Identification of Metro-Bikeshare Transfer Trip Chains by Matching Docked Bikeshare and Metro Smartcards

Xinwei Ma, Shuai Zhang, Yuchuan Jin, Minqing Zhu and Yufei Yuan
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Xinwei Ma: School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China
Shuai Zhang: School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China
Yuchuan Jin: School of Architecture and the Built Environment, Royal Institute of Technology (KTH), 114 28 Stockholm, Sweden
Minqing Zhu: School of Architecture and Art Design, Hebei University of Technology, Tianjin 300401, China
Yufei Yuan: Department of Transport & Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, P.O. Box 5048, 2600 GA Delft, The Netherlands

Energies, 2021, vol. 15, issue 1, 1-19

Abstract: Metro-bikeshare integration, an important way of improving the efficiency of public transportation, has grown rapidly during the last decades in many countries. However, most previous analysis of metro-bikeshare transfer trips were based on limited sample size and the number of recognized metro-bikeshare trips were not sufficient. The primary objective of this study is to derive a method to recognize metro-bikeshare transfer trips. The two data sources are provided by Nanjing Metro Company and Nanjing Public Bicycle Company over the same period from 9–29 March 2016. The identifying method includes three steps: (1) Matching Card Pairs (2) Filtering Card Pairs and (3) Identifying Card Pairs. The case study indicates that the Support Vector Classification (SVC) performs best with a high prediction accuracy of 95.9% using seamless smartcards. The identifying method is then used to recognize the transfer trips from other types of cards, resulting in 17,022 valid metro-bikeshare transfer trips made by 2948 travelers. Finally, travel patterns extracted from the two groups of identified transfer trips are analyzed comparatively. The method proposed presents new opportunities for analyzing metro-bikeshare transfer trip characteristics.

Keywords: metro-bikeshare integration; smartcard; identifying method; prediction model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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