Researchers have collected extensive vehicle activity data in Beijing using GPS and attempted to develop a comprehensive database of facility- and speed-specific operating mode (OpMode) distributions of various vehicle types for estimating on-road vehicle emissions. This study developed the specific OpMode distributions of light duty vehicles (LDVs) for both restricted access and unrestricted access road types at various average speeds for characteristic analysis. (1) Strong patterns are found in the variations in OpMode distributions with the increase in the average speed: the time fraction of Decelerating/Braking remains less than 7%. The fraction of Idling decreases dramatically from 95% to 0%, while the fraction of Cruising/Accelerating increases from 2% to 94%. The fraction of Coasting increases to 28% and then decreases. (2) The time fractions for restricted access and unrestricted access are significantly different at the same average speeds, especially in Operating Modes #0, #1, #11, #12, #13, #14, #21, and #22, possibly causing an error of 20% in the emissions estimations. (3) Taxis show different OpMode distributions than those for private cars in the operating modes of Decelerating/Braking, Idling, and high-VSP modes, especially at low average speeds. The differences are derived from the more skillful driving behaviors of taxi drivers and may cause an estimation error of over 10%. Thus, the activities of taxis and private cars should be modeled separately for on-road emissions estimations.


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    Title :

    Characteristics of operating mode distributions of light duty vehicles by road type, average speed, and driver type for estimating on-road emissions: Case study of Beijing


    Contributors:
    Zhai, Zhiqiang (author) / Song, Guohua (author) / Liu, Ying (author) / Cheng, Ying (author) / He, Weinan (author) / Yu, Lei (author)

    Published in:

    Publication date :

    2019-03-04


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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