Cluster analysis of daily cycling flow profiles during COVID-19 lockdown in the UK

Matthew Burke, Dilum Dissanayake*, Margaret Bell

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Downloads (Pure)

Abstract

The COVID-19 pandemic and resulting government-enforced lockdown affected the travel behavior and lives of people worldwide. In this research, hierarchical cluster analysis (HCA) is used to quantify the impact on daily flow profiles of cyclists due to the public's response to different levels of restrictions during a 6-month period of the COVID-19 pandemic in 2020. An inductive loop network in Tyne and Wear, the UK provided cycle flow data from 25 sites. A paired sample t-Test was carried out between the "Pre-COVID-19"baseline year and 2020 to determine how cycling volumes changed at each site. The HCA was then performed on the diurnal hourly flow profiles to observe how they changed within the same time period. Finally, the relationship between diurnal flow profile and volume was assessed. Overall cycling volume in the study area increased by 38% during the lockdown. The highest increases were found at coastal sites, with more modest increases in suburban areas and reduced volumes at city center locations. The HCA of the diurnal flow profiles revealed that locations associated with noncommuting-shaped flows witnessed the largest increases while commuting profiles saw a decrease. As lockdown restrictions eased, flow profiles began to revert back to the prepandemic norm but never fully returned to prepandemic levels. The adoption of working from home postpandemic will change commuting behavior. The conclusions drawn from this study suggest consideration of noncommuting trips should be made when planning the design and location of future cycling schemes, and the HCA of flow profiles can assist in this decision-making process as a method to quantify changes in daily flow profiles of cycling.

Original languageEnglish
Article number4217431
Number of pages16
JournalJournal of Advanced Transportation
Volume2022
DOIs
Publication statusPublished - 19 May 2022

Bibliographical note

Publisher Copyright:
© 2022 Matthew Burke et al.

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management

Fingerprint

Dive into the research topics of 'Cluster analysis of daily cycling flow profiles during COVID-19 lockdown in the UK'. Together they form a unique fingerprint.

Cite this