Tingting Huang wins top student paper in ITE Midwest District competition

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June 21, 2017
Photo shows Tingting being given a paper certificate
Tingting Huang, left receives the Best Paper award from Rebecca Szymkowski, President of ITE Midwest District

Big data led to some big-time recognition for Tingting Huang, a third-year PhD student who works at InTrans in the Traffic Operations Laboratory.

On June 19, Huang was awarded the District Student Paper Award at the the Midwestern District of the Institute of Transportation Engineers (ITE) annual conference. Her paper will be sent to the international ITE competition where she will compete against the best paper winners from the nine other ITE districts.

Huang, who is a member of the Transportation Student Association (TSA) at Iowa State, first won Best Student Paper in the Missouri Valley Section of the ITE in April. She then advanced to the Midwest District competition where she faced competitors from Arkansas, Iowa, Kansas, Missouri, Nebraska, Oklahoma, Illinois, Wisconsin, and the North Central area.

In her research, Huang wants to use data to make the roads safer for motorists and road construction workers. Her paper, titled “Evaluating the Impacts of Work Zone Speed Limits Using Large-Scale Sensor Data,” examines measures taken to reduce traffic speeds in work zones by analyzing massive amounts of data collected by Iowa DOT sensors.

“The Iowa DOT has deployed many sensors to monitor traffic conditions in work zone areas,” said Huang. “I think it’s is important to know how different measures that have been taken to reduce speeds in work zones impact the traffic through those zones.” Huang says her data analysis can be used to help work zone managers make better decisions to keep motorists and worker safe.

Huang said she appreciates the help of her faculty advisers, Anuj Sharma and Peter Savolainen, and her colleagues in the TSA. Huang said her participation in TSA has given her great opportunities to gather with other students interested in transportation, share research, listen to experts in the field, and more.

In the future, Huang hopes to continue using big data techniques to address other traffic mobility and safety issues.

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