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GER-EN – GNSS Error Reduction Using an Elastic Network Based on V2V and LiDAR

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Cyberspace Safety and Security (CSS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11161))

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Abstract

Vehicle2Vehicle is an emerging and promising research area, with several applications in IoT and in self-driving vehicles. It allows vehicle to establish ad-hoc connections for information sharing and improve users security while driving. V2V systems are strongly dependent on localization accuracy. In a common outdoor scenario, it is possible to use satellite-based navigation systems in order to determine user position in space, but the accuracy may vary due to interferences and when the sky visibility is sub-optimal.

In this paper we present GER-EN – GNSS Error Reduction using an Elastic Network based on V2V and LiDAR, a novel methodology for reducing satellite-based systems error using a combination of V2V, LiDAR-based distances and an elastic graph generated by the vehicles in the area.

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Authors and Affiliations

  1. Università degli Studi di Napoli Federico II, Naples, Italy

    Walter Balzano & Fabio Vitale

Authors
  1. Walter Balzano
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  2. Fabio Vitale
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Corresponding author

Correspondence to Walter Balzano .

Editor information

Editors and Affiliations

  1. University of Salerno, Fisciano, Italy

    Arcangelo Castiglione

  2. University Politehnica of Bucharest, Bucharest, Romania

    Florin Pop

  3. University of Campania “L. Vanvitelli”, Caserta, Italy

    Massimo Ficco

  4. University of Salerno, Fisciano, Italy

    Francesco Palmieri

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Balzano, W., Vitale, F. (2018). GER-EN – GNSS Error Reduction Using an Elastic Network Based on V2V and LiDAR. In: Castiglione, A., Pop, F., Ficco, M., Palmieri, F. (eds) Cyberspace Safety and Security. CSS 2018. Lecture Notes in Computer Science(), vol 11161. Springer, Cham. https://doi.org/10.1007/978-3-030-01689-0_10

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  • DOI: https://doi.org/10.1007/978-3-030-01689-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01688-3

  • Online ISBN: 978-3-030-01689-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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