Efforts in estimating emissions by an integration of traffic simulation models and emissions models have become a fast-evolving research area. However, because of the lack of effective methods and indicators to characterize traffic behaviors, the accuracy of emissions by such an approach has not been effectively verified or evaluated. The current study is intended to examine the applicability of traffic microsimulation models in vehicle emissions estimates on the basis of the explanatory parameter of vehicle emissions—the vehicle-specific power (VSP) distribution. Analyzing massive real-world and simulated vehicle activity data showed that the results from traffic simulation could not represent real-world driving behaviors for emissions estimates. The simulated vehicle- specific power distribution led to errors that were as high as 82.8%, 53.6%, and 29.6% for nitrogen oxides, hydrocarbons, and carbon monoxide emissions, respectively. Then a sensitivity analysis of 16 adjustments on eight parameters of simulation models was conducted to determine their effects on simulated VSP distributions: systematic errors existed in the use of traffic simulation models to represent second-by-second driving behaviors. The errors could not be reduced by parameter calibration on the simulation model. This study concluded that the traditional approach of integrating traffic simulation models with emissions models was not applicable for vehicle emissions estimates. The primary reasons for the errors need to be investigated further from the internal mechanism of submodels of microsimulation. On the basis of these findings, several recommendations are proposed for future studies.


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    Title :

    Applicability of Traffic Microsimulation Models in Vehicle Emissions Estimates


    Subtitle :

    Case Study of VISSIM


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Song, Guohua (author) / Yu, Lei (author) / Zhang, Yanhong (author)


    Publication date :

    2012-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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