The objective of this paper is to propose a vehicle emission prediction model based on trajectory data which considers the dispersion of vehicle speed. The sample data of US101 in NGSIM was used as input for MOVES to compute the vehicle emissions on freeway. Then regression analyses were conducted to explore the function forms of emission models based on trajectory data. The performance of the proposed model in prediction is well known through validation, and the estimation of emissions using the proposed model is extremely close to the accurate computation of MOVES. A contrastive analysis between three other methods in estimating total emissions shows that the estimation of emissions using the proposed model exceed these three emission models in estimating the vehicle emissions on freeway segments. The model can be applied for the practical engineering applications on freeways.


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    Titel :

    A Real-Time Vehicle Emission Prediction Model for Freeway Segments Based on Trajectory Data


    Beteiligte:
    Tu, Yu (Autor:in) / Wang, Wei (Autor:in) / Xu, Chengcheng (Autor:in)

    Kongress:

    18th COTA International Conference of Transportation Professionals ; 2018 ; Beijing, China


    Erschienen in:

    CICTP 2018 ; 2376-2384


    Erscheinungsdatum :

    2018-07-02




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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