Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data

Abstract

Modern public transit systems are often run with automated fare collection (AFC) systems in combination with smart cards. These systems passively collect massive amounts of detailed spatio-temporal trip data, thus opening up new possibilities for public transit planning and management as well as providing new insights for urban planners. We use smart card trip data from Taipei, Taiwan, to perform an in-depth analysis of spatio-temporal station-to-station metro trip patterns for a whole week divided into several time slices. Based on simple linear regression and line graphs, days of the week and times of the day with similar temporal passenger flow patterns are identified. We visualize magnitudes of passenger flow based on actual geography. By comparing flows for January to March 2019 and for January to March 2020, we look at changes in metro trips under the impact of the coronavirus pandemic (COVID-19) that caused a state of emergency around the globe in 2020. Our results show that metro usage under the impact of COVID-19 has not declined uniformly, but instead is both spatially and temporally highly heterogeneous.

The impact of COVID-19 and related containment measures on Bangkok’s public transport ridership

“…In their study, the bus ridership during the morning and midday peaks decreased less than during the afternoon peaks. Also, the study of Mützel and Scheiner (2021) shows that although there was a significant drop in ridership there was not much change in the trend of temporal metro usage in Taipei during the pandemic.…”

Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region

“…Since the outbreak of COVID-19, there has been extensive research into the impact of the pandemic on travel demand. Much of this research has focused on aggregate demand across the transport networks, sometimes with an explicitly spatial description of changing demand levels ( Jenelius and Cebecauer, 2020 ; Mützel and Scheiner, 2021 ; Orro et al, 2020 ; Wielechowski et al, 2020 ; Zhang et al, 2021 ). Location of trip origins is also used to link changes in travel to socio-demographic and economic neighbourhood compositions ( Almlöf et al, 2021 ; Liu et al, 2020 ; Sy et al, 2020 ).…”

Robustness and disturbances in public transport

“…For instance, in Wuhan, China, the municipal government expropriated, among others, bus stations to build shelter hospitals rather than using them for public transport purposes (Yu and Li 2020 ). Literally, the Covid-19 pandemic might deserve a comprehensive paper on its own; for some references see, e.g., Hirschhorn ( 2021 ), Marsden and Docherty ( 2021 ) and Mützel and Scheiner ( 2021 ).…”