Study on Clustering of Free-Floating Bike-Sharing Parking Time Series in Beijing Subway Stations

Dandan Xu, Yang Bian, Jian Rong, Jiachuan Wang and Baocai Yin
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Dandan Xu: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Yang Bian: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Jian Rong: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Jiachuan Wang: Beijing Transportation Information Center, Beijing 100073, China
Baocai Yin: Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China

Sustainability, 2019, vol. 11, issue 19, 1-20

Abstract: In recent years, the free-floating bike-sharing (FFBS) system has become a significant mode of travel to satisfy urban residents’ travel demands. However, with the rapid development of FFBS, many problems have arisen, among which the parking problem is the most prominent. To solve the FFBS parking problem around urban subways, firstly, the time series of FFBS parking pattern and subway station classification in Beijing were constructed based on parking intensity, showing a significant spatial distribution of subway stations with different intensity levels. Second, a hierarchical clustering method based on dynamic time warping (DTW) was proposed to cluster the FFBS parking time series. Subway stations in Beijing were grouped into 11 clusters, and the clustering purity reached 0.939, which achieved the expected effect. Then, the peak and off-peak period features of time series were extracted to discuss the clustering results. Finally, a two-level early-warning index for monitoring FFBS was constructed, which took the real-time parking quantity and land use capacity of FFBS into consideration. And FFBS parking management strategies for different early-warning indices were put forward. It is very important for the sustainable development of FFBS and cities.

Keywords: bike-sharing; park; subway station; time-series cluster; DTW (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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