Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions

Karagiannis, Georgios; Altintas, Onur; Ekici, Eylem; Heijenk, Geert; Jarupan, Boangoat; Lin, Kuo‐Hung; Weil, Tim

doi:10.1109/surv.2011.061411.00019

Cited by 1,353 publications

(755 citation statements)

References 106 publications

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“…P is the probability of choosing path i of vehicle j with the parameter of temperature T, (3) where:…”

Section: Algorithm To Collect and Transmit Data In The Rsumentioning

confidence: 99%

“…Intelligent transport systems use advances in techonology in the area of processing, sensing and communication in order to monitor traffic conditions in a particular region to manage traffic and reduce congestion as well as reduce the number of road accidents. In addition, they can be used to provide information and entertainment services to drivers and passengers in order to make their journey a more pleasant process [2,3]. A Vehicular Network is an important component in an ITS.…”

Section: Introductionmentioning

confidence: 99%

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Algorithms for Traffic Management in the Intelligent Transport Systems

Nikolaev¹,

Aung²,

Myo³

et al. 2017

IJAS

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Traffic jams interfere with the drivers and cost billions of dollars per year and lead to a substantial increase in fuel consumption. In order to avoid such problems the paper describes the algorithms for traffic management in intelligent transportation system, which collects traffic information in real time and is able to detect and manage congestion on the basis of this information. The results show that the proposed algorithms reduce the average travel time, emissions and fuel consumption.In particular, travel time has decreased by about 23%, the average fuel consumption of 9%, and the average emission of 10%.

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“…P is the probability of choosing path i of vehicle j with the parameter of temperature T, (3) where:…”

Section: Algorithm To Collect and Transmit Data In The Rsumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Algorithms for Traffic Management in the Intelligent Transport Systems

Nikolaev¹,

Aung²,

Myo³

et al. 2017

IJAS

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“…However, vehicular communications represent novel challenges for wireless networks [39]. On one hand, as critical data for traffic safety is handled, stringent requirements in terms of latency and reliability are needed.…”

Section: K Vehicular Communicationsmentioning

confidence: 99%

5G – Wireless Communications for 2020

Barreto

Faria²,

Almeida³

et al. 2016

JCIS

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Abstract-Existing cellular technologies are rapidly coming to their performance limits. This is due not only to the growth in data traffic and in the number of connected terminals, but also because we are on the verge of new era, where everyone and everything will be connected, with more demanding and varied requirements that cannot be satisfied by current networks. On account of this, efforts are being made all over the world to design new wireless technologies that will support the expected demands for the next decade. These technologies, embraced under the commercial name of 5 th generation, are currently being studied, and in this tutorial paper we will give an overview of the main trends that are likely to make their way in the next-generation standards.

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“…However, [46] unrealistically considers fixed velocities for all mobile scatterers and [47] unrealistically considers totally random directions of movement of mobile scatterers (i.e., uniformly distributed) 1 and unrealistically equal amplitudes for all diffuse multipath components. Also [46] and [47] focus on analyzing ACF and PSD only and not LCR and AFD.…”

Section: Stochastic Channel Modelsmentioning

confidence: 99%

“…The Rayleigh PDF is appropriate when multipath propagation occurs in dense scattering environments such as V-V channels under heavy traffic with obstructed LOS path [56]. The existence of one specular component, i.e., 1 s L  , with deterministic amplitude, 1 b , together with the diffuse part of equation (10) leads to a Rice PDF [49, Ch. (5)].…”

Section: A First Order Statistical Characterizationmentioning

confidence: 99%

Generic stochastic modeling of vehicle-to-vehicle wireless channels

Karadimas

Matolak

2014

Vehicular Communications

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We present a generic statistical characterization of the vehicle-to-vehicle (V-V) wireless channel by adopting a stochastic modeling approach. Our approach is based on the doubly underspread (DU) property of non-wide sense stationary uncorrelated scattering (non-WSSUS) wireless channels, with V-V channels pertaining to this category. DU channels exhibit explicit frequency and time intervals over which they are approximated as WSSUS. We call these intervals restricted time interval (RTI) and restricted bandwidth (RBW), and variations taking place inside them are characterized as small scale variations. Large scale variations take place outside RTI and RBW. In this paper, we focus on small scale variations, thus, our modeling finds its applicability within RTI and RBW. As practical V-V channels exhibit rapid

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Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions

Cited by 1,353 publications

References 106 publications

Algorithms for Traffic Management in the Intelligent Transport Systems

Algorithms for Traffic Management in the Intelligent Transport Systems

5G – Wireless Communications for 2020

Generic stochastic modeling of vehicle-to-vehicle wireless channels

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