IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v98y2020icp57-67.html
   My bibliography  Save this article

A quantitative analysis of potential impacts of automated vehicles in Austria using a dynamic integrated land use and transport interaction model

Author

Listed:
  • Emberger, Guenter
  • Pfaffenbichler, Paul

Abstract

Digitisation and automation are expected to change the transport system and settlement structures in a disruptive way. Due to new developments in sensor and communication technology different business models of automated vehicles (AV) - such as private AV, car-sharing-AV, ride-sharing-AV and public transport-AV – are likely to enter the transport market. Further, different penetration rates of AVs, extension of user groups (elderly and young, people without driving licenses etc.), different cost scenarios of AV veh-kms, parking regimes/fees, etc. will have significant impact on future transport demand. The objective of the work presented in this paper was to develop a simulation-based approach to analyse the potential impacts of different vehicle automation scenarios in Austria.

Suggested Citation

  • Emberger, Guenter & Pfaffenbichler, Paul, 2020. "A quantitative analysis of potential impacts of automated vehicles in Austria using a dynamic integrated land use and transport interaction model," Transport Policy, Elsevier, vol. 98(C), pages 57-67.
    • Handle: RePEc:eee:trapol:v:98:y:2020:i:c:p:57-67
    DOI: 10.1016/j.tranpol.2020.06.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X20305187
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2020.06.014?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Paul Pfaffenbichler & Günter Emberger & Simon Shepherd, 2008. "The Integrated Dynamic Land Use and Transport Model MARS," Networks and Spatial Economics, Springer, vol. 8(2), pages 183-200, September.
    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. Gelauff, George & Ossokina, Ioulia & Teulings, Coen, 2019. "Spatial and welfare effects of automated driving: Will cities grow, decline or both?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 277-294.
    4. Aggelos Soteropoulos & Martin Berger & Francesco Ciari, 2019. "Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 29-49, January.
    5. Correia, Gonçalo Homem de Almeida & van Arem, Bart, 2016. "Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 64-88.
    6. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    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. Dorsa Alipour & Hussein Dia, 2023. "A Systematic Review of the Role of Land Use, Transport, and Energy-Environment Integration in Shaping Sustainable Cities," Sustainability, MDPI, vol. 15(8), pages 1-29, April.
    2. Liliana Andrei & Mihaela Hermina Negulescu & Oana Luca, 2022. "Premises for the Future Deployment of Automated and Connected Transport in Romania Considering Citizens’ Perceptions and Attitudes towards Automated Vehicles," Energies, MDPI, vol. 15(5), pages 1-23, February.
    3. You Kong & Jihong Ou & Longfei Chen & Fengchun Yang & Bo Yu, 2023. "The Environmental Impacts of Automated Vehicles on Parking: A Systematic Review," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    4. Xu, Yuanxian & Dong, Jianjun & Ren, Rui & Yang, Kai & Chen, Zhilong, 2022. "The impact of metro-based underground logistics system on city logistics performance under COVID-19 epidemic: A case study of Wuhan, China," Transport Policy, Elsevier, vol. 116(C), pages 81-95.
    5. Rubén Cordera & Soledad Nogués & Esther González-González & José Luis Moura, 2021. "Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    6. Sarri, Paraskevi & Kaparias, Ioannis & Preston, John & Simmonds, David, 2023. "Using Land Use and Transportation Interaction (LUTI) models to determine land use effects from new vehicle transportation technologies; a regional scale of analysis," Transport Policy, Elsevier, vol. 135(C), pages 91-111.

    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. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    2. Guo, Yuntao & Souders, Dustin & Labi, Samuel & Peeta, Srinivas & Benedyk, Irina & Li, Yujie, 2021. "Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 364-398.
    3. Sajjad Shafiei & Ziyuan Gu & Hanna Grzybowska & Chen Cai, 2023. "Impact of self-parking autonomous vehicles on urban traffic congestion," Transportation, Springer, vol. 50(1), pages 183-203, February.
    4. Pudāne, Baiba, 2019. "Departure Time Choice and Bottleneck Congestion with Automated Vehicles: Role of On-board Activities," MPRA Paper 96328, University Library of Munich, Germany.
    5. Almlöf, Erik & Nybacka, Mikael & Pernestål, Anna & Jenelius, Erik, 2022. "Will leisure trips be more affected than work trips by autonomous technology? Modelling self-driving public transport and cars in Stockholm, Sweden," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 1-19.
    6. Jiang, Like & Chen, Haibo & Chen, Zhiyang, 2022. "City readiness for connected and autonomous vehicles: A multi-stakeholder and multi-criteria analysis through analytic hierarchy process," Transport Policy, Elsevier, vol. 128(C), pages 13-24.
    7. Engholm, Albin & Kristoffersson, Ida & Pernestal, Anna, 2021. "Impacts of large-scale driverless truck adoption on the freight transport system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 227-254.
    8. Kolarova, Viktoriya & Steck, Felix & Bahamonde-Birke, Francisco J., 2019. "Assessing the effect of autonomous driving on value of travel time savings: A comparison between current and future preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 155-169.
    9. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2023. "Implications of automated vehicles for physical road environment: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    10. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    11. Marletto, Gerardo, 2019. "Who will drive the transition to self-driving? A socio-technical analysis of the future impact of automated vehicles," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 221-234.
    12. Rubén Cordera & Soledad Nogués & Esther González-González & José Luis Moura, 2021. "Modeling the Impacts of Autonomous Vehicles on Land Use Using a LUTI Model," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    13. Shelly Etzioni & Jamil Hamadneh & Arnór B. Elvarsson & Domokos Esztergár-Kiss & Milena Djukanovic & Stelios N. Neophytou & Jaka Sodnik & Amalia Polydoropoulou & Ioannis Tsouros & Cristina Pronello & N, 2020. "Modeling Cross-National Differences in Automated Vehicle Acceptance," Sustainability, MDPI, vol. 12(22), pages 1-22, November.
    14. Saeed, Tariq Usman & Burris, Mark W. & Labi, Samuel & Sinha, Kumares C., 2020. "An empirical discourse on forecasting the use of autonomous vehicles using consumers’ preferences," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    15. Bray, Garrett & Cebon, David, 2022. "Operational speed strategy opportunities for autonomous trucking on highways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 75-94.
    16. Meyer, Jonas & Becker, Henrik & Bösch, Patrick M. & Axhausen, Kay W., 2017. "Autonomous vehicles: The next jump in accessibilities?," Research in Transportation Economics, Elsevier, vol. 62(C), pages 80-91.
    17. Hudson, John & Orviska, Marta & Hunady, Jan, 2019. "People’s attitudes to autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 164-176.
    18. Ostermeijer, Francis & Koster, Hans RA. & van Ommeren, Jos, 2019. "Residential parking costs and car ownership: Implications for parking policy and automated vehicles," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 276-288.
    19. Faber, Koen & van Lierop, Dea, 2020. "How will older adults use automated vehicles? Assessing the role of AVs in overcoming perceived mobility barriers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 353-363.
    20. Pel, Bonno & Raven, Rob & van Est, Rinie, 2020. "Transitions governance with a sense of direction: synchronization challenges in the case of the dutch ‘Driverless Car’ transition," Technological Forecasting and Social Change, Elsevier, vol. 160(C).

    More about this item

    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:eee:trapol:v:98:y:2020:i:c:p:57-67. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    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.