This paper proposes Enhanced Intelligent Driver Model for Adaptive Cruise Control (EIDM-ACC) vehicles, a novel car-following model that dynamically adjusts desired speed and considers acceleration inertia. The EIDM-ACC model is compared with two widely used models for simulating ACC vehicles – the ACC model developed by the PATH Project (PATH-ACC) at the University of California Transportation Institute and Continuous Asymmetric Optimal Velocity Relative Velocity (CAOVRV) model. Three models are calibrated and cross-validated using real vehicle trajectory data from the OpenACC dataset. Results show that the EIDM-ACC outperforms the other two models in small and large fluctuation stages. In addition, EIDM-ACC has better performance in capturing the instability and energy consumption of ACC vehicles, and also has advantages over the other two models in terms of safety.


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    Titel :

    A novel car-following model for adaptive cruise control vehicles using enhanced intelligent driver model


    Weitere Titelangaben:

    J. BAI ET AL.
    TRANSPORTATION LETTERS


    Beteiligte:
    Bai, Jun (Autor:in) / Mao, Suyi (Autor:in) / Lee, Jaeyoung Jay (Autor:in)

    Erschienen in:

    Transportation Letters ; 17 , 4 ; 702-718


    Erscheinungsdatum :

    21.04.2025


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch