IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v41y2007i6p684-700.html
   My bibliography  Save this article

Modeling the process of information relay through inter-vehicle communication

Author

Listed:
  • Wang, Xiubin

Abstract

In a new paradigm of the decentralized traffic information system as a recent thrust in the Intelligent Transportation Systems (ITS), vehicles form ad hoc mobile networks, and information may be propagated between vehicles through wireless communication with a short transmission range. Fundamental to the system design is effective information propagation. In this paper, we study information propagation along a traffic stream on which presence of equipped vehicles follows an independent homogeneous Poisson process. We define a relay process in which only the furthest equipped vehicle within each transmission range continues the relay, and model it as a transient Markov process. We present closed form formulas for the expected value and variance of propagation distance in the case without transmission delay. We also study the expected number of relays and the expected propagation distance in the case with transmission delay. The results make transparent the relationship between propagation distance, equipped vehicle density and transmission range. In addition, we study the probability distribution of propagation distance, and find that the Gamma distribution could be used as a good practical means of approximation especially when the number of equipped vehicles is large within a transmission range. The Gamma-like behavior is also observed on heterogeneous traffic. It is noted that the relay process has many other applications as well.

Suggested Citation

  • Wang, Xiubin, 2007. "Modeling the process of information relay through inter-vehicle communication," Transportation Research Part B: Methodological, Elsevier, vol. 41(6), pages 684-700, July.
    • Handle: RePEc:eee:transb:v:41:y:2007:i:6:p:684-700
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(06)00127-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    References listed on IDEAS

    as
    1. Jin, Wen-Long & Recker, Wilfred W., 2006. "Instantaneous information propagation in a traffic stream through inter-vehicle communication," Transportation Research Part B: Methodological, Elsevier, vol. 40(3), pages 230-250, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baiocchi, Andrea, 2016. "Analysis of timer-based message dissemination protocols for inter-vehicle communications," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 105-134.
    2. Jia, Dongyao & Ngoduy, Dong, 2016. "Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 172-191.
    3. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
    4. Jin, W L & Wang, Bruce, 2010. "Connectivity of vehicular ad hoc networks with continuous node distribution patterns," University of California Transportation Center, Working Papers qt1565f72s, University of California Transportation Center.
    5. Jin, W L, 2010. "Modeling connectivity of inter-vehicle communication networks along discrete traffic streams," University of California Transportation Center, Working Papers qt2jd4m0ck, University of California Transportation Center.
    6. Wang, Jian & Peeta, Srinivas & Lu, Lili & Li, Tao, 2019. "Multiclass information flow propagation control under vehicle-to-vehicle communication environments," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 96-121.
    7. Jin, Wen-Long & Recker, Wilfred W. & Wang, Xiubin B., 2016. "Instantaneous multihop connectivity of one-dimensional vehicular ad hoc networks with general distributions of communication nodes," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 159-177.

    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. Taniguchi, Yohei & Nishi, Ryosuke & Ezaki, Takahiro & Nishinari, Katsuhiro, 2015. "Jam-absorption driving with a car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 304-315.
    2. Jin, W L & Wang, Bruce, 2010. "Connectivity of vehicular ad hoc networks with continuous node distribution patterns," University of California Transportation Center, Working Papers qt1565f72s, University of California Transportation Center.
    3. Jia, Dongyao & Ngoduy, Dong, 2016. "Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 172-191.
    4. Baiocchi, Andrea, 2016. "Analysis of timer-based message dissemination protocols for inter-vehicle communications," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 105-134.
    5. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    6. Jin, Wen-Long & Recker, Wilfred W. & Wang, Xiubin B., 2016. "Instantaneous multihop connectivity of one-dimensional vehicular ad hoc networks with general distributions of communication nodes," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 159-177.
    7. Liu, Siyuan & Qu, Qiang, 2016. "Dynamic collective routing using crowdsourcing data," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 450-469.

    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:eee:transb:v:41:y:2007:i:6:p:684-700. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.