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Exploring Trust in Self-Driving Vehicles Through Text Analysis.

John D Lee1, Kristin Kolodge2

  • 15228 University of Wisconsin-Madison, USA.

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Summary
This summary is machine-generated.

Consumer attitudes toward self-driving vehicles are shaped by trust factors. Positive attitudes link to testing, while negative ones cite hacking concerns, influencing trust in automated driving systems.

Keywords:
consumer acceptancedread riskperceived riskrisk analysissurvey analysisvehicle automation

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Area of Science:

  • Human-computer interaction
  • Automotive engineering
  • Consumer psychology

Background:

  • Consumer attitudes are critical for the adoption of self-driving vehicles.
  • Understanding the basis of these attitudes is essential for technological advancement.
  • Survey data and open-ended comments offer insights into consumer perceptions.

Purpose of the Study:

  • To examine consumer attitudes toward self-driving vehicles.
  • To identify factors influencing these attitudes.
  • To understand the underlying reasons for trust and distrust in vehicle automation.

Main Methods:

  • Utilized structural topic modeling on qualitative comments from a large-scale survey (J.D. Power U.S. Tech Choice Study).
  • Analyzed 7,947 (2016) and 8,517 (2017) driver responses regarding trust in self-driving vehicles.
  • Identified key themes and assessed their prevalence based on trust ratings and survey year.

Main Results:

  • Identified 13 distinct topics influencing attitudes, such as 'Tested for a long time' (positive) and 'Hacking & glitches' (negative).
  • Found 'Self-driving accidents' and 'Trust when mature' topics increased in prominence from 2016 to 2017.
  • Demonstrated a clear link between specific themes and reported levels of trust.

Conclusions:

  • Structural topic modeling effectively reveals the nuanced reasons behind consumer attitudes toward vehicle automation.
  • Attitudes are influenced by trust in automation, perceived risks, desire for control, and various societal, relational, and experiential factors.
  • Findings inform the ongoing debate on safety thresholds for automated vehicles and factors influencing user trust.