An analysis of the Texas vehicle fleet and development of a vehicle operating cost model for use in transportation planning

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2011-05

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Abstract

Vehicle operating costs are an invaluable tool to transportation engineers, who utilize them in applications such as cost-benefit analyses and utilization pricing. Many of the existing models in use, however, are significantly out-of-date with current technology.
Research was undertaken in partnership with the Texas Department of Transportation (TxDOT) to develop a new model of the operating costs associated with Texas vehicle fleets. A vehicle operating cost (Vcost) model was produced which estimates variable and fixed costs associated with both light-duty and heavy-duty vehicles. The model calculates both aggregate fleet costs and costs for individual representative vehicles. An analysis of Texas Vehicles, Titles, and Registration (VTR) records; Weigh-in-Motion data; vehicle counts; and national car sales data was used to generate the breakdown of the Texas fleet of vehicles and to determine representative vehicles. Operational costs for these vehicles fell into two main categories: fixed costs (depreciation, financing, insurance, and other) and variable costs (fuel and maintenance/repair). Relations were determined for each cost category for each representative vehicle over its entire operational age. In the case of heavy-duty vehicles, much of the operational costs information is proprietary and had to be gathered in survey work conducted with other members of a research team. A computer program was written that incorporates the cost relations for the representative vehicles as well as the Texas fleet characteristics in such a way that the user can examine the costs of both an individual vehicle and the aggregate costs associated with a fleet of vehicles. The user can also input a default fleet composition. The model allows users to alter key parameters (such as fuel price, financing rates, insurance costs, or vehicle fuel economies) for future adaptability to a changing economic and technological landscape. The model was developed in parallel with another researcher working on an advanced fuel consumption model, which would later be integrated into to the Vcost model.

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