Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility Data

Abstract

The constrained outbreak of COVID-19 in Mainland China has recently been regarded as a successful example of fighting this highly contagious virus. Both the short period (in about three months) of transmission and the sub-exponential increase of confirmed cases in Mainland China have proved that the Chinese authorities took effective epidemic prevention measures, such as case isolation, travel restrictions, closing recreational venues, and banning public gatherings. These measures can, of course, effectively control the spread of the COVID-19 pandemic. Meanwhile, they may dramatically change the human mobility patterns, such as the daily transportation-related behaviors of the public. To better understand the impact of COVID-19 on transportation-related behaviors and to provide more targeted anti-epidemic measures, we use the huge amount of human mobility data collected from Baidu Maps, a widely-used Web mapping service in China, to look into the detail reaction of the people there during the pandemic. To be specific, we conduct data-driven analysis on transportationrelated behaviors during the pandemic from the perspectives of 1) means of transportation, 2) type of visited venues, 3) check-in time of venues, 4) preference on "origin-destination" distance, and 5) "origin-transportation-destination" patterns. For each topic, we also give our specific insights and policy-making suggestions. Given that the COVID-19 pandemic is still spreading in more than 200 countries and territories worldwide, infecting millions of people, the insights and suggestions provided here may help fight COVID-19. CCS CONCEPTS• Human-centered computing → Empirical studies in ubiquitous and mobile computing; • Applied computing → Sociology; Transportation.

A mixed-methods analysis of mobility behavior changes in the COVID-19 era in a rural case study

“…Under consideration of a reduction trip by other means of transport, like bus, the modal share of walking increased somehow. The findings of an increase of car use in modal split in recent studies [4,23,34] could not be replicated in this study. In contrast, the respondents report a reduction of trips by car on the modal share and a reduction of daily use, which was also found in a study by de Haas, Faber and Hamersma [20].…”

“…A considerable share of respondents in a German study expressed their intention to buy a car as a reaction to the COVID-19 situation [23]. This trend towards an increase of the relative share of private car trips within the remaining mobility was shown in further studies from Hungary [13], Spain [4] and China [34]. At the same time, studies reveal an increase in the number of trips by bike [36,45] and an increase of cycling in the modal share [4,34].…”

Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective

“…The density of the global network of flights also decreased by 51% during this time. A survey conducted on the impact of COVID-19 related restrictions in European countries concluded that each airport lost 50% of its connections in the global airport network [10]. Travel limitations and closure of borders debilitatingly affected the air terminals and the avionics sectors of the travel industry.…”

“…Huang et al [10] investigate the impact of a pandemic on transportation-related behaviours. Travel restrictions were one of the major effective measures taken in Mainland China to control the COVID-19 outbreak.…”

“…Moreover, people preferred zero-touch transportation to reach their destination. Sun et al [10] conducted an empirical analysis on the air transportation systems using multi-granularity network analysis including international, domestic, and worldwide airport networks from January to May 2020. It was found that flight restrictions were imposed on long-distance international flights, while the impact of pandemic was lower on domestic flights.…”