Abstract Traffic oscillation, a traffic phenomenon that generates many carbon emissions, originates from the amplification of traffic disturbance. The connected and automated vehicle (CAV) technology may help to weaken oscillations and reduce carbon emissions from mixed traffic. This paper explores the effects of various characteristics of disturbances and mixed platoons on CO2 emissions under different disturbance types. The results indicate that the addition of even only one CAV reduces carbon emissions under some disturbances. The disturbance types that make mixed traffic increase carbon emissions have also been identified. Diverse disturbance characteristics play different essential roles in ecological impacts of CAVs. The platoon characteristics such as CAV's position in a platoon and the heterogeneity of human factors, affect the extent of carbon emission reduction. Based on these findings, this paper proposes optimization recommendations for CAV cooperative eco-driving and green traffic management.


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    Titel :

    Carbon Emission Impacts of Longitudinal Disturbance on Low-penetration Connected Automated Vehicle Environments


    Beteiligte:
    Zong, Fang (Autor:in) / Yue, Sheng (Autor:in)


    Erscheinungsdatum :

    2023-09-05




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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