Trust and Visual Focus in Automated Vehicles: A Comparative Study of Beginner and Experienced Drivers

要旨

This study investigated the relationship between trust in automation, gaze behavior, and driving performance in beginner and experienced drivers during a simulated driving session. Twenty participants completed a 17-minute drive across three conditions: manual driving, non-critical automated driving, and critical automated driving, with a non-driving-related task (NDRT) introduced between conditions to assess visual attention. Driving performance was evaluated using the Standard Deviation of Lateral Position (SDLP), and eye-tracking data in terms of mean gaze duration (MGD). While both groups demonstrated increased trust in the automated system post-session, beginners showed greater lateral position variability in critical conditions, suggesting over-reliance on automation. Eye-tracking analysis revealed significant changes in glance behavior across driving conditions, particularly in response to critical events. These findings highlight how driver experience shapes interactions with automated systems, emphasizing the importance of trust calibration in automated driving scenarios.

著者
Richa Singh
Tampere University , Tampere, Pirkanmaa, Finland
Mounia Ziat
Bentley University, Waltham, Massachusetts, United States
Oleg Spakov
Tampere University, Tampere, Finland
John Mäkelä
Tampere University, Tampere, Finland
Veikko Surakka
Tampere University, Tampere, Finland
Roope Raisamo
Tampere University, Tampere, Finland
DOI

10.1145/3706598.3713806

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713806

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Autonomus Vehicle

Annex Hall F204
7 件の発表
2025-05-01 18:00:00
2025-05-01 19:30:00
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