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Travel patterns of free-floating e-bike-sharing users before and during COVID-19 pandemic
Seung Eun Choi1, Jinhee Kim2, Dayoung Seo3
1School of Civil and Environmental Engineering, Transportation Systems Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA 30332, United States of America.
Abstract:
Free-floating micro-mobility as a mobility solution is becoming increasingly popular in cities. In this study, the travel patterns of free-floating electric bike-sharing service (FFEBSS) users before and during the COVID-19 pandemic were explored using big data and data mining. Existing real-time data studies provide a limited understanding of trip patterns and the characteristics of each user. Interpretations concerning the occurrence of life-changing events such as the COVID-19 pandemic are important. This study aimed to understand each user over 13 months comprising multiple time frames of market trends, seasonal change, and the COVID-19 pandemic outbreak. Multiple features were extracted from each user to explain the hidden data characteristics, and a data mining method was employed for clustering and evaluating user similarities with the extracted features. The results showed that FFEBSS users demonstrated a moderately stable travel pattern despite the COVID-19 pandemic, indicating the possibility of micro-mobilities being well adoptedas our future urban transportation.
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