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Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification
Joint Authors
Bi, Jun
Zhang, Jun
Zhi, Ru
Xie, Dong-Fan
Zhao, Xiao-Mei
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This work explores the characteristics of the usage behaviour of station-based car-sharing users based on the actual operation data from a car-sharing company in Gansu, China.
We analyse the characteristics of the users’ demands, such as usage frequency and order quantity, for a day with 24 1 h time intervals.
Results show that most car-sharing users are young and middle-aged men with a low reuse rate.
The distribution of users’ usage during weekdays shows noticeable morning and evening peaks.
We define two attributes, namely, the latent ratio and persistence ratio, as classification indicators to understand the user diversity and heterogeneity thoroughly.
We apply the k-means clustering algorithm to group the users into four categories, namely, lost, early loyal, late loyal, and motivated users.
The usage characteristics of lost users, including maximum rental time and travel distance, minimum percentage of same pickup and return station, and low percentage of locals, have noticeable differences from those of the other users.
Late loyal users have lower rental time and travel distance than those of the other users.
This manifestation is in line with the short-term lease of shared cars to complete short- and medium-distance travel design concepts.
We also propose a model that predicts the driver cluster based on the decision tree.
Numerical tests indicate that the accuracy is 91.61% when the user category is predicted four months in advance using the observation-to-judgment period ratio of 3 : 1.
The results in this study can support enterprises in user management.
American Psychological Association (APA)
Bi, Jun& Zhi, Ru& Xie, Dong-Fan& Zhao, Xiao-Mei& Zhang, Jun. 2020. Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1175652
Modern Language Association (MLA)
Bi, Jun…[et al.]. Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification. Journal of Advanced Transportation No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1175652
American Medical Association (AMA)
Bi, Jun& Zhi, Ru& Xie, Dong-Fan& Zhao, Xiao-Mei& Zhang, Jun. Capturing the Characteristics of Car-Sharing Users: Data-Driven Analysis and Prediction Based on Classification. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1175652
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175652