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Congestion Rate Estimation for VANET Infrastructure using Fuzzy Logic

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Published:25 March 2017Publication History

ABSTRACT

Rapid Urbanization and higher usage of private transport has led to increase in vehicular traffic in cities across the globe. However, there has been no drastic improvement in terms of the resources to monitor and regulate the vehicular traffic. This leads to frequent congestion in roads and the delay in reaching any destination within the city limits has become inevitable. One of the advancements in wireless technologies to address this issue is Vehicular Ad-hoc Network (VANET) Infrastructure. As one among the service application of VANET, the Congestion Rate (CR) information is essential for travelers to make adaptive decisions and avoid overcrowding. This paper proposes a novel approach to calculate CR in a target geographic area for the smart vehicles of VANET Infrastructure using fuzzy based controllers. In addition, this paper proposes a novel method to reduce the computational complexity owing to the irregularity of traffic and frequent updation of CR value in VANET. Further, simulation models of moderate traffic were created using VISSIM and their corresponding CR values are evaluated using fuzzy logic controller in MATLAB. The results also show that the proposed selective updating algorithm reduces the CR updation by 85% in comparison with conventional periodic updation.

References

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  • Published in

    cover image ACM Other conferences
    ISMSI '17: Proceedings of the 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence
    March 2017
    171 pages
    ISBN:9781450347983
    DOI:10.1145/3059336

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    Publication History

    • Published: 25 March 2017

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