Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic

Abstract

The COVID-19 pandemic has led to a globally unprecedented change in human mobility. Leveraging two-year bike-sharing trips from the largest bike-sharing program in Chicago, this study examines the spatiotemporal evolution of bike-sharing usage across the pandemic and compares it with other modes of transport. A set of generalized additive (mixed) models are fitted to identify relationships and delineate nonlinear temporal interactions between station-level daily bike-sharing usage and various independent variables including socio-demographics, land use, transportation features, station characteristics, and COVID-19 infections. Results show: 1) the proportion of commuting trips is substantially lower during the pandemic; 2) the trend of bike-sharing usage follows an "increase-decrease-rebound" pattern; 3) bike-sharing presents as a more resilient option compared with transit, driving, and walking; 4) regions with more white, Asian, and fewer African-American residents are found to become less dependent on bike-sharing; 5) open space and residential areas exhibit less decrease and earlier start-to-recover time; 6) stations near the city center, with more docks, or located in high-income areas go from more increase before the pandemic to more decrease during the pandemic. Findings provide a timely understanding of bike-sharing usage changes and offer suggestions on how different stakeholders should respond to this unprecedented crisis.

Keywords: Bike-sharing; COVID-19; Generalized additive mixed model; Human mobility; Nonlinearity; Socio-economic disparity.

Fig. 1

Time series of bike-sharing pickups in Chicago. (a) From June 27^th, 2013 to July 31st, 2020; (b) From February 1^st, 2020 to July 31^st, 2020.

Fig. 2

Station-level cumulative relative change during COVID-19.

Fig. 3

Temporal patterns of Divvy bike-sharing pickups. (a) Hourly total trips; (b) Weekly total trips from 0 (Monday) to 6 (Sunday).

Fig. 4

Spatial patterns of Divvy bike-sharing pickups. (a) Average daily pickups from March 11^st, 2019 to July 31^st, 2019; (b) Average daily pickups from March 11^st, 2020 to July 31^st, 2020.

Fig. 5

Spatial patterns of Cumulative relative changes by July 31^st, 2020. (a) Cumulative relative changes with positive values; (b) Absolute of cumulative relative changes with negative values.

Fig. 6

Temporal evolution of relative volume of different modes of transport across the pandemic, from January 1^st, 2020 to July 31^st, 2020, compared to a baseline volume on January 13^th, 2020.

Fig. 7

Nonlinear interactions between time index and different independent variables of interest regarding the cumulative relative changes. Note: a) All models have controlled weather conditions (temperature and rainfall), holidays, time-series seasonality (weekly and monthly), and other linear fixed effects except for the variable of interest. b) Only variables with statistically significant interaction with time index (i.e. P-value <0.1) are plotted. c) The horizontal axis varies from February 1^st, 2020 to July 31^st, 2020. March 11^st, 2020 is set as Day 0, and days with negative indexes represent days earlier than March 11^st, 2020. d) For some comparable pairs of variables, i.e., Prop. of White vs. Prop. of Asian vs. Prop. of Black, Prop. of Openspace vs. Prop. of Residential, the scale of color bar is set as the same.