logo
Loading...
Resilience and recovery of public transport use during COVID-19

Transportation

Resilience and recovery of public transport use during COVID-19

J. Wang, J. Huang, et al.

Explore how Kunming's public transport system navigated the challenges of the COVID-19 pandemic in this insightful study by Jiaoe Wang, Jie Huang, Haoran Yang, and David Levinson. Discover the resilience displayed by commuters and the varying travel behaviors exhibited by different age groups during unprecedented times.... show more
Abstract
To better understand how public transport use varied during the first year of COVID-19, we define and measure travel behavior resilience. With trip records between November 2019 and September 2020 in Kunming, China, we identify people who relied on traveling by subway both before and after the first pandemic wave. We investigate whether and how travelers recover to their pre-pandemic mobility level. We find that public transport use recovered slowly, as urban mobility is a result of urban functionality, transport supply, social context, and inter-personal differences. In general, urban mobility represents a strengthened revisiting tendency during COVID-19, as individual's trips occur within a more limited space. We confirm that travel behavior resilience differs by groups. Commuters recover travel frequency and length, while older people decrease frequency but retain activity space. The study suggests that policymakers take group heterogeneity and travel behavior resilience into account for transport management and city restoration.
Publisher
npj Urban Sustainability
Published On
Jun 29, 2022
Authors
Jiaoe Wang, Jie Huang, Haoran Yang, David Levinson
Tags
public transport
COVID-19
travel behavior
resilience
urban functionality
commuters
activity space
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 22+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny