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Choice Behavior of Autonomous Vehicles Based on Logistic Models

Author

Listed:
  • Limin Tan

    () (School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Changxi Ma

    () (School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xuecai Xu

    () (School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Jin Xu

    () (College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract

To understand the public’s acceptance of autonomous vehicles, studies were conducted from the perspectives of personal attributes, travel demand and cognitions of autonomous vehicles based on 403 valid questionnaires. Influencing factors of whether travelers are purchasing autonomous vehicles, whether travelers without a driver’s license intend to take a driver’s license in the future and whether travelers are choosing an autonomous private car if travelers can only take a taxi or drive a private car are analyzed by building Logistic regression models. The results show that personal monthly income, driver’s license, driving confidence, preference for autonomous vehicles and convenience of arriving at public transport stations will affect the purchase decision of autonomous vehicles; teenagers, long-distance travelers, students and employees of enterprises and institutions, those who believe that traditional taxis/taxi-hailing are unsafe, and those who lack confidence in driving have a higher probability of choosing autonomous vehicles. This research can be used to predict the probability of future purchase and use decisions for autonomous vehicles based on data from other populations.

Suggested Citation

  • Limin Tan & Changxi Ma & Xuecai Xu & Jin Xu, 2019. "Choice Behavior of Autonomous Vehicles Based on Logistic Models," Sustainability, MDPI, Open Access Journal, vol. 12(1), pages 1-16, December.
  • Handle: RePEc:gam:jsusta:v:12:y:2019:i:1:p:54-:d:299817
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Malokin, Aliaksandr & Circella, Giovanni & Mokhtarian, Patricia L., 2019. "How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarios," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 82-114.
    5. Bansal, Prateek & Kockelman, Kara M., 2017. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 49-63.
    6. Anania, Emily C. & Rice, Stephen & Walters, Nathan W. & Pierce, Matthew & Winter, Scott R. & Milner, Mattie N., 2018. "The effects of positive and negative information on consumers’ willingness to ride in a driverless vehicle," Transport Policy, Elsevier, vol. 72(C), pages 218-224.
    7. Wang, Shenhao & Zhao, Jinhua, 2019. "Risk preference and adoption of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 215-229.
    8. 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.
    9. 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.
    10. Peng Jing & Hao Huang & Bin Ran & Fengping Zhan & Yuji Shi, 2019. "Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China," Sustainability, MDPI, Open Access Journal, vol. 11(4), pages 1-20, February.
    11. Xu, Xian & Fan, Chiang-Ku, 2019. "Autonomous vehicles, risk perceptions and insurance demand: An individual survey in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 549-556.
    12. 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.
    13. 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.
    14. 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.
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    More about this item

    Keywords

    autonomous vehicles; questionnaire; influencing factors; Logistic regression model;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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