IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v148y2021icp402-422.html
   My bibliography  Save this article

Investigating autonomous vehicle impacts on individual activity-travel behavior

Author

Listed:
  • Dannemiller, Katherine A.
  • Mondal, Aupal
  • Asmussen, Katherine E.
  • Bhat, Chandra R.

Abstract

This paper develops an analytic system to investigate the effects of AV availability on multiple dimensions of activity-travel behavior at once, based on a direct survey-based modeling approach. In particular, the model uses individual socio-demographics, built environment variables, as well as psycho-social variables (in the form of latent psychological constructs) as determinant variables to explain likely AV impacts on five dimensions of short-term activity-travel choices: (1) Additional local area trips (that is, those that would not characterized as long distance trips; a long distance trip was defined in the survey as a trip more than 75 miles one-way), (2) Trip distance to shop or eat-out activities in the local area, (3) Trip distance to leisure activities in the local area, (4) Additional long distance road trips beyond the local area, and (5) Commute travel time. The model system includes a confirmatory factor analysis step, a multivariate linear regression model for the latent constructs, and a multivariate ordered-response model for the five main outcomes just listed. Data from a 2019 Austin area survey of new mobility service adoption and use forms the basis for our empirical analysis. Our results, when aggregated across all respondents, does suggest that AVs may not after all have a substantial impact on overall trip-making levels, although local area trips are likely to become longer (for all purposes, including the commute). The highest impact of AVs will, it appears, be on the number of long distance trips (with such trips increasing). Our in-depth examination of the variations in AV activity-travel responses across population segments and geographies underscores the importance of modeling multiple activity-travel dimensions all at once. In addition, our results highlight the value of using psycho-social latent constructs in studies related to the adoption/use of current and emerging mobility services, both in terms of improved prediction fit as well as proactive strategies to design equitable, safe, and community-driven AV systems. There is likely to be considerable heterogeneity in how different population groups view and respond to AVs, and it is imperative that AV campaigns and AV design consider such heterogeneity so as to not “leave anyone behind”.

