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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A genetic fuzzy system for modeling mandatory lane changing


    Contributors:
    Hou, Yi (author) / Edara, Praveen (author) / Sun, Carlos (author)


    Publication date :

    2012-09-01


    Size :

    644102 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    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

    Free access

    Efficient Mandatory Lane Changing of Connected and Autonomous Vehicles

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