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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19924
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dc.contributor.authorTempl, Matthias-
dc.contributor.authorHeitz, Christoph-
dc.date.accessioned2020-04-20T07:18:12Z-
dc.date.available2020-04-20T07:18:12Z-
dc.date.issued2020-02-
dc.identifier.issn1026-597Xde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/19924-
dc.description.abstractFor redistribution and operating bikes in a free-floating systems, two measures are of highest priority. First, the information about the expected number of rentals on a day is an important measure for service providers for management and service of their fleet. The estimation of the expected number of bookings is carried out with a simple model and a more complex model based on meterological information, as the number of loans depends strongly on the current and forecasted weather. Secondly, the knowledge of a service level violation in future on a fine spatial resolution is important for redistribution of bikes. With this information, the service provider can set reward zones where service level violations will occur in the near future. To forecast a service level violation on a fine geographical resolution the current distribution of bikes as well as the time and space information of past rentals has to be taken into account. A Markov Chain Model is formulated to integrate this information. We develop a management tool that describes in an explorative way important information about past, present and predicted future counts on rentals in time and space. It integrates all estimation procedures. The management tool is running in the browser and continuously updates the information and predictions since the bike distribution over the observed area is in continous flow as well as new data are generated continuously.de_CH
dc.language.isoende_CH
dc.publisherAustrian Statistical Societyde_CH
dc.relation.ispartofAustrian Journal of Statisticsde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectFree-floating bike systemde_CH
dc.subjectSpatio-temporal datade_CH
dc.subjectGeneralized additive modelde_CH
dc.subjectMarkov chainde_CH
dc.subjectManagment toolde_CH
dc.subject.ddc003: Systemede_CH
dc.titleFleet management in free-floating bike sharing systems using predictive modelling and explorative toolsde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.17713/ajs.v49i2.1114de_CH
dc.identifier.doi10.21256/zhaw-19924-
zhaw.funding.euNode_CH
zhaw.issue2de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end69de_CH
zhaw.pages.start53de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume49de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDigital Mobilityde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

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Templ, M., & Heitz, C. (2020). Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools. Austrian Journal of Statistics, 49(2), 53–69. https://doi.org/10.17713/ajs.v49i2.1114
Templ, M. and Heitz, C. (2020) ‘Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools’, Austrian Journal of Statistics, 49(2), pp. 53–69. Available at: https://doi.org/10.17713/ajs.v49i2.1114.
M. Templ and C. Heitz, “Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools,” Austrian Journal of Statistics, vol. 49, no. 2, pp. 53–69, Feb. 2020, doi: 10.17713/ajs.v49i2.1114.
TEMPL, Matthias und Christoph HEITZ, 2020. Fleet management in free-floating bike sharing systems using predictive modelling and explorative tools. Austrian Journal of Statistics. Februar 2020. Bd. 49, Nr. 2, S. 53–69. DOI 10.17713/ajs.v49i2.1114
Templ, Matthias, and Christoph Heitz. 2020. “Fleet Management in Free-Floating Bike Sharing Systems Using Predictive Modelling and Explorative Tools.” Austrian Journal of Statistics 49 (2): 53–69. https://doi.org/10.17713/ajs.v49i2.1114.
Templ, Matthias, and Christoph Heitz. “Fleet Management in Free-Floating Bike Sharing Systems Using Predictive Modelling and Explorative Tools.” Austrian Journal of Statistics, vol. 49, no. 2, Feb. 2020, pp. 53–69, https://doi.org/10.17713/ajs.v49i2.1114.


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