journal article·2022-08-30Open access

Operation Characteristics of a Free-Floating Bike Sharing System as a Feeder Mode to Rail Transit Based on GPS Data

Juchen Li, Xiucheng Guo

Applied Sciences· Volume 12· Issue 17

Abstract

The jobs-housing imbalance and long commuting distances for residents in many megacities in China are promoting the increase in mode share with rail transit. The emergence of free-floating bike sharing (FFBS) provides an attractive and cost-effective multi-modal solution to the first/last mile problem. This study identifies the mobility patterns of free-floating bikes as a feeder mode to 277 rail transit stations in Beijing using detailed GPS data, and the relationships between these patterns, culture and spatial layout of the city are examined. The results show that the distribution of free-floating bikes, as a feeder mode to rail transit, exhibits an aggregating feature in the spatial-temporal pattern on weekdays. According to the results of the Clusters method and ANOVA analysis, the operation characteristics of free-floating bikes are related to the location of the transit station and the job-to-housing ratio around that area, and imbalanced usage of shared bikes across the city may result from the extreme values of job-to-housing ratios. Based on the fitted distance decay curve, accessing distance is greatly influenced by urban morphology and location. Based on these findings, recommendations for planning, management, and rebalancing of the FFBS system as a feeder mode to rail transit are proposed to promote the integration of FFBS and the rail transit system.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Urban Transport and Accessibility · Human Mobility and Location-Based Analysis · Urban and Freight Transport Logistics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, China

Funding

Social Science Foundation of Jiangsu Province

References (36)

Show source-provided references
1. Revisiting inequalities in the commuting burden: Institutional constraints and job-housing relationships in Beijing10.1016/j.jtrangeo.2018.06.024 ↗
2. Residential location, transportation, and welfare-to-work in the United States: A case study of Milwaukee10.1080/10511482.2005.9521551 ↗
3. A Novel Hybrid Evaluation Method for Transfer Efficiency Assessment between Rail Transit and Public Bicycles10.7307/ptt.v32i2.3263 ↗
4. Waiting time perceptions at transit stops and stations: Effects of basic amenities, gender, and security
5. Planning for Bike Share Connectivity to Rail Transit10.5038/2375-0901.19.2.1 ↗
6. What drives the utility of shared transport services for urban travellers? A stated preference survey in German cities10.1016/j.tbs.2021.09.010 ↗
7. Free-floating bike sharing: Solving real-life large-scale static rebalancing problems10.1016/j.trc.2017.03.016 ↗
8. Reclaim street space!—Exploit the European potential of car sharing
9. Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach
10. Impact of the COVID-19 pandemic on urban human mobility-A multiscale geospatial network analysis using New York bike-sharing data10.1016/j.cities.2022.103677 ↗
11. Impacts of COVID-19 on bike-sharing usages in Seoul, South Korea10.1016/j.cities.2022.103849 ↗
12. Spatiotemporal evolving patterns of bike-share mobility networks and their associations with land-use conditions before and after the COVID-19 outbreak10.1016/j.physa.2021.126819 ↗
13. The motivations for using bike sharing during the COVID-19 pandemic: Insights from Lisbon10.1016/j.trf.2021.09.016 ↗
14. The role of bike sharing during the coronavirus pandemic: An analysis of the mobility patterns and perceptions of Lisbon’s GIRA users
15. Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic10.1016/j.jtrangeo.2021.102997 ↗
16. Public bicycle as a feeder mode to rail transit in China: The role of gender, age, income, trip purpose, and bicycle theft experience10.1080/15568318.2016.1253802 ↗
17. Free-floating bike-sharing green relocation problem considering greenhouse gas emissions
18. Social Factors Influencing the Choice of Bicycle: Difference Analysis among Private Bike, Public Bike Sharing and Free-Floating Bike Sharing in Kunming, China10.1007/s12205-019-2078-7 ↗
19. Nonlinear and threshold effects of traffic condition and built environment on dockless bike sharing at street level10.1016/j.jtrangeo.2022.103375 ↗
20. Does large scale free-floating bike sharing really improve the sustainability of urban transportation? Empirical evidence from Beijing10.1016/j.scs.2021.103533 ↗
21. Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China10.1016/j.jtrangeo.2020.102787 ↗
22. Inventory rebalancing and vehicle routing in bike sharing systems10.1016/j.ejor.2016.08.029 ↗
23. Dynamic green bike repositioning problem—A hybrid rolling horizon artificial bee colony algorithm approach10.1016/j.trd.2017.06.023 ↗
24. A static free-floating bike repositioning problem with multiple heterogeneous vehicles, multiple depots, and multiple visits10.1016/j.trc.2018.02.008 ↗
25. A modeling framework for the dynamic management of free-floating bike-sharing systems10.1016/j.trc.2018.01.001 ↗
26. Bikeshare: A Review of Recent Literature10.1080/01441647.2015.1033036 ↗
27. Analysis of bike sharing system by clustering: The Velib’ case
28. Evaluating public transit modal shift dynamics in response to bikesharing: A tale of two US cities10.1016/j.jtrangeo.2014.06.026 ↗
29. Hail a cab or ride a bike? A travel time comparison of taxi and bicycle-sharing systems in New York City
30. Bicycle Sharing and Public Transit Does Capital Bikeshare Affect Metrorail Ridership in Washington, DC?10.3141/2534-01 ↗
31. Determinants of Bicycle-On-Bus Boardings: A Case Study of the Greater Cleveland RTA10.5038/2375-0901.16.2.4 ↗
32. Froehlich, J., Neumann, J., and Oliver, N. (2022, January 23–29). Sensing and Predicting the Pulse of the City through Shared Bicycling. Proceedings of the 1st International Joint Conference on Artificial Intelligence (Ijcai-09), Vienna, Austria.
33. Braun, L.M., Barajas, J.M., Lee, B., and Martin, R. (2022). Walking the Last Mile: Barriers and Solutions to Suburban Transit Access. Transp. Res. Rec.10.1177/03611981221095748 ↗
34. Travel demand and the 3Ds: Density, diversity, and design10.1016/S1361-9209(97)00009-6 ↗
35. Travel satisfaction with dockless bike-sharing: Trip stages, attitudes and the built environment10.1016/j.trd.2022.103280 ↗
36. Analysis of integrated uses of dockless bike sharing and ridesourcing with metros: A case study of Shanghai, China10.1016/j.scs.2022.103918 ↗