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Sensors 2013, 13(2), 2399-2418; doi:10.3390/s130202399

An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments

1,* , 2
1 DIIS, University of Zaragoza, Ciudad Escolar s/n, Teruel 44003, Spain 2 DISCA, Universitat Polit'ecnica de Val'encia, Camino de Vera s/n, Valencia 46022, Spain
* Author to whom correspondence should be addressed.
Received: 8 January 2013 / Revised: 25 January 2013 / Accepted: 30 January 2013 / Published: 11 February 2013
(This article belongs to the Section Physical Sensors)
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In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes.
Keywords: vehicular networks; vehicular density estimation; warning message dissemination; VANETs vehicular networks; vehicular density estimation; warning message dissemination; VANETs
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Sanguesa, J.A.; Fogue, M.; Garrido, P.; Martinez, F.J.; Cano, J.-C.; Calafate, C.T.; Manzoni, P. An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments. Sensors 2013, 13, 2399-2418.

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