Driver is a key component in vehicle simulation. An ideal driver model simulates driving patterns a human driver may perform to negotiate road profiles. There are simulation packages having the capability to simulate driver behavior. However, it is rarely documented how they work with road profiles. This paper proposes a new truck driver model for vehicle simulation to imitate actual driving behavior in negotiating road grade and curvature.The proposed model is developed based upon Gipps' car-following model. Road grade and curvature were not considered in the original Gipps' model although it is based directly on driver behavior and expectancy for vehicles in a stream of traffic. New parameters are introduced to capture drivers' choice of desired speeds that they intend to use in order to negotiating road grade and curvature simultaneously. With the new parameters, the proposed model can emulate behaviors like uphill preparation for different truck drivers. Speed variation while cruising can be explained by the empirical model and therefore facilitating a better estimation of performance in vehicle simulation. Actual driving data, collected in an 89-km section of I-40 around Ashville, NC area from a Heavy Truck Duty Cycle (HTDC) project, were used to calibrate the proposed model. Root-mean-square error of speed along the section is used to evaluate the estimation and it can be as good as 4.76 km/hr. In considering performance over the 89-km hilly section, the model shows promising results in describing the impact of road grade and curvature on truck driving for vehicle simulation.


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    Titel :

    Modeling the Impact of Road Grade and Curvature on Truck Driving for Vehicle Simulation


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Smith, David (Autor:in) / Li, Jan-Mou (Autor:in)

    Kongress:

    SAE 2014 World Congress & Exhibition ; 2014



    Erscheinungsdatum :

    2014-04-01




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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