IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v19y1985i4p347-358.html
   My bibliography  Save this article

Estimating daily vehicle usage distributions and the implications for limited-range vehicles

Author

Listed:
  • Greene, David L.

Abstract

Understanding the potential market for limited-range vehicles is important to planning research and development programs for electric and hybrid vehicles and for gaseous-fueled vehicles as well. Studies of consumer preferences and perceptions have shown vehicle range to be a very important vehicle attribute. Studies of household vehicle use, on the other hand, have suggested that the range requirements most households place on vehicles are quite modest. The latter, however, have been severely limited by the absence of longitudinal data on the usage of individual vehicles. Instead, they have relied on single-day surveys on many vehicles, an inappropriate data source. This study develops a method for estimating daily travel distributions for individual vehicles and applies it to a recent longitudinal survey of miles and days between refuelings for over 2000 vehicles. Every vehicle in the sample has at least 30 consecutive refueling intervals. A variety of measures of "range requirement" are defined and calculated. The results confirm the existence of a substantial potential market (20-50% of all household vehicles) for vehicles with ranges on the order of 100 miles. Future research using these data and this method could describe the nature of vehicles with limited-range needs and the households which own them.

Suggested Citation

  • Greene, David L., 1985. "Estimating daily vehicle usage distributions and the implications for limited-range vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 19(4), pages 347-358, August.
    • Handle: RePEc:eee:transb:v:19:y:1985:i:4:p:347-358
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0191-2615(85)90041-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Han Su & Qian Zhang & Wanying Wang & Xiaoan Tang, 2021. "A Driving Behavior Distribution Fitting Method Based on Two-Stage Hybrid User Classification," Sustainability, MDPI, vol. 13(13), pages 1-24, June.
    2. Lin, Zhenhong & Ou, Shiqi & Elgowainy, Amgad & Reddi, Krishna & Veenstra, Mike & Verduzco, Laura, 2018. "A method for determining the optimal delivered hydrogen pressure for fuel cell electric vehicles," Applied Energy, Elsevier, vol. 216(C), pages 183-194.
    3. Sperling, Daniel & Setiawan, Winardi & Hungerford, David, 1995. "The target market for methanol fuel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 29(1), pages 33-45, January.
    4. Plötz, Patrick & Jakobsson, Niklas & Sprei, Frances, 2017. "On the distribution of individual daily driving distances," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 213-227.
    5. Jiahang He & Toshiyuki Yamamoto, 2020. "Characterization of Daily Travel Distance of a University Car Fleet for the Purpose of Replacing Conventional Vehicles with Electric Vehicles," Sustainability, MDPI, vol. 12(2), pages 1-12, January.
    6. Verena Ehrler & Pierre Camilleri, 2021. "Optimising the acceptance of electric vehicles for urban logistics with evidence from France and Germany [Optimiser l’acceptation des véhicules électriques dans le domaine de la logistique urbaine ," Post-Print hal-03305264, HAL.
    7. Zhenhong Lin, 2014. "Optimizing and Diversifying Electric Vehicle Driving Range for U.S. Drivers," Transportation Science, INFORMS, vol. 48(4), pages 635-650, November.
    8. Shiqi Ou & Rujie Yu & Zhenhong Lin & Huanhuan Ren & Xin He & Steven Przesmitzki & Jessey Bouchard, 2020. "Intensity and daily pattern of passenger vehicle use by region and class in China: estimation and implications for energy use and electrification," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(3), pages 307-327, March.
    9. Eisenmann, Christine & Buehler, Ralph, 2018. "Are cars used differently in Germany than in California? Findings from annual car-use profiles," Journal of Transport Geography, Elsevier, vol. 69(C), pages 171-180.
    10. Golob, Thomas F. & Gould, Jane, 1998. "Projecting use of electric vehicles from household vehicle trials," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 441-454, September.
    11. Xuefang Li & Chenhui Liu & Jianmin Jia, 2019. "Ownership and Usage Analysis of Alternative Fuel Vehicles in the United States with the 2017 National Household Travel Survey Data," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    12. Franke, Thomas & Krems, Josef F., 2013. "What drives range preferences in electric vehicle users?," Transport Policy, Elsevier, vol. 30(C), pages 56-62.
    13. Kurani, Kenneth S. & Turrentine, Tom & Sperling, Daniel, 1994. "Demand for Electric Vehicles in Hybrid Households: An Exploratory Analysis," University of California Transportation Center, Working Papers qt1c29r4hr, University of California Transportation Center.
    14. Jiahang He & Toshiyuki Yamamoto & Tomio Miwa & Takayuki Morikawa, 2020. "Hazard Duration Model with Panel Data for Daily Car Travel Distance: A Toyota City Case Study," Sustainability, MDPI, vol. 12(16), pages 1-13, August.
    15. Jensen, Anders Fjendbo & Mabit, Stefan Lindhard, 2017. "The use of electric vehicles: A case study on adding an electric car to a household," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 89-99.
    16. Zhixin Pan & Jianming Wang & Wenlong Liao & Haiwen Chen & Dong Yuan & Weiping Zhu & Xin Fang & Zhen Zhu, 2019. "Data-Driven EV Load Profiles Generation Using a Variational Auto-Encoder," Energies, MDPI, vol. 12(5), pages 1-15, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:19:y:1985:i:4:p:347-358. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.