A Fuzzy Logic-based lane changing model was developed for mandatory lane changes at lane drops. Genetic Algorithm was used for optimizing the widths of membership functions. The Next Generation Simulation (NGSIM) dataset of vehicle trajectories was used for model development and validation. The model performed better than a comparable binary Logit model in terms of predicting the merge and non-merge events. The model has applications in traffic simulation and driver assistance systems.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A genetic fuzzy system for modeling mandatory lane changing


    Beteiligte:
    Hou, Yi (Autor:in) / Edara, Praveen (Autor:in) / Sun, Carlos (Autor:in)


    Erscheinungsdatum :

    01.09.2012


    Format / Umfang :

    644102 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees

    Hou, Yi / Edara, Praveen / Sun, Carlos | IEEE | 2014




    Evolutionary Dynamics of Mandatory Lane Changing for Bus Exiting

    Ronghan Yao / Xiaojing Du / Wenyan Qi et al. | DOAJ | 2021

    Freier Zugriff

    Efficient Mandatory Lane Changing of Connected and Autonomous Vehicles

    Lin, Shang-Chien / Kung, Chia-Chu / Lin, Lee et al. | IEEE | 2021