IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v44y2017i6d10.1007_s11116-017-9802-2.html
   My bibliography  Save this article

Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria, Australia

Author

Listed:
  • Long T. Truong

    (Monash University)

  • Chris Gruyter

    (Monash University)

  • Graham Currie

    (Monash University)

  • Alexa Delbosc

    (Monash University)

Abstract

Autonomous vehicles (AVs) potentially increase vehicle travel by reducing travel and parking costs and by providing improved mobility to those who are too young to drive or older people. The increase in vehicle travel could be generated by both trip diversion from other modes and entirely new trips. Existing studies however tend to overlook AVs’ impacts on entirely new trips. There is a need to develop a methodology for estimating possible impacts of AVs on entirely new trips across all age groups. This paper explores the impacts of AVs on car trips using a case study of Victoria, Australia. A new methodology for estimating entirely new trips associated with AVs is proposed by measuring gaps in travel need at different life stages. Results show that AVs would increase daily trips by 4.14% on average. The 76+ age group would have the largest increase of 18.5%, followed by the 18–24 age group and the 12–17 age group with 14.6 and 11.1% respectively. If car occupancy remains constant in AV scenarios, entirely new trips and trip diversions from public transport and active modes would lead to a 7.31% increase in car trips. However increases in car travel are substantially magnified by reduced car occupancy rates, a trend evidenced throughout the world. Car occupancy would need to increase by at least 5.3–7.3% to keep car trips unchanged in AV scenarios.

Suggested Citation

  • Long T. Truong & Chris Gruyter & Graham Currie & Alexa Delbosc, 2017. "Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria, Australia," Transportation, Springer, vol. 44(6), pages 1279-1292, November.
    • Handle: RePEc:kap:transp:v:44:y:2017:i:6:d:10.1007_s11116-017-9802-2
    DOI: 10.1007/s11116-017-9802-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-017-9802-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-017-9802-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. David Levinson, 2015. "Climbing Mount Next: The Effects of Autonomous Vehicles on Society," Working Papers 000139, University of Minnesota: Nexus Research Group.
    2. Wadud, Zia & MacKenzie, Don & Leiby, Paul, 2016. "Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 1-18.
    3. Jeffery B. Greenblatt & Samveg Saxena, 2015. "Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles," Nature Climate Change, Nature, vol. 5(9), pages 860-863, September.
    4. Liang, Xiao & Correia, Gonçalo Homem de Almeida & van Arem, Bart, 2016. "Optimizing the service area and trip selection of an electric automated taxi system used for the last mile of train trips," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 115-129.
    Full references (including those not matched with items on IDEAS)

    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. Jia Guo & Yusak Susilo & Constantinos Antoniou & Anna Pernestål Brenden, 2020. "Influence of Individual Perceptions on the Decision to Adopt Automated Bus Services," Sustainability, MDPI, vol. 12(16), pages 1-13, August.
    2. 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.
    3. Sergey Naumov & David R. Keith & Charles H. Fine, 2020. "Unintended Consequences of Automated Vehicles and Pooling for Urban Transportation Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1354-1371, May.
    4. Hardaway, Kendrick & Teran, Oscar & Cai, Hua, 2025. "Silent emissions: The cyber-infrastructure environmental impacts of autonomous vehicles," Applied Energy, Elsevier, vol. 392(C).
    5. Roberto Battistini & Luca Mantecchini & Maria Nadia Postorino, 2020. "Users’ Acceptance of Connected and Automated Shuttles for Tourism Purposes: A Survey Study," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    6. 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.
    7. Millard-Ball, Adam, 2019. "The autonomous vehicle parking problem," Transport Policy, Elsevier, vol. 75(C), pages 99-108.
    8. Anna Eliza Wolnowska & Lech Kasyk, 2022. "Transport Preferences of City Residents in the Context of Urban Mobility and Sustainable Development," Energies, MDPI, vol. 15(15), pages 1-32, August.
    9. Kaplan, Leah & Nurullaeva, Lola & Helveston, John Paul, 2024. "Modeling the operational and labor costs of autonomous robotaxi services," Transport Policy, Elsevier, vol. 159(C), pages 108-119.
    10. Scott B. Kelley & Bradley W. Lane & John M. DeCicco, 2019. "Pumping the Brakes on Robot Cars: Current Urban Traveler Willingness to Consider Driverless Vehicles," Sustainability, MDPI, vol. 11(18), pages 1-15, September.
    11. Nunes, Ashley & Hernandez, Kristen D., 2020. "Autonomous taxis & public health: High cost or high opportunity cost?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 28-36.
    12. Mulrow, John & Derrible, Sybil & Samaras, Constantine, 2019. "Sociotechnical convex hulls and the evolution of transportation activity: A method and application to US travel survey data," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    13. Iacobucci, Riccardo & McLellan, Benjamin & Tezuka, Tetsuo, 2018. "Modeling shared autonomous electric vehicles: Potential for transport and power grid integration," Energy, Elsevier, vol. 158(C), pages 148-163.
    14. 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.
    15. Zhang, Fang & Lu, Jian & Hu, Xiaojian, 2022. "Integrated path controlling and subsidy scheme for mobility and environmental management in automated transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    16. Xiaojuan Yu & Vincent van den Berg & Erik Verhoef, 2019. "Autonomous cars and dynamic bottleneck congestion revisited: how in-vehicle activities determine aggregate travel patterns," Tinbergen Institute Discussion Papers 19-067/VIII, Tinbergen Institute.
    17. Sieber, L. & Ruch, C. & Hörl, S. & Axhausen, K.W. & Frazzoli, E., 2020. "Improved public transportation in rural areas with self-driving cars: A study on the operation of Swiss train lines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 35-51.
    18. repec:cdl:itsrrp:qt8042k3d7 is not listed on IDEAS
    19. Liu, Peng & Ma, Yanjiao & Zuo, Yaqing, 2019. "Self-driving vehicles: Are people willing to trade risks for environmental benefits?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 139-149.
    20. 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).
    21. 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).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:kap:transp:v:44:y:2017:i:6:d:10.1007_s11116-017-9802-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.