Analyzing bike repositioning strategies based on simulations for public bike sharing systems: Simulating bike repositioning strategies for bike sharing systems

I. Lin Wang, Chun Wei Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

With the contributions on reducing the traffic congestion and air pollution, bike sharing systems become more popular recently in many metropolitan areas worldwide. Without effective bike redistribution strategies, a bike rental station may easily become out or full of bikes, which incurs the customer inconvenience and conflicts its purpose. In order to evaluate the impacts and performance on different bike redistribution strategies, we propose and simulate several bike redistribution strategies with and without different levels of real-time or historical bike rental information. In particular, for a system that conducts no or simple bike repositioning operations, we further consider whether the system is capable of learning preferred bike-return destinations specified by commuters, suggesting bike-return destinations to customers, or exploiting the historical trend of commuter traffics.

Original languageEnglish
Title of host publicationProceedings - 2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013
Pages306-311
Number of pages6
DOIs
Publication statusPublished - 2013
Event2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013 - Matsue, Japan
Duration: 2013 Aug 312013 Sep 4

Publication series

NameProceedings - 2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013

Other

Other2nd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2013
CountryJapan
CityMatsue
Period13-08-3113-09-04

All Science Journal Classification (ASJC) codes

  • Information Systems

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