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Costs and Benefits of Electrifying and Automating Bus Transit Fleets

Author

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  • Neil Quarles

    (Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin—6.9 E. Cockrell Jr. Hall, Austin, TX 78712-1076, USA)

  • Kara M. Kockelman

    (Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin—6.9 E. Cockrell Jr. Hall, Austin, TX 78712-1076, USA)

  • Moataz Mohamed

    (Department of Civil Engineering, McMaster University JHE 301, Hamilton, ON L8S 4L7, Canada)

Abstract

Diesel-powered, human-driven buses currently dominate public transit options in most U.S. cities, yet they produce health, environmental, and cost concerns. Emerging technologies may improve fleet operations by cost-effectively reducing emissions. This study analyzes both battery-electric buses and self-driving (autonomous) buses from both cost and qualitative perspectives, using the Capital Metropolitan Transportation Authority’s bus fleet in Austin, Texas. The study predicts battery-electric buses, including the required charging infrastructure, will become lifecycle cost-competitive in or before the year 2030 at existing U.S. fuel prices ($2.00/gallon), with the specific year depending on the actual rate of cost decline and the diesel bus purchase prices. Rising diesel prices would result in immediate cost savings before reaching $3.30 per gallon. Self-driving buses will reduce or eliminate the need for human drivers, one of the highest current operating costs of transit agencies. Finally, this study develops adoption schedules for these technologies. Recognizing bus lifespans and driver contracts, and assuming battery-electric bus adoption beginning in year-2020, cumulative break-even (neglecting extrinsic benefits, such as respiratory health) occurs somewhere between 2030 and 2037 depending on the rate of battery cost decline and diesel-bus purchase prices. This range changes to 2028 if self-driving technology is available for simultaneous adoption on new electric bus purchases beginning in 2020. The results inform fleet operators and manufacturers of the budgetary implications of converting a bus fleet to electric power, and what cost parameters allow electric buses to provide budgetary benefits over their diesel counterparts.

Suggested Citation

  • Neil Quarles & Kara M. Kockelman & Moataz Mohamed, 2020. "Costs and Benefits of Electrifying and Automating Bus Transit Fleets," Sustainability, MDPI, vol. 12(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:3977-:d:357303
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    References listed on IDEAS

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    Cited by:

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    4. Zhou, Yu & Meng, Qiang & Ong, Ghim Ping, 2022. "Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 49-75.
    5. Ioannis Tikoudis & Walid Oueslati, 2023. "The future of transport-related emissions in dense urban areas: an analysis of various policy scenarios with MOLES," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(2), pages 205-268, April.
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    8. Liu, Zhaocai & Wang, Qichao & Sigler, Devon & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb & Garikapati, Venu, 2023. "Data-driven simulation-based planning for electric airport shuttle systems: A real-world case study," Applied Energy, Elsevier, vol. 332(C).
    9. Alvo, Matías & Angulo, Gustavo & Klapp, Mathias A., 2021. "An exact solution approach for an electric bus dispatch problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    10. Orlando Barraza & Miquel Estrada, 2021. "Battery Electric Bus Network: Efficient Design and Cost Comparison of Different Powertrains," Sustainability, MDPI, vol. 13(9), pages 1-28, April.
    11. Hatem Abdelaty & Moataz Mohamed, 2021. "A Prediction Model for Battery Electric Bus Energy Consumption in Transit," Energies, MDPI, vol. 14(10), pages 1-26, May.
    12. Anastasia Soukhov & Ahmed Foda & Moataz Mohamed, 2022. "Electric Mobility Emission Reduction Policies: A Multi-Objective Optimization Assessment Approach," Energies, MDPI, vol. 15(19), pages 1-21, September.
    13. Paula Vicente & Abdul Suleman & Elizabeth Reis, 2020. "Index of Satisfaction with Public Transport: A Fuzzy Clustering Approach," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    14. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    15. Anders Grauers & Sven Borén & Oscar Enerbäck, 2020. "Total Cost of Ownership Model and Significant Cost Parameters for the Design of Electric Bus Systems," Energies, MDPI, vol. 13(12), pages 1-28, June.
    16. Raka Jovanovic & Islam Safak Bayram & Sertac Bayhan & Stefan Voß, 2021. "A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems," Energies, MDPI, vol. 14(20), pages 1-23, October.
    17. Oliwia Pietrzak & Krystian Pietrzak, 2021. "The Economic Effects of Electromobility in Sustainable Urban Public Transport," Energies, MDPI, vol. 14(4), pages 1-28, February.
    18. Szilassy, Péter Ákos & Földes, Dávid, 2022. "Consumption estimation method for battery-electric buses using general line characteristics and temperature," Energy, Elsevier, vol. 261(PA).
    19. Elliot, Thomas & Levasseur, Annie, 2022. "System dynamics life cycle-based carbon model for consumption changes in urban metabolism," Ecological Modelling, Elsevier, vol. 473(C).
    20. Zbigniew Czapla & Grzegorz Sierpiński, 2023. "Driving and Energy Profiles of Urban Bus Routes Predicted for Operation with Battery Electric Buses," Energies, MDPI, vol. 16(15), pages 1-19, July.
    21. He, Yi & Liu, Zhaocai & Zhang, Yiming & Song, Ziqi, 2023. "Time-dependent electric bus and charging station deployment problem," Energy, Elsevier, vol. 282(C).

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