Suggested Citation

  • Dannemiller, Katherine A. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Chandra R., 2021. "Investigating autonomous vehicle impacts on individual activity-travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 402-422.
    • Handle: RePEc:eee:transa:v:148:y:2021:i:c:p:402-422
    DOI: 10.1016/j.tra.2021.04.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096585642100104X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2021.04.006?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. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    2. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    3. Nwankwo, Sonny & Hamelin, Nicolas & Khaled, Meryem, 2014. "Consumer values, motivation and purchase intention for luxury goods," Journal of Retailing and Consumer Services, Elsevier, vol. 21(5), pages 735-744.
    4. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    7. Marikyan, Davit & Papagiannidis, Savvas & Alamanos, Eleftherios, 2019. "A systematic review of the smart home literature: A user perspective," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 139-154.
    8. Lyn Craig & Abigail Powell, 2018. "Shares of Housework Between Mothers, Fathers and Young People: Routine and Non-routine Housework, Doing Housework for Oneself and Others," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 269-281, February.
    9. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
    10. Gary Solon & Steven J. Haider & Jeffrey M. Wooldridge, 2015. "What Are We Weighting For?," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 301-316.
    11. 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.
    12. Rashidi, Taha Hossein & Waller, Travis & Axhausen, Kay, 2020. "Reduced value of time for autonomous vehicle users: Myth or reality?," Transport Policy, Elsevier, vol. 95(C), pages 30-36.
    13. Gaurav Vyas & Pooneh Famili & Peter Vovsha & Daniel Fay & Ashish Kulshrestha & Greg Giaimo & Rebekah Anderson, 2019. "Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH," Transportation, Springer, vol. 46(6), pages 2081-2102, December.
    14. Correia, Gonçalo Homem de Almeida & Looff, Erwin & van Cranenburgh, Sander & Snelder, Maaike & van Arem, Bart, 2019. "On the impact of vehicle automation on the value of travel time while performing work and leisure activities in a car: Theoretical insights and results from a stated preference survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 359-382.
    15. Rico Krueger & Taha H. Rashidi & Vinayak V. Dixit, 2019. "Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey," Papers 1905.11486, arXiv.org, revised Sep 2019.
    16. Bhat, Chandra R., 2014. "The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(1), pages 1-117, July.
    17. 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.
    18. Kieran Walsh & Thomas Scharf & Norah Keating, 2017. "Social exclusion of older persons: a scoping review and conceptual framework," European Journal of Ageing, Springer, vol. 14(1), pages 81-98, March.
    19. Chee, Pei Nen Esther & Susilo, Yusak O. & Wong, Yiik Diew, 2020. "Determinants of intention-to-use first-/last-mile automated bus service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 350-375.
    20. Jason Hawkins & Khandker Nurul Habib, 2019. "Integrated models of land use and transportation for the autonomous vehicle revolution," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 66-83, January.
    21. Hohenberger, Christoph & Spörrle, Matthias & Welpe, Isabell M., 2017. "Not fearless, but self-enhanced: The effects of anxiety on the willingness to use autonomous cars depend on individual levels of self-enhancement," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 40-52.
    22. Fraedrich, Eva & Heinrichs, Dirk & Bahamonde-Birke, Francisco J. & Cyganski, Rita, 2019. "Autonomous driving, the built environment and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 162-172.
    23. Yap, Menno D. & Correia, Gonçalo & van Arem, Bart, 2016. "Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 1-16.
    24. Bernardo, Christina & Paleti, Rajesh & Hoklas, Megan & Bhat, Chandra, 2015. "An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 71-91.
    25. Inès Chouk & Zied Mani, 2017. "Drivers of consumers’ resistance to smart products," Post-Print hal-02980400, HAL.
    26. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
    27. Kröger, Lars & Kuhnimhof, Tobias & Trommer, Stefan, 2019. "Does context matter? A comparative study modelling autonomous vehicle impact on travel behaviour for Germany and the USA," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 146-161.
    28. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    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. Teodorovicz, Thomaz & Kun, Andrew L. & Sadun, Raffaella & Shaer, Orit, 2022. "Multitasking while driving: a time use study of commuting knowledge workers to access current and future uses," LSE Research Online Documents on Economics 117830, London School of Economics and Political Science, LSE Library.
    2. Katalin Ásványi & Márk Miskolczi & Melinda Jászberényi & Zsófia Kenesei & László Kökény, 2022. "The Emergence of Unconventional Tourism Services Based on Autonomous Vehicles (AVs)—Attitude Analysis of Tourism Experts Using the Q Methodology," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    3. Fatemeh Nazari & Yellitza Soto & Mohamadhossein Noruzoliaee, 2023. "Privately-Owned versus Shared Automated Vehicle: The Roles of Utilitarian and Hedonic Beliefs," Papers 2309.03283, arXiv.org.
    4. Bhat, Chandra R. & Mondal, Aupal, 2022. "A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 244-266.
    5. Macea, Luis F. & Serrano, Iván & Carcache-Guas, Camila, 2023. "A reservation-based parking behavioral model for parking demand management in urban areas," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    6. Tamakloe, Reuben & Park, Dongjoo, 2023. "Discovering latent topics and trends in autonomous vehicle-related research: A structural topic modelling approach," Transport Policy, Elsevier, vol. 139(C), pages 1-20.
    7. Mondal, Aupal & Bhat, Chandra R., 2022. "A spatial rank-ordered probit model with an application to travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 374-393.
    8. Asmussen, Katherine E. & Mondal, Aupal & Bhat, Chandra R., 2022. "Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 156-179.
    9. Fatemeh Nazari & Mohamadhossein Noruzoliaee & Abolfazl Mohammadian, 2023. "Behavioral acceptance of automated vehicles: The roles of perceived safety concern and current travel behavior," Papers 2302.12225, arXiv.org, revised Jan 2024.
    10. Mohammadhossein Abbasi & Amir Reza Mamdoohi & Grzegorz Sierpiński & Francesco Ciari, 2023. "Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips," Sustainability, MDPI, vol. 15(2), pages 1-17, January.

