Cluster Analysis of Daily Cycling Flow Profiles during COVID-19 Lockdown in the UK

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.

WITHDRAWN: Evaluation of Different Phases of Covid-19 Pandemic using by Hybrid Approach Modeling

“…To determine how the time of day and the places where people cycled changed during the lockdown and as gradually as the restrictions were released, another research focuses on data clustering of daily ows. The hierarchical cluster analysis (HCA) technique was used since the cycle ow data were regarded as a continuous variable [19].…”

Two-Step Cluster Analysis of Passenger Mobility Segmentation during the COVID-19 Pandemic

“…Burke et al [80] used cluster analysis in the evaluation of an alternative mode of transport, namely cycling transport. Their research shows that even if the pandemic had an impact on the popularity of cycling, only its subsequent promotion and investment in cycling infrastructure will result in a more permanent benefit to its preference in the future.…”