Point A to Point B
Like many urban commuters, Assistant Professor Ying Song is not a fan of traffic.
Traffic was especially bad in Song’s hometown, Wuhan, China. “It would take me an hour on the bus to cross a bridge,” Song said. “Sometimes you could get off the bus and walk faster.”
Faced with an all-too-familiar problem, Song was inspired to do something. “The horrible traffic in Wuhan motivated me to study transportation,” Song said. “There might be some solution to solve this.”
That began Song’s career studying geographic information science (GIS), transportation geography, and spatio-temporal modeling. After receiving her PhD in geography from Ohio State University, Song started as an assistant professor at the University of Minnesota. Her research focuses on urban accessibility, sustainable transportation, and human mobility.
The Perfect City
The U of M provides the perfect setting to study these issues, Song said. “I was attracted to one of the top research universities and to the rich resources here to conduct research.”
In particular, Song points to the University’s vast amount of data and potential collaborations available for researchers, including the Center for Transportation Studies, the Minnesota Population Center, the Center for Urban and Regional Affairs, and more.
The city of Minneapolis itself is also advantageous. With bike-friendly infrastructure, steady urban development, and a growing transportation system, Song has a lot to work with.
She recently partnered with a municipality transit system to start a pilot program testing new methods to improve the estimations of bus arrival time. Song is using data to analyze traffic patterns, investigate traffic delays, and create estimation models for transit operations.
Better Data = Better Transit
Rather than using broad approximations of the population as a whole, Song analyzes movements of individual commuters and vehicles, receiving anonymous data from navigation companies and transportation authorities.
This individualized data is important considering the variable nature of human movement. Song explained personal mobility with a hypothetical example. “If I have a meeting with you right now, that’s some sort of fixed schedule that shapes my daily activities,” Song said. “I can’t go and grab a cup of coffee in the middle of a meeting.”
Songs’ research allows for in-depth analysis and more accurate estimate of mobility accounting for individuals’ daily schedules.
On a larger scale, Song’s research provides insight on rider’s habits, traffic flow, and transit use, helping policymakers decide “whether they should provide more frequent services or whether there should be more business opportunities around certain areas,” Song said.
Song’s research helps public transit incorporate traffic situations, commuter delays, and real-time vehicle locations into their service design and management. In turn, transit systems can provide better time estimates to riders through the apps—information that encourages people to use public transit.
Moving Toward Progress
Heading into her third year at the U, Professor Song remains committed to fostering a more efficient and sustainable transportation network.
With the Twin Cities at her disposal, rich data at her fingertips, and the U’s resources at her back, Song has continued exploring the patterns of traffic flow, the mobility of commuters, and the efficiency of our public transportation system.
Although Song appreciates the academic aspects of her work, she also values the real world impact. Using her data, MetroTransit can evaluate its overall system performance, improve its efficiency, and gain more riders.
It all comes back to her original concern: getting from point A to point B better.
“It’s not just looking at moving people quicker, faster, and further,” Song said. “Rather, it's about helping [people] reach their destination easier.”