Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy

Svenja Reiss; Klaus Bogenberger

doi:10.1109/ITSC.2016.7795976

Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy

Svenja Reiss, Klaus Bogenberger

Chair of Traffic Engineering and Control

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Scopus citations

Abstract

Based on an empirical data analysis, a simulation was built up in order to forecast the upcoming demand for an urban Bike Sharing System (BSS). To satisfy this demand, a relocation strategy is applied to rebalance the fleet of the BSS. In case of moderate imbalances, a pricing model incents users to ride bikes from "bad" to "good" spots. This saves operator's cost as no further relocation trips by trucks are generated. If the imbalances are severe though, the user-based method is not sufficient and the operator needs to intervene supplementary. Therefore, the relocation model provides an optimal strategy to combine both methods.

Original language	English
Title of host publication	2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2613-2618
Number of pages	6
ISBN (Electronic)	9781509018895
DOIs	https://doi.org/10.1109/ITSC.2016.7795976
State	Published - 22 Dec 2016
Event	19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016 - Rio de Janeiro, Brazil Duration: 1 Nov 2016 → 4 Nov 2016

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Conference

Conference	19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016
Country/Territory	Brazil
City	Rio de Janeiro
Period	1/11/16 → 4/11/16

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10.1109/ITSC.2016.7795976

Cite this

Reiss, S., & Bogenberger, K. (2016). Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016 (pp. 2613-2618). Article 7795976 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2016.7795976

Reiss, Svenja ; Bogenberger, Klaus. / Optimal bike fleet management by smart relocation methods : Combining an operator-based with an user-based relocation strategy. 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2613-2618 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

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abstract = "Based on an empirical data analysis, a simulation was built up in order to forecast the upcoming demand for an urban Bike Sharing System (BSS). To satisfy this demand, a relocation strategy is applied to rebalance the fleet of the BSS. In case of moderate imbalances, a pricing model incents users to ride bikes from {"}bad{"} to {"}good{"} spots. This saves operator's cost as no further relocation trips by trucks are generated. If the imbalances are severe though, the user-based method is not sufficient and the operator needs to intervene supplementary. Therefore, the relocation model provides an optimal strategy to combine both methods.",

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Reiss, S & Bogenberger, K 2016, Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy. in 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016., 7795976, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, Institute of Electrical and Electronics Engineers Inc., pp. 2613-2618, 19th IEEE International Conference on Intelligent Transportation Systems, ITSC 2016, Rio de Janeiro, Brazil, 1/11/16. https://doi.org/10.1109/ITSC.2016.7795976

Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy. / Reiss, Svenja; Bogenberger, Klaus.
2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2613-2618 7795976 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Based on an empirical data analysis, a simulation was built up in order to forecast the upcoming demand for an urban Bike Sharing System (BSS). To satisfy this demand, a relocation strategy is applied to rebalance the fleet of the BSS. In case of moderate imbalances, a pricing model incents users to ride bikes from "bad" to "good" spots. This saves operator's cost as no further relocation trips by trucks are generated. If the imbalances are severe though, the user-based method is not sufficient and the operator needs to intervene supplementary. Therefore, the relocation model provides an optimal strategy to combine both methods.

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Reiss S, Bogenberger K. Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems, ITSC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 2613-2618. 7795976. (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). doi: 10.1109/ITSC.2016.7795976

Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy

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