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Article: A modeling framework for the dynamic management of free-floating bike-sharing systems
Title | A modeling framework for the dynamic management of free-floating bike-sharing systems |
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Authors | |
Keywords | Free-floating bike sharing systems Spatio-temporal clustering Non-linear autoregressive neural network forecasting Decision Support System Dynamic fleet relocation |
Issue Date | 2018 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc |
Citation | Transportation Research Part C: Emerging Technologies, 2018, v. 87, p. 159-182 How to Cite? |
Abstract | Given the growing importance of bike-sharing systems nowadays, in this paper we suggest an alternative approach to mitigate the most crucial problem related to them: the imbalance of bicycles between zones owing to one-way trips. In particular, we focus on the emerging free-floating systems, where bikes can be delivered or picked-up almost everywhere in the network and not just at dedicated docking stations. We propose a new comprehensive dynamic bike redistribution methodology that starts from the prediction of the number and position of bikes over a system operating area and ends with a relocation Decision Support System. The relocation process is activated at constant gap times in order to carry out dynamic bike redistribution, mainly aimed at achieving a high degree of user satisfaction and keeping the vehicle repositioning costs as low as possible. An application to a test case study, together with a detailed sensitivity analysis, shows the effectiveness of the suggested novel methodology for the real-time management of the free-floating bike-sharing systems. |
Persistent Identifier | http://hdl.handle.net/10722/259229 |
ISSN | 2023 Impact Factor: 7.6 2023 SCImago Journal Rankings: 2.860 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Caggiani, L | - |
dc.contributor.author | Camporeale, R | - |
dc.contributor.author | Ottomanelli, M | - |
dc.contributor.author | Szeto, WY | - |
dc.date.accessioned | 2018-09-03T04:03:29Z | - |
dc.date.available | 2018-09-03T04:03:29Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Transportation Research Part C: Emerging Technologies, 2018, v. 87, p. 159-182 | - |
dc.identifier.issn | 0968-090X | - |
dc.identifier.uri | http://hdl.handle.net/10722/259229 | - |
dc.description.abstract | Given the growing importance of bike-sharing systems nowadays, in this paper we suggest an alternative approach to mitigate the most crucial problem related to them: the imbalance of bicycles between zones owing to one-way trips. In particular, we focus on the emerging free-floating systems, where bikes can be delivered or picked-up almost everywhere in the network and not just at dedicated docking stations. We propose a new comprehensive dynamic bike redistribution methodology that starts from the prediction of the number and position of bikes over a system operating area and ends with a relocation Decision Support System. The relocation process is activated at constant gap times in order to carry out dynamic bike redistribution, mainly aimed at achieving a high degree of user satisfaction and keeping the vehicle repositioning costs as low as possible. An application to a test case study, together with a detailed sensitivity analysis, shows the effectiveness of the suggested novel methodology for the real-time management of the free-floating bike-sharing systems. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/trc | - |
dc.relation.ispartof | Transportation Research Part C: Emerging Technologies | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Free-floating bike sharing systems | - |
dc.subject | Spatio-temporal clustering | - |
dc.subject | Non-linear autoregressive neural network forecasting | - |
dc.subject | Decision Support System | - |
dc.subject | Dynamic fleet relocation | - |
dc.title | A modeling framework for the dynamic management of free-floating bike-sharing systems | - |
dc.type | Article | - |
dc.identifier.email | Szeto, WY: ceszeto@hku.hk | - |
dc.identifier.authority | Szeto, WY=rp01377 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.trc.2018.01.001 | - |
dc.identifier.scopus | eid_2-s2.0-85044115523 | - |
dc.identifier.hkuros | 289317 | - |
dc.identifier.volume | 87 | - |
dc.identifier.spage | 159 | - |
dc.identifier.epage | 182 | - |
dc.identifier.isi | WOS:000428496300011 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 0968-090X | - |