Utilizing vehicles' previous transmitted motion information through information communication technologies (ICT) wirelessly an anticipation-memory (AM) car following model is derived to investigate the effects of anticipating driving behaviour on vehicles' position, velocity, acceleration. The changes of space headway, velocity differences, and memory of driving to the preceding vehicle are presented as a parameters of driving anticipation in autonomous and connected vehicles (ACV) environment. The linear stability is carried out to study the qualitative properties of the AM model. The linear and nonlinear analysis support our newly developed model to illustrate the anticipation driving parameter based on previous motion information as feedback of driving in V2V environment which can effectively enhance the traffic flow stability, and the capacity of roads. All results depict that the AM model can potentially decrease the velocity fluctuations in a traffic flow system comparing to previous existing models.


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    Title :

    Nonlinear stability analysis for an anticipation-memory car following model in the era of autonomous and connected vehicles


    Contributors:


    Publication date :

    2020-04-01


    Size :

    159993 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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