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Electrifying Ride-Sharing: Transitioning to a Cleaner Future

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  • Jenn, Alan

Abstract

Incentives for plug-in electric vehicles (PEVs) are typically designed to encourage broad consumer adoption of the new technology. However, maximizing the emissions benefits from electrifying the transportation sector also requires incentives targeted at stakeholders with high travel intensity, i.e., those with particularly high passenger occupancy and/or vehicle-miles traveled (VMT). This policy brief focuses on one such class of stakeholders: transportation network companies (TNCs) such as Uber and Lyft. It examines empirical data of electric vehicle use in TNCs and discusses research findings on the potential impacts of electrifying TNCs. It also raises important considerations for the development of future policy. View the NCST Project Webpage

Suggested Citation

  • Jenn, Alan, 2019. "Electrifying Ride-Sharing: Transitioning to a Cleaner Future," Institute of Transportation Studies, Working Paper Series qt12s554kd, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt12s554kd
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    Cited by:

    1. Ma, Tai-Yu & Fang, Yumeng & Connors, Richard D. & Viti, Francesco & Nakao, Haruko, 2024. "A hybrid metaheuristic to optimize electric first-mile feeder services with charging synchronization constraints and customer rejections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    2. Tai-Yu Ma, 2021. "Two-stage battery recharge scheduling and vehicle-charger assignment policy for dynamic electric dial-a-ride services," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-27, May.
    3. Ma, Tai-Yu & Faye, Sébastien, 2022. "Multistep electric vehicle charging station occupancy prediction using hybrid LSTM neural networks," Energy, Elsevier, vol. 244(PB).

    More about this item

    Keywords

    Engineering; Social and Behavioral Sciences; electric vehicles; vehicle miles traveled; incentives; plug-in electric vehicles; transportation network companies; ridesharing;
    All these keywords.

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