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Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

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  • Musti, Sashank
  • Kockelman, Kara M.
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    Abstract

    In today's world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin's personal-fleet evolution. Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle's emissions, more strongly than they respond to information on fuel cost savings. Twenty five-year simulations of Austin's household vehicle fleet suggest that, under all scenarios modeled, Austin's vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet's VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO2 emissions by 30% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin's current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 45 (2011)
    Issue (Month): 8 (October)
    Pages: 707-720

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    Handle: RePEc:eee:transa:v:45:y:2011:i:8:p:707-720

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    Related research

    Keywords: Vehicle fleet evolution Vehicle ownership Plug-in Hybrid Electric Vehicles (PHEVs) Climate change policy Stated preference Opinion survey;

    References

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    Cited by:
    1. Gardner, Lauren M. & Duell, Melissa & Waller, S. Travis, 2013. "A framework for evaluating the role of electric vehicles in transportation network infrastructure under travel demand variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 76-90.
    2. Brand, Christian & Anable, Jillian & Tran, Martino, 2013. "Accelerating the transformation to a low carbon passenger transport system: The role of car purchase taxes, feebates, road taxes and scrappage incentives in the UK," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 132-148.
    3. Hirte, Georg & Tscharaktschiew, Stefan, 2013. "The optimal subsidy on electric vehicles in German metropolitan areas: A spatial general equilibrium analysis," Energy Economics, Elsevier, vol. 40(C), pages 515-528.
    4. Ziegler, Andreas, 2012. "Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1372-1385.
    5. Hackbarth, André & Madlener, Reinhard, 2011. "Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis," FCN Working Papers 20/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. Krupa, Joseph S. & Rizzo, Donna M. & Eppstein, Margaret J. & Brad Lanute, D. & Gaalema, Diann E. & Lakkaraju, Kiran & Warrender, Christina E., 2014. "Analysis of a consumer survey on plug-in hybrid electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 14-31.
    7. Campbell, Amy R. & Ryley, Tim & Thring, Rob, 2012. "Identifying the early adopters of alternative fuel vehicles: A case study of Birmingham, United Kingdom," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1318-1327.
    8. Schwanen, Tim & Banister, David & Anable, Jillian, 2011. "Scientific research about climate change mitigation in transport: A critical review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(10), pages 993-1006.

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