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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    Title :

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


    Additional title:

    J. BAI ET AL.
    TRANSPORTATION LETTERS


    Contributors:
    Bai, Jun (author) / Mao, Suyi (author) / Lee, Jaeyoung Jay (author)

    Published in:

    Transportation Letters ; 17 , 4 ; 702-718


    Publication date :

    2025-04-21


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English