March 19, 2018—Transportation agencies need travel behavior data to plan changes to their networks, systems, and policies. They’ll soon be able to purchase a new smartphone application called Daynamica, developed and patented by a University of Minnesota research team, to collect that important information more easily and for less cost than traditional methods.
The researchers, led by Humphrey School Associate Professor Yingling Fan, are in the final stages of creating a startup company and a licensing agreement with the University to sell Daynamica and its services.
This is the first patent and first startup company based on research completed at the Humphrey School, according to Associate Dean Carissa Slotterback.
“The work of Dr. Fan and her colleagues is a perfect example of the opportunities to use research to create products and outcomes that support practitioners in building healthy communities,” Slotterback says. “Her work has also connected to classes, creating opportunities for students to work at the forefront of transportation data and technology.”
Fan says Daynamica is a more efficient way to collect and process detailed data on how people get from place to place—driving or walking, biking or taking transit. It combines smartphone GPS sensing with advanced statistical and machine-learning techniques to automatically detect, identify, and summarize attributes of daily activity and travel periods. The app also allows users to view and add notes to the information at their convenience.
Fan says traditional travel survey methods like paper diaries are impractical, and GPS sensing tools can’t collect key information such as the purpose of a given trip, the traveler’s experience, and whether people are traveling alone or with companions.
“All of these factors are critical for understanding people’s travel choices,” Fan says. “Daynamica gives us the best of both worlds: It captures many more dimensions of travel behavior data than either GPS sensing or travel surveys can do alone.”
Daynamica places a much lower burden on users to recall and record their activities compared with traditional surveys, which means the data is more accurate and detailed. That ease of use could also allow agencies to study longer periods of time.
“Many traditional surveys track only a single day,” Fan says. “It would be better to collect a whole week of data to see how travel varies between weekdays and weekends. We could also look at seasonal variations and other factors. The more data, the better.”
Unlike other apps, Daynamica hosts both the data obtained from sensors and the data entered by users in a single device, and the two data sources interact with each other in real time. This in turn allows for data calibration and processing refinements over time.
“The algorithm learns from past mistakes,” Fan explains. “As it gets smarter, users need to make fewer corrections. After about a week of use, most data collection is automated. It learns what your location is—home, job, day care, or grocery store, for example—and remembers it.”
Daynamica offers several other advantages, Fan says. It’s easier to distribute and manage than other technologies because it doesn’t require an additional device; respondents can simply download the app and run it on their smartphones. In addition, Daynamica collects data in a way that reduces the need for processing, she says, which saves time and expense for the agencies using it.
Fan, who is the CEO of the new Daynamica, Inc., says the app will be marketed to businesses and government agencies interested in understanding and shaping transportation patterns, and to individuals interested in understanding and changing their own behavior for better economic, environmental, and health outcomes.
Daynamica was developed by a multidisciplinary team including Fan, Assistant Professor Julian Wolfson of the School of Public Health, Professor Gediminas Adomavicius of the Carlson School of Management, and computer science students Yash Khandelwal and Jie Kang.
Daynamica expands on the previous SmarTrAC app developed by the team under contract with the Volpe Center at the U.S. Department of Transportation in support of the Intelligent Transportation Systems Joint Program Office. Funding was also provided by the Center for Transportation Studies.