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Minimum Transmission Range Estimation for Vehicular Ad Hoc Networks in Signalised Arterials

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Computer Networks (CN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 718))

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Abstract

In this paper the connectivity is analysed of vehicular ad hoc networks (VANETs) in arterial roads with signalised intersections. A method is proposed to derive an estimate of minimum transmission range (MTR), i.e., a minimum value of the vehicles transmission range that allows all vehicles in a given road section to be connected via multihop communication. The introduced method takes into account the impact of traffic signals coordination on formation of vehicle platoons. It is applicable for both the under-saturated and the over-saturated traffic conditions. The main contribution in this paper is formulation of a relationship, which allows the upper bound of MTR to be estimated for VANETs in unidirectional and bidirectional signalized arterial roads. The conducted experiments confirm that the derived estimate fits well with results of simulation experiments.

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Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, Będzińska 39, 41-200, Sosnowiec, Poland

    Bartłomiej Płaczek & Marcin Bernas

Authors
  1. Bartłomiej Płaczek
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  2. Marcin Bernas
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Correspondence to Bartłomiej Płaczek .

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Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Piotr Gaj

  2. Silesian University of Technology, Gliwice, Poland

    Andrzej Kwiecień

  3. Silesian University of Technology, Gliwice, Poland

    Michał Sawicki

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Płaczek, B., Bernas, M. (2017). Minimum Transmission Range Estimation for Vehicular Ad Hoc Networks in Signalised Arterials. In: Gaj, P., Kwiecień, A., Sawicki, M. (eds) Computer Networks. CN 2017. Communications in Computer and Information Science, vol 718. Springer, Cham. https://doi.org/10.1007/978-3-319-59767-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-59767-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59766-9

  • Online ISBN: 978-3-319-59767-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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