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Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound

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  • Taiebat, Morteza
  • Stolper, Samuel
  • Xu, Ming

Abstract

Connected and automated vehicles (CAVs) are expected to yield significant improvements in safety, energy efficiency, and time utilization. However, their net effect on energy and environmental outcomes is unclear. Higher fuel economy reduces the energy required per mile of travel, but it also reduces the fuel cost of travel, incentivizing more travel and causing an energy “rebound effect.” Moreover, CAVs are predicted to vastly reduce the time cost of travel, inducing further increases in travel and energy use. In this paper, we forecast the induced travel and rebound from CAVs using data on existing travel behavior. We develop a microeconomic model of vehicle miles traveled (VMT) choice under income and time constraints; then we use it to estimate elasticities of VMT demand with respect to fuel and time costs, with fuel cost data from the 2017 United States National Household Travel Survey (NHTS) and wage-derived predictions of travel time cost. Our central estimate of the combined price elasticity of VMT demand is -0.4, which differs substantially from previous estimates. We also find evidence that wealthier households have more elastic demand, and that households at all income levels are more sensitive to time costs than to fuel costs. We use our estimated elasticities to simulate VMT and energy use impacts of full, private CAV adoption under a range of possible changes to the fuel and time costs of travel. We forecast a 2-47% increase in travel demand for an average household. Our results indicate that backfire – i.e., a net rise in energy use – is a possibility, especially in higher income groups. This presents a stiff challenge to policy goals for reductions in not only energy use but also traffic congestion and local and global air pollution, as CAV use increases.

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  • Taiebat, Morteza & Stolper, Samuel & Xu, Ming, 2019. "Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound," LawArXiv dk6qv, Center for Open Science.
  • Handle: RePEc:osf:lawarx:dk6qv
    DOI: 10.31219/osf.io/dk6qv
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    References listed on IDEAS

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    1. Christopher R. Knittel & Ryan Sandler, 2018. "The Welfare Impact of Second-Best Uniform-Pigouvian Taxation: Evidence from Transportation," American Economic Journal: Economic Policy, American Economic Association, vol. 10(4), pages 211-242, November.
    2. Morteza Taiebat & Austin L. Brown & Hannah R. Safford & Shen Qu & Ming Xu, 2019. "A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehicles," Papers 1901.10581, arXiv.org, revised Feb 2019.
    3. Zia Wadud & Daniel J. Graham & Robert B. Noland, 2010. "Gasoline Demand with Heterogeneity in Household Responses," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 47-74.
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    1. Dowds, Jonathan & Sullivan, James & Rowangould, Gregory & Aultman-Hall, Lisa, 2021. "Consideration of Automated Vehicle Benefits and Research Needs for Rural America," Institute of Transportation Studies, Working Paper Series qt4v25q5n9, Institute of Transportation Studies, UC Davis.
    2. Dong, Haoxuan & Zhuang, Weichao & Chen, Boli & Wang, Yan & Lu, Yanbo & Liu, Ying & Xu, Liwei & Yin, Guodong, 2022. "A comparative study of energy-efficient driving strategy for connected internal combustion engine and electric vehicles at signalized intersections," Applied Energy, Elsevier, vol. 310(C).
    3. Max Luke & Priyanshi Somani & Turner Cotterman & Dhruv Suri & Stephen J. Lee, 2020. "No COVID-19 Climate Silver Lining in the US Power Sector," Papers 2008.06660, arXiv.org, revised May 2021.
    4. Pan, Shuai & Fulton, Lewis M. & Roy, Anirban & Jung, Jia & Choi, Yunsoo & Gao, H. Oliver, 2021. "Shared use of electric autonomous vehicles: Air quality and health impacts of future mobility in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    5. Harb, Mustapha PhD & Malik, Jai PhD & Circella, Giovanni PhD & Walker, Joan L. PhD, 2022. "Simulating Life with Personally-Owned Autonomous Vehicles through a Naturalistic Experiment with Personal Drivers," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt79g921rp, Institute of Transportation Studies, UC Berkeley.
    6. Liao, Zitong & Taiebat, Morteza & Xu, Ming, 2021. "Shared autonomous electric vehicle fleets with vehicle-to-grid capability: Economic viability and environmental co-benefits," Applied Energy, Elsevier, vol. 302(C).
    7. Möller, Jasmin & Daschkovska, Kateryna & Bogaschewsky, Ronald, 2019. "Sustainable city logistics: rebound effects from self-driving vehicles," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 299-337, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    8. Jan C. T. Bieser & Vlad C. Coroamă, 2021. "Direkte und indirekte Umwelteffekte der Informations- und Kommunikationstechnologie [Direct and indirect environmental effects of information and communication technology]," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(1), pages 1-11, March.
    9. Yuan, Zhen & Xu, Jie & Li, Bing & Yao, Tingting, 2022. "Limits of technological progress in controlling energy consumption: Evidence from the energy rebound effects across China's industrial sector," Energy, Elsevier, vol. 245(C).
    10. Harb, Mustapha PhD & Malik, Jai PhD & Circella, Giovanni PhD & Walker, Joan L. PhD, 2022. "Simulating Life with Personally-Owned Autonomous Vehicles through a Naturalistic Experiment with Personal Drivers," Institute of Transportation Studies, Working Paper Series qt79g921rp, Institute of Transportation Studies, UC Davis.
    11. Rasti-Barzoki, Morteza & Moon, Ilkyeong, 2021. "A game theoretic approach for analyzing electric and gasoline-based vehicles’ competition in a supply chain under government sustainable strategies: A case study of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    12. Pudāne, Baiba & van Cranenburgh, Sander & Chorus, Caspar G., 2021. "A day in the life with an automated vehicle: Empirical analysis of data from an interactive stated activity-travel survey," Journal of choice modelling, Elsevier, vol. 39(C).
    13. Alexander Cremer & Katrin Müller & Matthias Finkbeiner, 2021. "A Systemic View of Future Mobility Scenario Impacts on and Their Implications for City Organizational LCA: The Case of Autonomous Driving in Vienna," Sustainability, MDPI, vol. 14(1), pages 1-19, December.
    14. Rasti-Barzoki, Morteza & Moon, Ilkyeong, 2020. "A game theoretic approach for car pricing and its energy efficiency level versus governmental sustainability goals by considering rebound effect: A case study of South Korea," Applied Energy, Elsevier, vol. 271(C).
    15. Taiebat, Morteza & Stolper, Samuel & Xu, Ming, 2022. "Widespread range suitability and cost competitiveness of electric vehicles for ride-hailing drivers," Applied Energy, Elsevier, vol. 319(C).
    16. Moneim Massar & Imran Reza & Syed Masiur Rahman & Sheikh Muhammad Habib Abdullah & Arshad Jamal & Fahad Saleh Al-Ismail, 2021. "Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative?," IJERPH, MDPI, vol. 18(11), pages 1-23, May.

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