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An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
by
Martinez, Francisco
, Cano, Juan-Carlos
, Calafate, Carlos
, Sanguesa, Julio
, Fogue, Manuel
, Garrido, Piedad
, Manzoni, Pietro
in
Beacons
/ Cameras
/ Density
/ Estimates
/ Information systems
/ Infrastructure
/ Messages
/ Roads & highways
/ Sensors
/ Simulation
/ Urban environments
/ VANETs
/ Vehicles
/ vehicular density estimation
/ vehicular networks
/ warning message dissemination
/ Wireless communication
/ Wireless communications
2013
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An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
by
Martinez, Francisco
, Cano, Juan-Carlos
, Calafate, Carlos
, Sanguesa, Julio
, Fogue, Manuel
, Garrido, Piedad
, Manzoni, Pietro
in
Beacons
/ Cameras
/ Density
/ Estimates
/ Information systems
/ Infrastructure
/ Messages
/ Roads & highways
/ Sensors
/ Simulation
/ Urban environments
/ VANETs
/ Vehicles
/ vehicular density estimation
/ vehicular networks
/ warning message dissemination
/ Wireless communication
/ Wireless communications
2013
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Do you wish to request the book?
An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
by
Martinez, Francisco
, Cano, Juan-Carlos
, Calafate, Carlos
, Sanguesa, Julio
, Fogue, Manuel
, Garrido, Piedad
, Manzoni, Pietro
in
Beacons
/ Cameras
/ Density
/ Estimates
/ Information systems
/ Infrastructure
/ Messages
/ Roads & highways
/ Sensors
/ Simulation
/ Urban environments
/ VANETs
/ Vehicles
/ vehicular density estimation
/ vehicular networks
/ warning message dissemination
/ Wireless communication
/ Wireless communications
2013
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An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
Journal Article
An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
2013
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Overview
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.
Publisher
MDPI AG,Molecular Diversity Preservation International (MDPI)
Subject
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