Schetley, Dillon
(2020)
Rebalancing techniques for station-based bike sharing systems.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
With bike-sharing systems that utilize fixed rent and drop off stations becoming popular in cities and metropolitan areas worldwide, the issue of station fill balance becomes apparent. It is important for the user experience and the organization's bottom line that bikes are available at the stations where they are needed and that stations do not become too crowded and thus prevent easy returns. There is not, however, a clear solution of how to perform this rebalancing. Considerations include how to determine the stations that most need to be rebalanced, how frequently to do this rebalancing in the system, and how many resources to expend doing it. Methodologies answering some of these questions have been proposed, but many do not provide all of the answers necessary to fully implement a real-world solution. Additionally, there is no benchmarking tool to fairly compare these rebalancing approaches on a given system.
This thesis proposes exactly this kind of tool in the form of a station-based bike-sharing system simulator. The simulator is modular and provides several parameters to allow the comparison of different systems, historical data, workloads, and rebalancing strategies. To demonstrate its capabilities, experiments were run comparing the effects of individual parameter changes and various combinations of parameter configurations on various metrics, including gross revenue and lost revenue from missed demand. Analysis of these experimental results gives not only a look into the simulation's uses as a comparative tool, but also provides information on alternatives to common predictive rebalancing strategies.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
20 August 2020 |
| Date Type: |
Publication |
| Defense Date: |
31 July 2020 |
| Approval Date: |
20 August 2020 |
| Submission Date: |
7 August 2020 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
58 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Computing and Information > Computer Science |
| Degree: |
MS - Master of Science |
| Thesis Type: |
Master's Thesis |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Bike-sharing systems, Station-based, Rebalancing, Simulation |
| Date Deposited: |
20 Aug 2020 19:02 |
| Last Modified: |
20 Aug 2020 19:02 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/39565 |
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