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ABSTRACT: A thorough understanding of the communications channel between vehicles is essential for realistic modeling of Vehicular Ad Hoc Networks (VANETs) and the development of related technology and applications. The impact of vehicles as obstacles on vehicle-to-vehicle (V2V) communication has been largely neglected in VANET research, especially in simulations. Useful models accounting for vehicles as obstacles must satisfy a number of requirements, most notably accurate positioning, realistic mobility patterns, realistic propagation characteristics, and manageable complexity. We present a model that satisfies all of these requirements. Vehicles are modeled as physical obstacles affecting the V2V communication. The proposed model accounts for vehicles as three-dimensional obstacles and takes into account their impact on the LOS obstruction, received signal power, and the packet reception rate. We utilize two real world highway datasets collected via stereoscopic aerial photography to test our proposed model, and we confirm the importance of modeling the effects of obstructing vehicles through experimental measurements. Our results show considerable obstruction of LOS due to vehicles. By obstructing the LOS, vehicles induce significant attenuation and packet loss. The algorithm behind the proposed model allows for computationally efficient implementation in VANET simulators. It is also shown that by modeling the vehicles as obstacles, significant realism can be added to existing simulators with clear implications on the design of upper layer protocols.
IEEE Journal on Selected Areas in Communications 01/2011; 29:15-28. · 3.41 Impact Factor
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2011 IEEE Vehicular Networking Conference, IEEE VNC 2011, Amsterdam, The Netherlands, November 14-16, 2011; 01/2011
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Proceedings of the Second IEEE Vehicular Networking Conference, VVNC 2010, Jersey City, New Jersey, USA, December 13-15, 2010; 01/2010
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IEEE Communications Letters. 01/2009; 13:995-997.
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ABSTRACT: Aiming at a realistic mobile connectivity model for vehicular sensor networks in urban environments, we propose the combination
of large-scale traffic simulation and computational tools to characterize fundamental graph-theoretic parameters. To illustrate
the proposed approach, we use the DIVERT simulation framework to illuminate the temporal evolution of the average node degree
in this class of networks and provide an algorithm for computing the transitive connectivity profile that ultimately determines
the flow of information in a vehicular sensor network.
06/2008: pages 112-125;
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Proceedings of the 2008 ACM Symposium on Applied Computing (SAC), Fortaleza, Ceara, Brazil, March 16-20, 2008; 01/2008
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ABSTRACT: Channel models for vehicular networks typically disregard the effect of vehicles as physical obstructions for the wireless signal. We aim to clarify the validity of this simplification by quantifying the impact of obstructions through a series of wireless experiments. Using two cars equipped with Dedicated Short Range Communications (DSRC) hardware designed for vehicular use, we perform experimental measurements in or-der to collect received signal power and packet delivery ratio information in a multitude of relevant scenarios: parking lot, highway, suburban and urban canyon. Upon separating the data into line of sight (LOS) and non-line of sight (NLOS) categories, our results show that obstructing vehicles cause significant impact on the channel quality. A single obstacle can cause a drop of over 20 dB in received signal strength when two cars communicate at a distance of 10 m. At longer distances, NLOS conditions affect the usable range of communication, effectively halving the distance at which communication can be achieved with 90% chance of success. The presented results motivate the inclusion of vehicles in the radio propagation models used for VANET simulation in order to increase the level of realism.
