Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve traffic flow and eventually reshape the driving cycle of a typical commute. In this paper, we use a corridor consisting of a four-way intersection, a merging roadway, and a speed reduction zone to evaluate and quantify the impact of CAVs on a typical driving cycle. First, we use conventional vehicles that travel through this corridor to identify the baseline driving cycle, and then we use CAVs to determine how the baseline driving cycle is altered. We introduce specific metrics to quantitatively characterize a driving cycle and use these metrics to prescribe the new class of driving cycles for CAVs.


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    Titel :

    Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles


    Beteiligte:


    Erscheinungsdatum :

    2018-11-01


    Format / Umfang :

    796491 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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