Impact of COVID-19 on Public Transit Accessibility and Ridership
April 2023·
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Michael Wilbur
Afiya Ayman
Amutheezan Sivagnanam
Anna Ouyang
Vincent Poon
Riyan Kabir
Abhiram Vadali
Philip Pugliese
Dan Freudberg
Aron Laszka
Abhishek Dubey
Abstract
COVID-19 has radically transformed urban travel behavior throughout the world. Agencies have had to provide adequate service while navigating a rapidly changing environment with reduced revenue. As COVID-19-related restrictions are lifted, transit agencies are concerned about their ability to adapt to changes in ridership behavior and public transit usage. To aid their becoming more adaptive to sudden or persistent shifts in ridership, we addressed three questions: To what degree has COVID-19 affected fixed-line public transit ridership and what is the relationship between reduced demand and -vehicle trips? How has COVID-19 changed ridership patterns and are they expected to persist after restrictions are lifted? Are there disparities in ridership changes across socioeconomic groups and mobility-impaired riders? Focusing on Nashville and Chattanooga, TN, ridership demand and vehicle trips were compared with anonymized mobile location data to study the relationship between mobility patterns and transit usage. Correlation analysis and multiple linear regression were used to investigate the relationship between socioeconomic indicators and changes in transit ridership, and an analysis of changes in paratransit demand before and during COVID-19. Ridership initially dropped by 66% and 65% over the first month of the pandemic for Nashville and Chattanooga, respectively. Cellular mobility patterns in Chattanooga indicated that foot traffic recovered to a greater degree than transit ridership between mid-April and the last week in June, 2020. Education-level had a statistically significant impact on changes in fixed-line bus transit, and the distribution of changes in demand for paratransit services were similar to those of fixed-line bus transit.
Type
Venue
Transportation Research Record, 2677(4), 531–546
Authors

Ph.D. 2025
Afiya Ayman joined the Applied Artificial Intelligence Lab as a Ph.D. student in January 2019. Her research interest
is in contemporary computational sciences, including and not limited to Data Science, Machine Learning, and Cyber
Security. She earned her bachelor’s degree in Computer Science & Engineering from Chittagong University of
Engineering & Technology, Bangladesh. Currently, her research focuses on the application of neural networks and
machine learning to restructure the operational planning of a regional transportation authority to be more
energy-efficient.

Ph.D. 2025
Amutheezan joined the Applied Artificial Intelligence Lab as a Ph.D. student in fall 2019. His research interest is
in Machine Learning and Data Science. Previously, he graduated with a Bachelors’s Degree in Computer Science and
Engineering from the University of Moratuwa, Sri Lanka in 2017. He worked as an intern at WSO2 Lanka (PVT) Ltd., as
part of the Data Analytics Team in 2016. He also worked as a software engineer in MillenniumIT Software PVT Ltd. from
2018 to 2019. He has previously worked on a machine learning project on semi-supervised based sentiment analysis of
microblogging platforms and on a data analytics project on monitoring flows of HL7 messages. Currently, his research
work focuses on optimizing bus-route scheduling and minimizing energy costs.

Associate Professor
Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.