    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. Asmussen, Katherine E. & Mondal, Aupal & Bhat, Chandra R., 2022. "Adoption of partially automated vehicle technology features and impacts on vehicle miles of travel (VMT)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 156-179.
    2. Fatemeh Nazari & Mohamadhossein Noruzoliaee & Abolfazl Mohammadian, 2023. "Behavioral acceptance of automated vehicles: The roles of perceived safety concern and current travel behavior," Papers 2302.12225, arXiv.org, revised Jan 2024.
    3. Lee, Jaehyung & Lee, Euntak & Yun, Jaewoong & Chung, Jin-Hyuk & Kim, Jinhee, 2021. "Latent heterogeneity in autonomous driving preferences and in-vehicle activities by travel distance," Journal of Transport Geography, Elsevier, vol. 94(C).
    4. 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.
    5. Attié, Elodie & Meyer-Waarden, Lars, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    6. 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).
    7. Wang, Jinghui & Yang, Hao, 2023. "Low carbon future of vehicle sharing, automation, and electrification: A review of modeling mobility behavior and demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    8. 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.
    9. Limin Tan & Changxi Ma & Xuecai Xu & Jin Xu, 2019. "Choice Behavior of Autonomous Vehicles Based on Logistic Models," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    10. Benoît Lécureux & Adrien Bonnet & Ouassim Manout & Jaâfar Berrada & Louafi Bouzouina, 2022. "Acceptance of Shared Autonomous Vehicles: A Literature Review of stated choice experiments," Working Papers hal-03814947, HAL.
    11. Devon McAslan & Farah Najar Arevalo & David A. King & Thaddeus R. Miller, 2021. "Pilot project purgatory? Assessing automated vehicle pilot projects in U.S. cities," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-16, December.
    12. Liliana Andrei & Oana Luca & Florian Gaman, 2022. "Insights from User Preferences on Automated Vehicles: Influence of Socio-Demographic Factors on Value of Time in Romania Case," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    13. Jörg Sonnleitner & Markus Friedrich & Emely Richter, 2022. "Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results," Transportation, Springer, vol. 49(3), pages 927-950, June.
    14. Mohamad Shatanawi & Mohammed Hajouj & Belal Edries & Ferenc Mészáros, 2022. "The Interrelationship between Road Pricing Acceptability and Self-Driving Vehicle Adoption: Insights from Four Countries," Sustainability, MDPI, vol. 14(19), pages 1-32, October.
    15. 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).
    16. Schikofsky, Jan & Dannewald, Till & Kowald, Matthias, 2020. "Exploring motivational mechanisms behind the intention to adopt mobility as a service (MaaS): Insights from Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 296-312.
    17. Rashidi, Taha Hossein & Waller, Travis & Axhausen, Kay, 2020. "Reduced value of time for autonomous vehicle users: Myth or reality?," Transport Policy, Elsevier, vol. 95(C), pages 30-36.
    18. Asrar Ahmed Sabir & Iftikhar Ahmad & Hassan Ahmad & Muhammad Rafiq & Muhammad Asghar Khan & Neelum Noreen, 2023. "Consumer Acceptance and Adoption of AI Robo-Advisors in Fintech Industry," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    19. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
    20. Hwang, Jinuk & Kim, Seheon, 2023. "Autonomous vehicle transportation service for people with disabilities: Policy recommendations based on the evidence from hybrid choice model," Journal of Transport Geography, Elsevier, vol. 106(C).

    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:transa:v:148:y:2021:i:c:p:402-422. 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/547/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.