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Sociotechnical imaginaries of autonomous vehicles: Comparing laboratory and online eye-tracking methods

  • 0FinEst Centre for Smart Cities, Tallinn University of Technology, Tallinn, Estonia.
Plos One +

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November 17, 2025

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November 17, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study used eye-tracking to explore how people envision autonomous vehicles (AVs). Global participants focused more on AVs, while lab participants prioritized human decision-making in non-AV scenarios.

Area Of Science

  • Human-Computer Interaction
  • Sociotechnical Systems
  • Cognitive Science

Background

  • Sociotechnical imaginaries shape public perception of emerging technologies like autonomous vehicles (AVs).
  • Understanding cognitive engagement with AVs is crucial for their development and integration.
  • Previous research often lacks diverse perspectives on human-AV interaction.

Purpose Of The Study

  • To investigate sociotechnical imaginaries of AVs using a dual eye-tracking approach.
  • To examine variations in cognitive engagement with AVs across different decision-making scenarios.
  • To compare in-lab and online methodologies for studying human perception of AVs.

Main Methods

  • Employed a dual approach: in-lab and online eye-tracking experiments.
  • Presented participants with hypothetical decision-making scenarios involving AV algorithmic failure.
  • Analyzed gaze durations and overall cognitive engagement patterns.

Main Results

  • Both in-lab and online participants showed longer gaze durations in AV scenarios.
  • In-lab participants focused more on non-AV scenarios, emphasizing human decision-making.
  • Online participants showed increased attention to AV scenarios, reflecting diverse global perspectives.

Conclusions

  • Perception of AVs and concerns about algorithmic decision-making vary globally.
  • Eye-tracking reveals differences in cognitive engagement based on sample diversity and sociotechnical imaginaries.
  • The study highlights the complementary value of in-lab and online methods for understanding emerging technologies.