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Analysis Framework for Electric Vehicle Sharing Systems Using Vehicle Movement Data Stream

  • Junghoon Lee
  • Hye-Jin Kim
  • Gyung-Leen Park
  • Ho-Young Kwak
  • Moo Yong Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7234)

Abstract

This paper designs and builds a serviceability analysis framework for electric vehicle sharing systems based on the vehicle movement data stream collected from the taxi telematics system. For the given sharing station distribution and the relocation strategy, our framework can accurately trace the current number of available vehicles in each station using actual travel data consist of the pick-up and drop-off records. Combined with the discrete event simulation, it is possible to measure the service ratio and moving distance. Experiments are conducted to assess the effect of the number of electric vehicles and the access distance to the service ratio for Jeju city area, discovering that up to 91 % service ratio can be achieved with 5 stations and 50 vehicles. In addition, the per-station trace reveals that the relocation strategy must consider the area-specific unbalance between pick-ups and returns, as it significantly affects the service ratio.

Keywords

Electric Vehicle Smart Grid Road Segment Shopping Mall Sharing Station 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Junghoon Lee
    • 1
  • Hye-Jin Kim
    • 1
  • Gyung-Leen Park
    • 1
  • Ho-Young Kwak
    • 2
  • Moo Yong Lee
    • 3
  1. 1.Dept. of Computer Science and StatisticsJeju National UniversityJeju-DoRepublic of Korea
  2. 2.Dept. of Electric EngineeringJeju National UniversityJeju-DoRepublic of Korea
  3. 3.Jinwoo Soft InnovationJeju-DoRepublic of Korea

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