I vde a novel approach to estimate vehicular density by using vehicular networks

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://hdl.handle.net/10251/71132

• https://riunet.upv.es/bitstream/10251/71132/3/paper_adhocnow_v2_Calafate.pdf

• http://link.springer.com/content/pdf/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

• https://riunet.upv.es/handle/10251/71132,

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