IDEAS home Printed from https://ideas.repec.org/a/taf/transp/v46y2023i1p93-118.html
   My bibliography  Save this article

An intelligent management system for relocating semi-autonomous shared vehicles

Author

Listed:
  • Elias K. Xidias
  • Ilias E. Panagiotopoulos
  • Paraskevi Th. Zacharia

Abstract

Car sharing services with Semi-Autonomous Electric Vehicles (SAEVs) represent an emerging transportation scheme which may comprise an important link in the green mobility chain for smart city operations. The main goal of the present paper is to introduce and develop an intelligent management system for the efficient relocation of SAEVs within the urban car-sharing context. A novel relocation strategy is analyzed regarding the upcoming technology of platooning. Considering real urban road networks for SAEVs, routing decisions are assessed based on the traffic conditions and energy efficiency. Fuzzy logic concepts are incorporated into the proposed system to simulate the uncertainty related to the roads’ traffic conditions. The problem addressed in this work is a constrained optimization problem. Solutions to the addressed problem are yielded using a Genetic Algorithm (GA) in accordance with the fuzzy logic module. Simulated experiments over the city of Patras (Greece) show the efficiency of the developed approach.

Suggested Citation

  • Elias K. Xidias & Ilias E. Panagiotopoulos & Paraskevi Th. Zacharia, 2023. "An intelligent management system for relocating semi-autonomous shared vehicles," Transportation Planning and Technology, Taylor & Francis Journals, vol. 46(1), pages 93-118, January.
    • Handle: RePEc:taf:transp:v:46:y:2023:i:1:p:93-118
    DOI: 10.1080/03081060.2022.2162052
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03081060.2022.2162052
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03081060.2022.2162052?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:transp:v:46:y:2023:i:1:p:93-118. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GTPT20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.