In this paper, a rear-end collision control model is proposed using the fuzzy logic control scheme for the autonomous or cruising vehicles in Intelligent Transportation Systems (ITSs). Through detailed analysis of the car-following cases, our controller is established on some reasonable control rules. In addition, to refine the initialized fuzzy rules considering characteristics of the rear-end collisions, the genetic algorithm is introduced to reduce the computational complexity while maintaining accuracy. Numerical results indicate that our Genetic algorithm-optimized Fuzzy Logic Controller (GFLC) outperforms the traditional fuzzy logic controller in terms of better safety guarantee and higher traffic efficiency.


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    Titel :

    A Rear-End Collision Avoidance Scheme for Intelligent Transportation System


    Beteiligte:
    Chen Chen (Autor:in) / Liu Hongyun (Autor:in) / Xiang Hongyu (Autor:in) / Li Meilian (Autor:in) / Pei Qingqi (Autor:in) / Wang Shengda (Autor:in)


    Erscheinungsdatum :

    2016




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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