Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data

Eun Hak Lee

24 citations0/0 files storedJournal of Advanced Transportation

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Transportation Planning and Optimization Urban Transport and Accessibility Transportation and Mobility Innovations

Abstract

As the coronavirus (COVID-19) pandemic continues, many protective measures have been taken in Seoul, Korea, and around the world. This situation has drastically changed lifestyle and travel behavior. An important issue concerns understanding the reasons for giving up transit use and the potential impact on travel patterns during the COVID-19 pandemic. To shed light on these issues that are essential for transit policy, this study explores transit use choice, such as whether users have given-up transit use or not, during the COVID-19 pandemic. Two days of smart card data, before and during the COVID-19 pandemic, were used to look at users who gave up transit use during the COVID-19 pandemic. The choice set of the dataset includes two alternatives, for example, transit use and given-up transit use. An extreme gradient boosting (XGB) model was used to estimate the transit use behavior. Shapley additive explanations were performed to interpret the estimation results of the XGB model. The results for the overall specificity, sensitivity, and balanced accuracy of the proposed XGB model were estimated to be 0.909, 0.953, and 0.931, respectively. The feature analysis based on the Shapley value shows that the number of origin-to-destination trip feature substantially impacts transit use. As such, users tend to avoid transit use as travel time increased during the COVID-19 pandemic. The proposed model shows remarkable performance in accuracy and provided an understanding of the estimated results.

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References

195317. A Value for n-Person Games 2020The effect of COVID-19 and subsequent social distancing on travel behavior 2020How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands 2020Exploring the impacts of COVID-19 on travel behavior and mode preferences 2020How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago 2020Travel behavior changes during the COVID-19 pandemic in Japan: Analyzing the effects of risk perception and social influence on going-out self-restriction 2021Transport mode use during the COVID-19 lockdown period in Germany: The car became more important, public transport lost ground 2020Who left riding transit? Examining socioeconomic disparities in the impact of COVID-19 on ridership

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