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Inventi Impact: Fuzzy Systems

Articles

  • Inventi:efs/28950/19
    Fuzzy-Based Hybrid Location Algorithm for Vehicle Position in VANETs via Fuzzy Kalman Filtering Approach
    Research 2019 : July - September
    Jiyao An, Yingjun Yu, Jie Tang, Jiawei Zhan

    Location information is very critical to VANETs such as navigation, routing, network management, and road congestion. In this\npaper, the vehicle location problem under urban road conditions is investigated by employing the GPS,WiFi, and Cellular Network\n(CN) positioning systems and by developing neighbor vehicle utilization in VANETs. Since GPS is possibly affected by satellite\nsignal in real urban environment, whileWiFi is only suitable for urban and CN is affected by the number of Base Stations (BSs) and\nsignal strength, then a fuzzy-based hybrid location algorithm is developed.The algorithm has some advantages that it can enhance\nthese positioning features by establishing a new fuzzy-weighting location mechanism (FLM) and also can adjust dynamically the\nmeasurement noise covariance by making use of a novel fuzzy Kalman filtering method. Finally, experiment results are given to\nshow effectiveness and merit of the proposed approach.

    How to Cite this Article
    Attribution/ CC Compliant Citation: An, Jiyao, et al. \"Fuzzy-Based\nHybrid Location Algorithm for Vehicle Position in VANETs via\nFuzzy Kalman Filtering Approach.\" Advances in Fuzzy Systems\n2019 (2019).\nhttps://doi.org/10.1155/2019/5142937\nhttp://creativecommons.org/licenses/by/4.0/\nSome formatting elements, header, footer, logos, dates and\npagination were modified while adapting this article.
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