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Latent heterogeneity in autonomous driving preferences and in-vehicle activities by travel distance

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  • Lee, Jaehyung
  • Lee, Euntak
  • Yun, Jaewoong
  • Chung, Jin-Hyuk
  • Kim, Jinhee

Abstract

Autonomous driving technologies (ADTs) are transformative because they are expected to assume the task of driving. Since travel distance is closely related to the burden of driving, it is expected to affect the ADT preference; however, this effect has not been investigated in the transportation literature. Therefore, this study is designed to investigate the ADT preference and heterogeneity with respect to different travel distances. Hypothetical choice situations were designed to investigate people's ADT preferences over human driving for varying travel distances. Using the stated preference data collected via the experiments, four latent class models were estimated for heterogeneity across classes and travel distances. The estimation results show that three classes, we labeled as competitive, autonomous vehicle oriented, human-driven vehicle oriented, are revealed by the ADT preference, regardless of the travel distance. In addition, in-vehicle activities in hypothetical autonomous driving situations were observed across all the classes and travel distances.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:jotrge:v:94:y:2021:i:c:s0966692321001423
    DOI: 10.1016/j.jtrangeo.2021.103089
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    3. Hirte, Georg & Laes, Renée, 2022. "Working from self-driving cars," CEPIE Working Papers 01/22, Technische Universität Dresden, Center of Public and International Economics (CEPIE).

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