CAMDEN – Be it Beijing, Barcelona, or Burlington, anyone who drives the same commute each day knows plenty about when and where traffic strikes. A global concern that robs drivers of 4.2 billion hours each year, traffic can damage cars, the environment, and psyches, but has been difficult to measure and manage comprehensively. At Rutgers–Camden, an applied mathematician is working with colleagues the world over to implement innovative algorithms and models for a future with less stressful roadways.
Benedetto Piccoli, the Joseph and Loretta Lopez Chair in Mathematics at Rutgers University—Camden, has been studying traffic patterns for nearly a decade. His original theories have been applied by engineers from Berkeley, California to Rome, Italy and have resulted in applications poised to improve vehicular traffic through cell-phone technology and in-car tracking devices.
"Researchers have long investigated mathematical models for vehicular traffic," notes Piccoli, a senior research fellow in the Rutgers–Camden Ph.D. program in computational and integrative biology. "But they were studying a single road, that's all existing theories were allowing. The theory I worked with colleagues to develop deals with complex networks including cities' roads and highway systems."
Since the beginning of the 20th century, researchers have been developing models to better understand the implications of car traffic. One pivotal model in the 1950s used the equations describing water flow to depict traffic flow, leading to new discoveries of macroscopic fluid-dynamic models, like Piccoli's. While some methods include microscopic approaches, which take into account each single car, the model Piccoli developed describes more complex networks. This discovery has led to dozens of scholarly articles, one book – Traffic Flow on Networks – and two major applications.
In 2008, Mobile Millennium, a UC, Berkeley and Nokia research project used the GPS in cell phones to collect traffic data and communicate with users instantaneously for a year. Piccoli collaborated with lead engineer Alex Bayen to implement algorithms and models to process the extreme amount of data collected in the project that garnered national media attention. With the Italian company Octo Telematics, Piccoli and colleagues were able to forecast traffic nearly an hour and a half before it occurred based on data collected from sensors installed within vehicles.
"Advances in 'infomobility' allow us to get more precise data to better predict traffic," says Piccoli. "We've come a long way from stationary cameras and hovering helicopters." The knowledge garnered could impact how roads are designed, where toll booths are located, and how road construction is performed, all making life easier on drivers.
Piccoli's latest mathematical model addresses moving bottlenecks. Developed with colleagues Corrado Lattanzio and Amelio Maurizi, the research was published recently in SIAM Journal on Mathematical Analysis and was the most downloaded article on epubs
So what will the future hold for traffic reports? The Rutgers–Camden scholar says how the market digests his research is hardly predictable, but in all likelihood the consumer is sure to benefit.
"There are so many application possibilities, like better estimates for traffic modeling and a better optimization of paths for single drivers," offers Piccoli. "That's why I like applied mathematics, I get to build up the theories in my mind and then see them play out in the real world."
Piccoli joined the Rutgers–Camden faculty in 2009, as the school's first endowed chair. He has served as the research director of the Istituto per le Applicazioni del Calcolo in Rome; has taught with distinction at the University of Salerno and the University of Rome; and is the founding editor of Networks and Heterogeneous Media. He earned his Laurea degree in mathematics from the University of Padua and a Ph.D. in mathematics from Scuola Internazionale Superiore di Studi Avanzati. He currently resides in Cherry Hill.
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