IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v4y2019i1p28-d204683.html
   My bibliography  Save this article

Vehicular Ad Hoc Network (VANET) Connectivity Analysis of a Highway Toll Plaza

Author

Listed:
  • Saajid Hussain

    (School of Computer Science and Engineering, Dalian University of Technology Liaoning, Dalian 116024, China)

  • Di Wu

    (School of Computer Science and Engineering, Dalian University of Technology Liaoning, Dalian 116024, China)

  • Sheeba Memon

    (School of Information Science and Engineering, Central South University, Hunan, Changsha 410083, China)

  • Naadiya Khuda Bux

    (School of Information Science and Engineering, Central South University, Hunan, Changsha 410083, China)

Abstract

The aim of this paper was to study issues of network connectivity in vehicular ad hoc networks (VANETs) to avoid traffic congestion at a toll plaza. An analytical model was developed for highway scenarios where the traffic congestion could have the vehicles reduce their speed instead of blocking the flow of traffic. In this model, nearby vehicles must be informed when traffic congestion occurs before reaching the toll plaza so they can reduce their speed in order to avoid traffic congestion. Once they have crossed the toll plaza they can travel on at their normal speed. The road was divided into two or three sub-segments to help analyze the performance of connectivity. The proposed analytical model considered various parameters that might disturb the connectivity probability, including traveling speed, communication range of vehicles, vehicle arrival rate, and road length. The simulation results matched those of the analytical model, which showed the analytical model developed in this paper is effective.

Suggested Citation

  • Saajid Hussain & Di Wu & Sheeba Memon & Naadiya Khuda Bux, 2019. "Vehicular Ad Hoc Network (VANET) Connectivity Analysis of a Highway Toll Plaza," Data, MDPI, vol. 4(1), pages 1-18, February.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:1:p:28-:d:204683
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/4/1/28/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/4/1/28/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eirini Eleni Tsiropoulou & John S. Baras & Symeon Papavassiliou & Surbhit Sinha, 2017. "RFID-based smart parking management system," Cyber-Physical Systems, Taylor & Francis Journals, vol. 3(1-4), pages 22-41, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miraal Kamal & Manal Atif & Hafsa Mujahid & Tamer Shanableh & A. R. Al-Ali & Ahmad Al Nabulsi, 2019. "IoT Based Smart City Bus Stops," Future Internet, MDPI, vol. 11(11), pages 1-11, October.
    2. Jessie Marie Byrnes & Yu-Jau Lin & Tzong-Ru Tsai & Yuhlong Lio, 2019. "Bayesian Inference of δ = P ( X < Y ) for Burr Type XII Distribution Based on Progressively First Failure-Censored Samples," Mathematics, MDPI, vol. 7(9), pages 1-24, September.
    3. Alica Kalašová & Kristián Čulík & Miloš Poliak & Zuzana Otahálová, 2021. "Smart Parking Applications and Its Efficiency," Sustainability, MDPI, vol. 13(11), pages 1-17, May.

    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:gam:jdataj:v:4:y:2019:i:1:p:28-:d:204683. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.