(Created page with " == Abstract == The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39247-4_6 Road traffic is experiencing a drastic increase in recent ye...")
 
 
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== Abstract ==
 
== Abstract ==
  
The final publication is available at Springer via  http://dx.doi.org/10.1007/978-3-642-39247-4_6 Road traffic is experiencing a drastic increase in recent years, thereby increasing the every day traffic congestion problems, especially in cities. Vehicle density is one of the main metrics used for assessing the road traffic conditions. Currently, most of the existing vehicle density estimation approaches, such as inductive loop detectors or traffic surveillance cameras, require infrastructure-based traffic information systems to be installed at various locations. In this paper, we present I-VDE, a solution to estimate the density of vehicles that has been specially designed for Vehicular Networks. Our proposal allows Intelligent Transportation Systems to continuously estimate the vehicular density by accounting for the number of beacons received per Road Side Unit, as well as the roadmap topology. Simulation results indicate that our approach accurately estimates the vehicular density, and therefore automatic traffic controlling systems may use it to predict traffic jams and introduce countermeasures. Barrachina Villalba, J.; Garrido Picazo, MP.; Fogue, M.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). I-VDE: A Novel Approach to Estimate Vehicular Density by Using Vehicular Networks. En Ad-hoc, Mobile, and Wireless Network. Springer. 63-74. doi:10.1007/978-3-642-39247-4_6 Senia 63 74
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The final publication is available at Springer via  http://dx.doi.org/10.1007/978-3-642-39247-4_6 Road traffic is experiencing a drastic increase in recent years, thereby increasing the every day traffic congestion problems, especially in cities. Vehicle density is one of the main metrics used for assessing the road traffic conditions. Currently, most of the existing vehicle density estimation approaches, such as inductive loop detectors or traffic surveillance cameras, require infrastructure-based traffic information systems to be installed at various locations. In this paper, we present I-VDE, a solution to estimate the density of vehicles that has been specially designed for Vehicular Networks. Our proposal allows Intelligent Transportation Systems to continuously estimate the vehicular density by accounting for the number of beacons received per Road Side Unit, as well as the roadmap topology. Simulation results indicate that our approach accurately estimates the vehicular density, and therefore automatic traffic controlling systems may use it to predict traffic jams and introduce countermeasures. This work was partially supported by the Ministerio de Ciencia e Innovaci´on, Spain, under Grant TIN2011-27543-C03-01, as well as by the Fundaci´on Universitaria Antonio Gargallo (FUAG), and the Caja de Ahorros de la Inmaculada (CAI) Barrachina Villalba, J.; Garrido Picazo, MP.; Fogue, M.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). I-VDE: A Novel Approach to Estimate Vehicular Density by Using Vehicular Networks. En Ad-hoc, Mobile, and Wireless Network. Springer. 63-74. doi:10.1007/978-3-642-39247-4_6 S 63 74
 
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Document type: Part of book or chapter of book
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== Full document ==
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<pdf>Media:Draft_Content_857915373-beopen774-2109-document.pdf</pdf>
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* [https://riunet.upv.es/bitstream/10251/71132/3/paper_adhocnow_v2_Calafate.pdf https://riunet.upv.es/bitstream/10251/71132/3/paper_adhocnow_v2_Calafate.pdf]
 
* [https://riunet.upv.es/bitstream/10251/71132/3/paper_adhocnow_v2_Calafate.pdf https://riunet.upv.es/bitstream/10251/71132/3/paper_adhocnow_v2_Calafate.pdf]
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* [http://link.springer.com/content/pdf/10.1007/978-3-642-39247-4_6 http://link.springer.com/content/pdf/10.1007/978-3-642-39247-4_6],
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: [http://dx.doi.org/10.1007/978-3-642-39247-4_6 http://dx.doi.org/10.1007/978-3-642-39247-4_6] under the license http://www.springer.com/tdm
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* [https://riunet.upv.es/handle/10251/71132 https://riunet.upv.es/handle/10251/71132],
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: [https://link.springer.com/10.1007/978-3-642-39247-4_6 https://link.springer.com/10.1007/978-3-642-39247-4_6],
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: [https://www.scipedia.com/public/Barrachina_Villalba_et_al_2013a https://www.scipedia.com/public/Barrachina_Villalba_et_al_2013a],
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: [https://dx.doi.org/10.1007/978-3-642-39247-4_6 https://dx.doi.org/10.1007/978-3-642-39247-4_6],
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: [http://dx.doi.org/10.1007/978-3-642-39247-4_6 http://dx.doi.org/10.1007/978-3-642-39247-4_6],
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: [https://dblp.uni-trier.de/db/conf/adhoc-now/adhoc-now2013.html#BarrachinaGFMCCM13 https://dblp.uni-trier.de/db/conf/adhoc-now/adhoc-now2013.html#BarrachinaGFMCCM13],
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: [https://academic.microsoft.com/#/detail/189734321 https://academic.microsoft.com/#/detail/189734321]

Latest revision as of 14:22, 21 January 2021

Abstract

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39247-4_6 Road traffic is experiencing a drastic increase in recent years, thereby increasing the every day traffic congestion problems, especially in cities. Vehicle density is one of the main metrics used for assessing the road traffic conditions. Currently, most of the existing vehicle density estimation approaches, such as inductive loop detectors or traffic surveillance cameras, require infrastructure-based traffic information systems to be installed at various locations. In this paper, we present I-VDE, a solution to estimate the density of vehicles that has been specially designed for Vehicular Networks. Our proposal allows Intelligent Transportation Systems to continuously estimate the vehicular density by accounting for the number of beacons received per Road Side Unit, as well as the roadmap topology. Simulation results indicate that our approach accurately estimates the vehicular density, and therefore automatic traffic controlling systems may use it to predict traffic jams and introduce countermeasures. This work was partially supported by the Ministerio de Ciencia e Innovaci´on, Spain, under Grant TIN2011-27543-C03-01, as well as by the Fundaci´on Universitaria Antonio Gargallo (FUAG), and the Caja de Ahorros de la Inmaculada (CAI) Barrachina Villalba, J.; Garrido Picazo, MP.; Fogue, M.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). I-VDE: A Novel Approach to Estimate Vehicular Density by Using Vehicular Networks. En Ad-hoc, Mobile, and Wireless Network. Springer. 63-74. doi:10.1007/978-3-642-39247-4_6 S 63 74


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-3-642-39247-4_6 under the license http://www.springer.com/tdm
https://link.springer.com/10.1007/978-3-642-39247-4_6,
https://www.scipedia.com/public/Barrachina_Villalba_et_al_2013a,
https://dx.doi.org/10.1007/978-3-642-39247-4_6,
http://dx.doi.org/10.1007/978-3-642-39247-4_6,
https://dblp.uni-trier.de/db/conf/adhoc-now/adhoc-now2013.html#BarrachinaGFMCCM13,
https://rd.springer.com/chapter/10.1007/978-3-642-39247-4_6,
https://academic.microsoft.com/#/detail/189734321
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Published on 01/01/2013

Volume 2013, 2013
DOI: 10.1007/978-3-642-39247-4_6
Licence: CC BY-NC-SA license

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