. “So, in kinetic equations, if we replace the atomic particles with individual drivers, then we can get a statistical description of the drivers and their responses to other drivers and vehicles.”
Nelson discussed his findings in a session, “Mathematical Models for Traffic Flow: Phantom Jams and Real Data,” at the annual meeting of the American Association for the Advancement of Science in Denver in February. Nelson’s research creates some interesting possibilities for the average motorist. A realistic traffic model would enable researchers to predict delays, allowing them to reccomend alternate routes for drivers. They could also use Nelson’s research to develop technological advances or suggest highway construction plans to make driving as efficient as possible.
To determine how reliable models such as these actually are, Nelson has singled out other kinetic models that attempt to describe traffic flow. Nelson said the Prigogine-Herman model, developed by Nobel Prize-winners Ilya Prigogine and Robert Herman, can replicate the flow of real traffic but cannot supply sufficiently realistic predictions for drivers to use in everyday driving.
“In stop-and-go traffic, for instance, the Prigogine-Herman model would predict that cars in stop mode were actually stopped,” Nelson said. “But we know that that’s not really the case — the cars usually just slow down before speeding up again.”
Other complicated models also fail the test known as Occam’s razor, said Nelson in an interview with Science News Online. Occam’s razor says that the simplest theory that explains an occurrence is the best theory. Nelson said complex models “clearly can be tuned to produce about any effect one wishes to produce,” and therefore may not explain traffic as much as one might think.
“Of course, we’ll never be able to make 100 percent accurate predictions because there are always unforeseen circumstances in traffic,” Nelson said. “But we can hope to be right more often than we’re wrong.”
A perfect answer may not be available for Nelson’s ongoing research at A&M and the efforts of his colleagues abroad, but their work does promise many improvements for kinetic models and, in effect, highways worldwide.
Hopefully one day soon, the term “rush hour traffic” will be all but forgotten, and commuters will enjoy as much freedom on their drive to work as they would a peaceful drive in the country.

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