Lane changing is one of the basic driving behaviours, which may induce traffic oscillations and incidents. However, it is difficult to well model the lane-changing decision process due to the complex traffic status. To promote the prediction accuracy of lane-changing decisions, this paper presents a probability lane-changing model by taking into account the memory effect. That is, the lane-changing decision model considers a series of trajectory data rather than the data of a specific time utilized in most existing models. Furthermore, the drivers are classified in terms of lane-changing trajectories, which is expected to further promote the prediction accuracy of the lane-changing decision model. Calibrations and validations are carried out based on the NGSIM data, which indicate that the proposed model can significantly promote the prediction accuracy of lane-changing decisions.


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    Titel :

    A probability lane-changing model considering memory effect and driver heterogeneity


    Beteiligte:
    Pang, Meng-Yuan (Autor:in) / Jia, Bin (Autor:in) / Xie, Dong-Fan (Autor:in) / Li, Xin-Gang (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2020-01-02


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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