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Charging forward: deploying EV infrastructure for Uber and Lyft in California

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  • Alan Jenn

    (University of California)

Abstract

With recent policies such as the Clean Miles Standard in California and Lyft’s announcement to reach 100% electric vehicles (EVs) by 2030, the electrification of vehicles on ride-hailing platforms is inevitable. The impacts of this transition are not well-studied. This work attempts to examine the infrastructure deployment necessary to meet demand from electric vehicles being driven on Uber and Lyft platforms using empirical trip data from the two services. We develop the Widespread Infrastructure for Ride-hail EV Deployment model to examine a set of case studies for charger installation in San Diego, Los Angeles, and the San Francisco Bay Area. We also conduct a set of sensitivity scenarios to measure the tradeoff between explicit costs of infrastructure versus weighting factors for valuing the time for drivers to travel to a charger (from where they are providing rides) and valuing the rate of charging (to minimize the amount of time that drivers have to wait to charge their vehicle). There are several notable findings from our study: (1) DC fast charging infrastructure is the dominant charger type necessary to meet ride-hailing demand, (2) shifting to overnight charging behavior that places less emphasis on daytime public charging can significantly reduce costs, and (3) the necessary ratio of chargers is approximately 10 times higher for EVs in Uber and Lyft compared to chargers for the general EV owning public.

Suggested Citation

  • Alan Jenn, 2024. "Charging forward: deploying EV infrastructure for Uber and Lyft in California," Transportation, Springer, vol. 51(5), pages 1663-1678, October.
    • Handle: RePEc:kap:transp:v:51:y:2024:i:5:d:10.1007_s11116-023-10381-5
    DOI: 10.1007/s11116-023-10381-5
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    References listed on IDEAS

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    1. Ferro, G. & Minciardi, R. & Robba, M., 2020. "A user equilibrium model for electric vehicles: Joint traffic and energy demand assignment," Energy, Elsevier, vol. 198(C).
    2. Alan Jenn, 2020. "Emissions benefits of electric vehicles in Uber and Lyft ride-hailing services," Nature Energy, Nature, vol. 5(7), pages 520-525, July.
    3. Globisch, Joachim & Plötz, Patrick & Dütschke, Elisabeth & Wietschel, Martin, 2019. "Consumer preferences for public charging infrastructure for electric vehicles," Transport Policy, Elsevier, vol. 81(C), pages 54-63.
    4. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    5. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Calviño, Aida, 2019. "Fast charging stations placement methodology for electric taxis in urban zones," Energy, Elsevier, vol. 188(C).
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