With environmental degradation and energy security as serious concerns, it is important to anticipate how vehicle ownership and usage patterns can change under different policies and contexts. This work ascertains the acquisition, disposal, and use patterns of personal vehicles of a synthetic population over time and relies on microsimulation to anticipate fleet composition, usage, and greenhouse gas emissions under different settings. Twenty-five-year simulations predict the highest market share for plug-in hybrid electric vehicles (PHEVs), hybrid electric vehicles, and smart cars and the greatest reductions in carbon emissions under an increased gasoline price ($7/gal). Results under a “feebate” policy scenario (where fees apply to low-fuel-economy vehicles, and rebates rise with fuel economies above a threshold) indicated a shift toward fuel-efficient vehicles but with vehicle miles traveled (VMT) rising, thanks to lower driving costs. Excepting the low PHEV price and feebate policy simulations, all other scenarios predicted a lower fleet VMT value. The high-density scenario (job and household densities quadrupled) resulted in the lowest vehicle ownership levels and lower VMT values and emissions. The low-PHEV-price scenario resulted in higher shares of PHEVs but negligible impacts from greenhouse gas emissions. Adoption and widespread use of plug-in vehicles will depend on marketing, competitive pricing, government incentives, reliable driving-range reports, and charging infrastructure. Though just 29% of survey respondents stated support for a (specific) feebate policy, 35% indicated an interest in purchasing a PHEV if it cost just $6,000 more than its gasoline counterpart.


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    Title :

    Evolution of the Light-Duty Vehicle Fleet


    Subtitle :

    Anticipating Adoption of Plug-In Hybrid Electric Vehicles and Greenhouse Gas Emissions Across the U.S. Fleet


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2011-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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