From Initial to Situational Automation Trust: The Interplay of Personality, Interpersonal Trust, and Trust Calibration in Young Males

Tang, Menghan; Lu, Tianjiao; You, Xuqun · 2026 · Behavioral Sciences

DOI: 10.3390/bs16020176

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Summary

This study investigates the evolution of trust in automation, specifically examining how stable individual differences (personality and interpersonal trust) influence initial trust expectations and subsequent situational trust calibration during driving. The research addresses a critical gap in human–machine interaction literature: the lack of understanding regarding how trait-level characteristics translate into dynamic behavioral and physiological responses across different automation levels. The authors propose a framework distinguishing between stable traits, initial trust (pre-interaction expectations), and situational trust (dynamic calibration via gaze, physiology, and behavior). The researchers conducted a driving simulator experiment with 30 young male participants, comparing manual (Level 0), semi-automated (Level 2), and fully automated (Level 4) driving conditions. The study combined eye-tracking data (pupillometry and fixation duration) with psychometric assessments, including the Eysenck Personality Questionnaire (EPQ), Interpersonal Trust Scale (ITS), and Trust in Automation (TIA) scale. Participants performed collision avoidance tasks while their reaction times, hazard detection sensitivity, and physiological workload were recorded. Statistical analyses included linear mixed-effects models for reaction times, signal detection theory for hazard discrimination, and mediation analysis to explore trait pathways. Results indicated that semi-automation yielded higher hazard detection sensitivity ($d' = 0.81$) compared to full automation but imposed greater physiological costs, evidenced by larger pupil diameters ($\eta_p^2 = 0.445$) and increased fixation on instrument displays. Manual driving produced significantly faster reaction times than both automated conditions. Crucially, mediation analysis revealed that neuroticism influenced initial trust in automation indirectly through interpersonal trust. A paradoxical "social complacency" effect was observed: individuals with high interpersonal trust exhibited slower reaction times in semi-automated conditions ($B = 0.60, p = 0.035$), despite reporting lower initial trust. This suggests that high interpersonal trust leads to implicit behavioral reliance on the system, reducing readiness to intervene. The findings imply that situational trust is a multi-layered calibration process involving dissociated attentional, perceptual, and behavioral mechanisms. The study concludes that semi-automation induces a high-effort monitoring state that does not necessarily improve behavioral readiness. The identified "wary but complacent" driver profile highlights a risk where social faith in partners translates to dangerous lethargy with machine agents. These results suggest that human–machine interfaces for semi-automated vehicles require adaptive interventions, such as multimodal alerts tailored to individual trust profiles, to counteract complacency and ensure timely takeover responses.

Key finding

Trust in automation calibrates across personality, initial expectations, and situation-specific gaze/behavior, with high interpersonal trust producing a 'wary but complacent' young-male driver who has slower reaction times in semi-automation despite reporting low initial trust.

Methodology

simulator

Sample size: 30

Provenance

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StageOutcomeToolModelPromptAttemptsCompleted
discover success 1 2026-05-03
archive success 5 2026-05-04
extract success cached 2 2026-06-10
clean success 1 2026-06-01
chunk success 1 2026-06-01
embed success 1 2026-06-02
enrich success openalex 2 2026-06-01
promote success 1 2026-05-03
summarize success llm qwen3.6-27b-prismaquant summ-v5 2 2026-06-10
tag success vector_similarity 16 2026-06-11
verify success 2 2026-06-10

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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