IEEE Transactions on Vehicular Technology (IEEE T VEH TECHNOL)

Publisher: Vehicular Technology Society; Institute of Electrical and Electronics Engineers; IEEE Vehicular Technology Group, Institute of Electrical and Electronics Engineers

Journal description

Land, airborne, and maritime mobile services; portable or hand-carried and citizens' communications services, when used as an adjunct to a vehicular system; vehicular electrotechnology, equipment, and systems ordinarily identified with the automotive industry, excluding systems associated with public transit.

Current impact factor: 2.64

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 2.642
2012 Impact Factor 2.063
2011 Impact Factor 1.921
2010 Impact Factor 1.485
2009 Impact Factor 1.488
2008 Impact Factor 1.308
2007 Impact Factor 1.191
2006 Impact Factor 1.071
2005 Impact Factor 0.86
2004 Impact Factor 0.611
2003 Impact Factor 0.861
2002 Impact Factor 1.22
2001 Impact Factor 0.776
2000 Impact Factor 0.735
1999 Impact Factor 0.902
1998 Impact Factor 0.67
1997 Impact Factor 0.812
1996 Impact Factor 0.769
1995 Impact Factor 0.627
1994 Impact Factor 0.796
1993 Impact Factor 1.095
1992 Impact Factor 0.879

Impact factor over time

Impact factor
Year

Additional details

5-year impact 2.02
Cited half-life 4.90
Immediacy index 0.25
Eigenfactor 0.03
Article influence 0.80
Website IEEE Transactions on Vehicular Technology website
Other titles IEEE transactions on vehicular technology, Transactions on vehicular technology, Vehicular technology
ISSN 0018-9545
OCLC 1644964
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Institute of Electrical and Electronics Engineers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
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    • If funding rules apply authors may post Author's post-print version in funder's designated repository
    • Author's Post-print - Publisher copyright and source must be acknowledged with citation (see above set statement)
    • Author's Post-print - Must link to publisher version with DOI
    • Publisher's version/PDF cannot be used
    • Publisher copyright and source must be acknowledged
  • Classification
    ‚Äč green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Vehicular Ad hoc NETworks (VANETs) belong to a class of complex networks due to constant addition and deletion of nodes. Stimulating cooperation in these networks is a research challenge due to this uncertainty. The reason is that the node behavior is highly influenced by the neighborhood structure. Game theory has been significantly used to model ad hoc networks and optimize cooperation. However, in vehicular interactions, apart from the individual node behavior, networking properties play a vital role in the evolution of cooperation. This paper presents a public goods game (PGG) group interaction model for vehicular networks. We analyze how networking properties can impact the diffusion of cooperation. Simulation results show that higher network connectivity induces higher clustering in the network. This influences the probability of nodes receiving common packets from the neighborhood. The average path length proportional to clustering impacts the benefit sharing in the neighborhood. Results show that cooperation diffusion in these networks cannot be forced but evolves with different networking conditions.
    IEEE Transactions on Vehicular Technology 05/2015; 64(5):2015-2022. DOI:10.1109/TVT.2014.2334655
  • [Show abstract] [Hide abstract]
    ABSTRACT: Data aggregation has been recognized as an effective technique for reducing communication costs while obtaining useful aggregated information. In this paper, we study the crucial problem of delay-constrained data aggregation in vehicular ad hoc networks (VANETs), which has not been well studied in the literature. With the analysis based on real traces, we observe that there is heterogeneity with node contact patterns, which indicates that some nodes contact other nodes more frequently. Motivated by this observation, we propose an approach called aTree. The centralized aTree first constructs a data aggregation tree based on the shortest path tree and then assigns a waiting time budget to each node on the tree based on dynamic programming. We further develop a distributed aTree, in which a shortest path tree is built in a distributed fashion, and nodes determine their waiting time budgets collaboratively. We have performed extensive simulations on real taxi traces, and results show that our aTree schemes incur much lower transmission overhead while achieving the same performance compared with other schemes.
    IEEE Transactions on Vehicular Technology 05/2015; 64(5):2097-2107. DOI:10.1109/TVT.2014.2335232