City Research Online

Abstract

The use of bicycles can provide myriad benefits to society, especially in crowded urban centres where other modes of transport are at or near capacity. However, integrating cycling into policy and planning requires more comprehensive data about their use in space and time. Current approaches, using sparse networks of counters provide one possible route to more comprehensive data. In this paper we investigate another, using data collected from Paris’ bicycle sharing system to explore use during 2020. We chose 2020 as a test year because the use of bicycles was strongly influenced by the COVID-19 pandemic, allowing us to explore how bicycle use adapted to both legal and environmental influences. We used interactive visualization to allow hypothesis generation and data exploration, before analysing bicycle use as a function of weather and COVID-19 restrictions. Our results show that bicycle sharing system data and Paris’ counters both capture very similar behaviour patterns, and therefore bicycle sharing system data are a reliable proxy for overall cycling behaviour, providing finer spatial granularity than existing sparse counter networks. Seasonally, precipitation influenced bicycle use more strongly in 2020 than COVID-19 measures.

Publication Type:	Article
Additional Information:	© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publisher Keywords:	Bicycle sharing system, Bicycle counters, Covid-19, Paris, Visualization
Subjects:	J Political Science > JA Political science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments:	School of Science & Technology > Computer Science
SWORD Depositor:	Symplectic Administrator

Export

Downloads