EFFECTS OF AUGMENTED SITUATIONAL AWARENESS ON DRIVER TRUST IN SEMI-AUTONOMOUS VEHICLE OPERATION

Tilbury, Dawn M. · 2017 · OpenAlex

DOI: 10.4271/2024-01-3654

archive: archived pipeline: cataloged verified

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Summary

This paper addresses the challenge of low driver trust in semi-autonomous vehicles, particularly within military contexts where drivers often fail to leverage automation despite its potential safety and efficiency benefits. The authors posit that a lack of situational awareness (SA) is a primary barrier to trust. Consequently, the study investigates whether augmenting a driver’s SA through specific vehicle-to-driver communication strategies can promote trust and acceptance of autonomous capabilities. The research aims to lay the groundwork for models of mutual trust between drivers and vehicles, ultimately seeking to predict when drivers will relinquish or seize control. The study employs a within-subjects experimental design involving thirty-six licensed drivers operating a static driving simulator. Participants performed a semi-autonomous driving task on a virtual two-lane highway while simultaneously engaging in a visually demanding secondary task (target recognition). The independent variable was the auditory message provided by the vehicle regarding stopped obstacles. Three conditions were tested using a Latin Square design to minimize ordering effects: Condition 1 (no message), Condition 2 (status update: “Stopped vehicle ahead”), and Condition 3 (projection: status update followed by specific action advice, such as “No action needed” or “Take control now”). Trust and SA were measured via self-reported surveys (including the Situation Awareness Rating Technique and NASA TLX), while behavioral and physiological metrics included eye-tracking data (monitoring frequency and ratio), heart rate variability, and simulation data on take-over behavior and secondary task performance. The paper outlines six specific hypotheses regarding the expected results, noting that subject testing was pending at the time of publication. The authors hypothesize that moving from Condition 1 to Condition 3 will increase self-reported trust and situational awareness while decreasing monitoring frequency and ratio. They further expect that enhanced trust and SA will lead to improved secondary task performance and more controlled driver take-over behaviors, characterized by reduced deceleration rates and steering input angles. The authors suggest that if confirmed, these results would indicate that projection-based communication is more effective than simple status updates in fostering trust. The significance of this work lies in its contribution to understanding the relationship between situational awareness, trust, and human-automation teaming. The authors argue that if increased SA leads to reduced monitoring, it validates the importance of projection-based communication as a key mechanism for encouraging autonomy use. This could inform the design of future autonomous systems, potentially allowing for the prediction of driver control transitions. Furthermore, the study highlights the distinction between self-reported trust and trusting behaviors, suggesting that effective trust must free up cognitive resources for secondary tasks to be truly beneficial. The findings aim to support the development of robust models for mutual trust, enabling better coordination between human drivers and semi-autonomous vehicle systems.

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Topics

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• trust calibration
• automation
• trust in automation foundations
• situational awareness
• automation surprise
• acceptance adoption

Information type

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• Empirical Findings: self report data