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Analyzing Consumer Experience of Autonomous Vehicles Using Topic Modeling

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HCI International 2023 Posters (HCII 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1835))

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Abstract

There have been many studies on consumer acceptance and perception of autonomous vehicles. In contrast, scant research has been conducted on the user experience of autonomous vehicles. This study explored the user experience of autonomous vehicles and investigates consumer problems and issues related to autonomous vehicles from the consumer perspective. Vehicle users share information and opinions and discuss various vehicle-related topics in online communities. We collected their online posts published between February 2014 and December 2022. Applying LDA topic modeling analysis was conducted as a method for text data analysis. Considering the coherence score and interpretability, we derived five topics. Each of the topics was specified as “Perceived risks,” “Knowledge share,” “Reasons to purchase,” “Arbitrary hardware mounting,” and “Arbitrary software manipulation.” First, consumers are concerned about lane departure and possible accidents. Second, consumers built up knowledge about autonomous driving technology by sharing information on and discussing the technical aspects of autonomous vehicles. Third, long-distance driving or commuting was the primary driver to purchase autonomous vehicles. Fourth, some consumers were active rather than passive in using autonomous driving technology in terms of both hardware and software manipulation. They mounted an auxiliary device to a non-autonomous vehicle and converted it into an autonomous one. They manipulated the default setting of the autonomous deriving system reflecting their own speeding or distancing preferences. Since autonomous vehicles are sensitive and complex structures, arbitrary mounting and manipulation can cause fatal accidents. Guidelines for using autonomous driving technology and legal and administrating measures are necessary for the safe use of autonomous driving technology. Customizing hardware and software which satisfy individual consumers’ need and want may reduce the risk of arbitrary manipulation.

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Authors and Affiliations

  1. Department of Consumer Science, Convergence Program for Social Innovation, Sungkyunkwan University, Seoul, South Korea

    Jinu Jung, Xinyu Wang, Jiaojiao Ge, Jingrui Niu & Seonglim Lee

Authors
  1. Jinu Jung
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  2. Xinyu Wang
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  3. Jiaojiao Ge
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  4. Jingrui Niu
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  5. Seonglim Lee
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Corresponding author

Correspondence to Seonglim Lee .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  3. Foundation for Research and Technology - Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

  4. University of Central Florida, Orlando, FL, USA

    Gavriel Salvendy

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Jung, J., Wang, X., Ge, J., Niu, J., Lee, S. (2023). Analyzing Consumer Experience of Autonomous Vehicles Using Topic Modeling. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2023 Posters. HCII 2023. Communications in Computer and Information Science, vol 1835. Springer, Cham. https://doi.org/10.1007/978-3-031-36001-5_8

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  • DOI: https://doi.org/10.1007/978-3-031-36001-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36000-8

  • Online ISBN: 978-3-031-36001-5

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