Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41341

Generating Rental Data for Car Sharing Relocation Simulations on the Example of Station-Based One-Way Car Sharing

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Title: Generating Rental Data for Car Sharing Relocation Simulations on the Example of Station-Based One-Way Car Sharing
Authors: Brendel, Alfred Benedikt
Rockenkamm, Christian
Kolbe, Lutz Maria
Keywords: car sharing
data generator
shared vehicle services
simulation
vehicle relocation
Issue Date: 04 Jan 2017
Abstract: Developing sophisticated car sharing simulations is a major task to improve car sharing as a sustainable means of transportation, because new \ algorithms for enhancing car sharing efficiency are formulated using them. \ \ Simulations rely on input data, which is often gathered in car sharing systems or artificially generated. Real-world data is often incomplete and biased while artificial data is mostly generated based on initial assumptions. Therefore, developing new ways for generating testing data is an important task for future research. \ \ In this paper, we propose a new approach for generating car sharing data for relocation simulations by utilizing machine learning. Based on real-world data, we could show that a combined methods approach consisting of a Gaussian Mixture Model and two classification trees can generate appropriate artificial testing data.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41341
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.188
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Service Analytics Minitrack



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