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A Smart Algorithm for CO2 Emissions Reduction on Realistic Traffic Scenarios Exploiting VANET Architecture

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Multimedia Communications, Services and Security (MCSS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1284))

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Abstract

In this paper, a smart vehicular traffic management through Vehicular Ad-hoc NETworks (VANETs) infrastructure and communications (V2I and V2V) is propose. A distributed algorithm called SeaWave with the aim to build less congested path for the vehicles in a urban scenario has been developed. It is also considered the problem regarding to enhance air quality around the cities reducing the vehicles CO2 emissions. There are different causes related to the CO2 emissions such as the average travelled time spent by vehicles inside the city and their average speed. Hence, with a better traffic management the average time spent by the vehicles in the city will be considerably reduced as well as CO2 emissions. These results are demonstrated in a discrete events simulator by using real traffic data. In particular, we used a congested scenario related a morning peak hour for the Bologna’s City.

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Authors and Affiliations

  1. University of Calabria, P. Bucci 39/C, Rende, CS, Italy

    Cesare Sottile & Nicola Cordeschi

  2. University of Trieste, Piazzale Europa, 1, 34127, Trieste, FVG, Italy

    Danilo Amendola

Authors
  1. Cesare Sottile
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  2. Nicola Cordeschi
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  3. Danilo Amendola
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Corresponding author

Correspondence to Nicola Cordeschi .

Editor information

Editors and Affiliations

  1. AGH University of Science and Technology, Kraków, Poland

    Andrzej Dziech

  2. Royal Military Academy, Brussels, Belgium

    Wim Mees

  3. Gdańsk University of Technology, Gdańsk, Poland

    Andrzej Czyżewski

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Sottile, C., Cordeschi, N., Amendola, D. (2020). A Smart Algorithm for CO2 Emissions Reduction on Realistic Traffic Scenarios Exploiting VANET Architecture. In: Dziech, A., Mees, W., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2020. Communications in Computer and Information Science, vol 1284. Springer, Cham. https://doi.org/10.1007/978-3-030-59000-0_9

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  • DOI: https://doi.org/10.1007/978-3-030-59000-0_9

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