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Driving demand: What can gasoline refueling patterns tell us about planning an alternative fuel network?

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  • Nicholas, Michael A.

Abstract

Knowing which variables predict gasoline demand can help inform which are useful in determining future demand at an alternative fuel station such as those for bio-fuels, natural gas, hydrogen, or fast-charge electricity. This study explores the spatial distribution of demand by comparing two main classes of variables: those without a displacement component such as population in a census block group, and those that imply a vector or directionality such as vehicle kilometers traveled. The spatial distribution of these variables is compared to the spatial distribution of demand for gasoline using regression. Many models examining the transition from gasoline to an alternative fuel assume a demand pattern for fuel a priori in order to estimate potential demand at a future alternative fuel station. This paper studies not the models themselves but the variables used to predict demand. The results indicate that vehicle kilometers traveled (VKT) is the best variable to pinpoint where demand for fuel will occur. However, travel to the central business district of the metropolitan area does not appear to translate into demand for fuel in proportion to the VKT. While gasoline demand does appear to vary with population as well, the location of demand is much less specific than that predicted by VKT. The results also suggest that the route between home and the nearest freeway entrance may help predict a large portion of refueling and merits further investigation. This possible tendency can be used to create a new variable called “population-traffic” which appears to describe the spatial distribution of demand well. The good performance of this independent variable in regressions suggests that stations sited along the freeway may serve customers needs and provide the necessary concentration of demand for initial alternative fuel stations. A practical application of this work would be to help define refueling demand patterns in a rollout of alternative fueled vehicles in a neighborhood or town.

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  • Nicholas, Michael A., 2010. "Driving demand: What can gasoline refueling patterns tell us about planning an alternative fuel network?," Journal of Transport Geography, Elsevier, vol. 18(6), pages 738-749.
    • Handle: RePEc:eee:jotrge:v:18:y:2010:i:6:p:738-749
    DOI: 10.1016/j.jtrangeo.2010.06.011
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    References listed on IDEAS

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    1. Lin, Zhenhong & Ogden, Joan M & Fan, Yueyue & Sperling, Dan, 2005. "Optimal Dynamic Strategy of Building a Hydrogen Infrastructure in Beijing," Institute of Transportation Studies, Working Paper Series qt2fj9b72q, Institute of Transportation Studies, UC Davis.
    2. Johnson, Nils & Yang, Christopher & Ni, Jason & Johnson, Joshua & Lin, Zhenhong & Ogden, Joan M, 2005. "Optimal Design of a Fossil Fuel-Based Hydrogen Infrastructure with Carbon Capture and Sequestration: Case Study in Ohio," Institute of Transportation Studies, Working Paper Series qt1t4846kh, Institute of Transportation Studies, UC Davis.
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    1. S. A. MirHassani & R. Ebrazi, 2013. "A Flexible Reformulation of the Refueling Station Location Problem," Transportation Science, INFORMS, vol. 47(4), pages 617-628, November.
    2. Kelley, Scott & Kuby, Michael, 2013. "On the way or around the corner? Observed refueling choices of alternative-fuel drivers in Southern California," Journal of Transport Geography, Elsevier, vol. 33(C), pages 258-267.
    3. Upchurch, Christopher & Kuby, Michael, 2010. "Comparing the p-median and flow-refueling models for locating alternative-fuel stations," Journal of Transport Geography, Elsevier, vol. 18(6), pages 750-758.
    4. Pramono, Ari & Oppewal, Harmen, 2021. "Where to refuel: Modeling on-the-way choice of convenience outlet," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    5. Hong, Shuyao & Kuby, Michael, 2016. "A threshold covering flow-based location model to build a critical mass of alternative-fuel stations," Journal of Transport Geography, Elsevier, vol. 56(C), pages 128-137.
    6. Pemberton, Simon & Nobajas, Alexandre & Waller, Richard, 2021. "Rapid charging provision, multiplicity and battery electric vehicle (BEV) mobility in the UK," Journal of Transport Geography, Elsevier, vol. 95(C).
    7. Scott Kelley, 2018. "Driver Use and Perceptions of Refueling Stations Near Freeways in a Developing Infrastructure for Alternative Fuel Vehicles," Social Sciences, MDPI, vol. 7(11), pages 1-18, November.
    8. Kuby, Michael, 2019. "The opposite of ubiquitous: How early adopters of fast-filling alt-fuel vehicles adapt to the sparsity of stations," Journal of Transport Geography, Elsevier, vol. 75(C), pages 46-57.
    9. Joonho Ko & Tae-Hyoung Tommy Gim & Randall Guensler, 2017. "Locating refuelling stations for alternative fuel vehicles: a review on models and applications," Transport Reviews, Taylor & Francis Journals, vol. 37(5), pages 551-570, September.
    10. Sadri, A. & Ardehali, M.M. & Amirnekooei, K., 2014. "General procedure for long-term energy-environmental planning for transportation sector of developing countries with limited data based on LEAP (long-range energy alternative planning) and EnergyPLAN," Energy, Elsevier, vol. 77(C), pages 831-843.
    11. Visaria, Anant Atul & Jensen, Anders Fjendbo & Thorhauge, Mikkel & Mabit, Stefan Eriksen, 2022. "User preferences for EV charging, pricing schemes, and charging infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 120-143.

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