IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1902.00382.html

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

Author

Listed:
  • Morteza Taiebat
  • Samuel Stolper
  • Ming Xu

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.

Suggested Citation

  • Morteza Taiebat & Samuel Stolper & Ming Xu, 2019. "Forecasting the Impact of Connected and Automated Vehicles on Energy Use A Microeconomic Study of Induced Travel and Energy Rebound," Papers 1902.00382, arXiv.org, revised May 2019.
    • Handle: RePEc:arx:papers:1902.00382
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1902.00382
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Wadud, Zia & Graham, Daniel J. & Noland, Robert B., 2009. "Modelling fuel demand for different socio-economic groups," Applied Energy, Elsevier, vol. 86(12), pages 2740-2749, December.
    4. repec:aen:journl:2010v31-01-a03 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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]," Sustainability Nexus Forum, Springer, vol. 29(1), pages 1-11, March.
    2. 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).
    3. Nuri C. Onat & Jafar Mandouri & Murat Kucukvar & Burak Sen & Saddam A. Abbasi & Wael Alhajyaseen & Adeeb A. Kutty & Rateb Jabbar & Marcello Contestabile & Abdel Magid Hamouda, 2023. "Rebound effects undermine carbon footprint reduction potential of autonomous electric vehicles," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. 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.
    5. Tscharaktschiew, Stefan & Reimann, Felix, 2025. "Cruising or Parking," Transportation Research Part A: Policy and Practice, Elsevier, vol. 198(C).
    6. Mamkhezri, Jamal & Khezri, Mohsen, 2024. "Vehicle miles traveled induced demand, rebound effect, and price and income elasticities: A US spatial econometric analysis," Transport Policy, Elsevier, vol. 158(C), pages 224-240.
    7. 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).
    8. 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.
    9. 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).
    10. 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).
    11. Batarce, Marco & Basso, Franco & Basso, Leonardo J., 2023. "The elasticity of demand on urban highways: The case of Santiago," Transport Policy, Elsevier, vol. 133(C), pages 234-241.
    12. 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).
    13. 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).
    14. 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.
    15. Samantha Heiberg & Emily Emond & Cody Allen & Dheeraj Raya & Venkataramana Gadhamshetty & Saurabh Sudha Dhiman & Achyuth Ravilla & Ilke Celik, 2023. "Environmental Impact Assessment of Autonomous Transportation Systems," Energies, MDPI, vol. 16(13), pages 1-13, June.
    16. 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).
    17. 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.
    18. 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).
    19. 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.
    20. Waltermann, Juliana & Henkel, Sven, 2025. "The human element in autonomous driving: Motivations, expectations, and behavioral change," Technological Forecasting and Social Change, Elsevier, vol. 213(C).
    21. Peer, Stefanie & Müller, Johannes & Naqvi, Asjad & Straub, Markus, 2024. "Introducing shared, electric, autonomous vehicles (SAEVs) in sub-urban zones: Simulating the case of Vienna," Transport Policy, Elsevier, vol. 147(C), pages 232-243.
    22. Guzzo, D. & Walrave, B. & Videira, N. & Oliveira, I.C. & Pigosso, D.C.A., 2024. "Towards a systemic view on rebound effects: Modelling the feedback loops of rebound mechanisms," Ecological Economics, Elsevier, vol. 217(C).
    23. 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.
    24. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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," Applied Energy, Elsevier, vol. 247(C), pages 297-308.
    2. 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," LawRxiv dk6qv, Center for Open Science.
    3. Hermann Buslei, 2023. "Schätzungen der langfristigen Preiselastizitäten der Energienachfrage für Heizung und Verkehr - eine Übersicht mit Schwerpunkt Deutschland," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 127, number pbk194.
    4. Jinwon Kim & Jucheol Moon & Dongyun Yang, 2024. "Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways," Working Papers 2402, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    5. Tarduno, Matthew, 2021. "The congestion costs of Uber and Lyft," Journal of Urban Economics, Elsevier, vol. 122(C).
    6. Ouyang, Jinlong & Long, Enshen & Hokao, Kazunori, 2010. "Rebound effect in Chinese household energy efficiency and solution for mitigating it," Energy, Elsevier, vol. 35(12), pages 5269-5276.
    7. Ahn, JaeBin, 2025. "Greenflation or greensulation? The case of fuel excise taxes and oil price pass-through," Energy Economics, Elsevier, vol. 148(C).
    8. Carlton, Justin & Burris, Mark, 2014. "Comprehensive Equity Analysis of Mileage-Based User Fees: Taxation and Expenditures for Roadways and Transit," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 53(2).
    9. Bergantino, Angela Stefania & Intini, Mario & Perdiguero, Jordi, 2020. "Pay cycles and fuel price: a quasi experimental approach," The Warwick Economics Research Paper Series (TWERPS) 1288, University of Warwick, Department of Economics.
    10. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    11. Antonio M. Bento & Mark R. Jacobsen & Christopher R. Knittel & Arthur A. van Benthem, 2020. "Estimating the Costs and Benefits of Fuel-Economy Standards," Environmental and Energy Policy and the Economy, University of Chicago Press, vol. 1(1), pages 129-157.
    12. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    13. Langford, Richard P. & Gillingham, Kenneth, 2023. "Quantifying the benefits of the introduction of the hybrid electric vehicle," International Journal of Industrial Organization, Elsevier, vol. 87(C).
    14. Eichner, Thomas & Pethig, Rüdiger, 2022. "Kantians defy the economists’ mantra of uniform Pigovian emissions taxes," Ecological Economics, Elsevier, vol. 200(C).
    15. Kotval-K, Zeenat & Vojnovic, Igor, 2016. "A socio-ecological exploration into urban form: The environmental costs of travel," Ecological Economics, Elsevier, vol. 128(C), pages 87-98.
    16. Yuanyuan Wu & Feng Zhu, 2021. "Junction Management for Connected and Automated Vehicles: Intersection or Roundabout?," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    17. Bjertnæs, Geir H.M., 2025. "Economical driving and taxation of road use," Energy Economics, Elsevier, vol. 142(C).
    18. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    19. Christian Haas & Karol Kempa, 2023. "Low-Carbon Investment and Credit Rationing," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(1), pages 109-145, October.
    20. Tirkaso, Wondmagegn Tafesse & Gren, Ing-Marie, 2020. "Road fuel demand and regional effects of carbon taxes in Sweden," Energy Policy, Elsevier, vol. 144(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1902.00382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.