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Evaluating the emission benefits of shared autonomous electric vehicle fleets: A case study in California

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  • Li, Yanning
  • Li, Xinwei
  • Jenn, Alan

Abstract

The transportation sector is a major source of greenhouse gas (GHG) emissions. Shared autonomous electric vehicles (SAEVs) have the potential to mitigate emissions, but the effect can be highly dependent on the growth and operation of the SAEV fleet as well as its interaction with the evolving power system. In this study, we simulate travel and charging behaviors of SAEVs based on empirical data of ride-hail service operations, and integrate SAEV charging with the Grid Optimized Operation Dispatch (GOOD) model, taking into account the expansion of renewable generation and charger capacity over time. Emissions from SAEVs are compared across different market adoption levels, occupancy rates, and charging strategies. We find that under the Californian power grid, SAEVs are generally more than 5 times less carbon intensive than modern day ICVs on a per mile basis. The extent of aligning charging schedule with renewable generation is an essential determinant of the economic and emission impact from an SAEV fleet. At higher levels of renewable penetration, synergizing SAEV charging with grid operation can be the most impactful means to reduce emissions from an SAEV fleet, generating up to 95% less emissions than other charging strategies. We also examine the introduction of a carbon tax and find that it can further amplify the advantage of smart charging by approximately 1.5 times in the cost-effectiveness of emission mitigation.

Suggested Citation

  • Li, Yanning & Li, Xinwei & Jenn, Alan, 2022. "Evaluating the emission benefits of shared autonomous electric vehicle fleets: A case study in California," Applied Energy, Elsevier, vol. 323(C).
    • Handle: RePEc:eee:appene:v:323:y:2022:i:c:s0306261922009400
    DOI: 10.1016/j.apenergy.2022.119638
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    1. Sumitkumar, Rathor & Al-Sumaiti, Ameena Saad, 2024. "Shared autonomous electric vehicle: Towards social economy of energy and mobility from power-transportation nexus perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 197(C).
    2. Zhang, Zihe & Liu, Jun & Bastidas, Javier Pena & Jones, Steven, 2024. "Charging infrastructure assessment for shared autonomous electric vehicles in 374 small and medium-sized urban areas: An agent-based simulation approach," Transport Policy, Elsevier, vol. 155(C), pages 58-78.
    3. Kumar, Gokula Manikandan Senthil & Guo, Xinman & Zhou, Shijie & Luo, Haojie & Wu, Qi & Liu, Yulin & Dou, Zhenyu & Pan, Kai & Xu, Yang & Yang, Hongxing & Cao, Sunliang, 2025. "State-of-the-art review of smart energy management systems for supporting zero-emission electric vehicles with X2V and V2X interactions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 208(C).
    4. Zhang, Zhe & Yu, Qing & Gao, Kun & He, Hong-Di & Liu, Yang & Huang, Haichao, 2025. "Carbon emission reduction benefits of ride-hailing vehicle electrification considering energy structure," Applied Energy, Elsevier, vol. 377(PA).
    5. Jingyi Xiao & Konstadinos G. Goulias & Srinath Ravulaparthy & Shivam Sharda & Ling Jin & C. Anna Spurlock, 2024. "Evaluating the Impacts of Autonomous Electric Vehicles Adoption on Vehicle Miles Traveled and CO 2 Emissions," Energies, MDPI, vol. 17(23), pages 1-19, December.

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