Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data
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 im...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/6458371 |
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| _version_ | 1849685129032630272 |
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| author | Eun Hak Lee |
| author_facet | Eun Hak Lee |
| author_sort | Eun Hak Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c2e8b7778afe418b983156dc66db6f5c |
| institution | DOAJ |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-c2e8b7778afe418b983156dc66db6f5c2025-08-20T03:23:15ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/6458371Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card DataEun Hak Lee0Multimodal Planning & Environment DivisionAs 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.http://dx.doi.org/10.1155/2022/6458371 |
| spellingShingle | Eun Hak Lee Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data Journal of Advanced Transportation |
| title | Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data |
| title_full | Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data |
| title_fullStr | Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data |
| title_full_unstemmed | Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data |
| title_short | Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data |
| title_sort | exploring transit use during covid 19 based on xgb and shap using smart card data |
| url | http://dx.doi.org/10.1155/2022/6458371 |
| work_keys_str_mv | AT eunhaklee exploringtransituseduringcovid19basedonxgbandshapusingsmartcarddata |