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Impact of Driver Reaction and Penetration Rate on GLOSA

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Communication Technologies for Vehicles (Nets4Cars/Nets4Trains/Nets4Aircraft 2019)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11461))

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Abstract

Cooperative Intelligent Transport Systems (C-ITS) aim to provide innovative solutions that can contribute to a better road management. Green Light Optimal Speed Advisory (GLOSA) is one of the traffic efficiency ITS services that can enhance traffic fluidity and fuel consumption economy. In this paper, we present driver reaction impact on GLOSA performance through a realistic simulation scenario taking into account the variation of penetration rate. In our work, we use vehicular network architecture ITS-G5 and we test our simple segment approach algorithm under a realistic traffic topology. Results show that driver reaction can significantly influence GLOSA performance in terms of fuel consumption and number of stopped vehicles.

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Notes

  1. 1.

    https://github.com/riebl/artery.

  2. 2.

    https://www.openstreetmap.org/#map=17/44.86316/-0.65115.

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Acknowledgement

This work is supported by C-ROADS France European project.

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Correspondence to Gerard Chalhoub .

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Karoui, M., Freitas, A., Chalhoub, G. (2019). Impact of Driver Reaction and Penetration Rate on GLOSA. In: Hilt, B., Berbineau, M., Vinel, A., Jonsson, M., Pirovano, A. (eds) Communication Technologies for Vehicles. Nets4Cars/Nets4Trains/Nets4Aircraft 2019. Lecture Notes in Computer Science(), vol 11461. Springer, Cham. https://doi.org/10.1007/978-3-030-25529-9_2

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  • DOI: https://doi.org/10.1007/978-3-030-25529-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-25528-2

  • Online ISBN: 978-3-030-25529-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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