Two Routes to Trust Calibration

Trust calibration takes place prior to and during system interaction along the available information. In an online study N = 519 participants were introduced to a conditionally automated driving (CAD) system and received different a priori information about the automation's reliability (low vs high) and brand of the CAD system (below average vs average vs above average reputation). Trust was measured three times during the study. Additionally, need for cognition (NFC) and other personality traits were assessed. Both heuristic brand information and reliability information influenced trust in automation. In line with the Elaboration Likelihood Model (ELM), participants with high NFC relied on the reliability information more than those with lower NFC. In terms of personality traits, materialism, the regulatory focus and the perfect automation scheme predicted trust in automation. These findings show that a priori information can influence a driver's trust in CAD and that such information is interpreted individually.

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Two Routes to Trust Calibration

International Journal of Mobile Human Computer Interaction ◽

10.4018/ijmhci.2019070101 ◽

2019 ◽

Vol 11 (3) ◽

pp. 1-17 ◽

Cited By ~ 2

Author(s):

Johannes Maria Kraus ◽

Yannick Forster ◽

Sebastian Hergeth ◽

Martin Baumann

Keyword(s):

Personality Traits ◽

Regulatory Focus ◽

A Priori ◽

A Priori Information ◽

Automated Driving ◽

Online Study ◽

Cad System ◽

Trust In Automation ◽

Likelihood Model ◽

Priori Information

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What’s Driving Me? Exploration and Validation of a Hierarchical Personality Model for Trust in Automated Driving

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/0018720820922653 ◽

2020 ◽

pp. 001872082092265

Author(s):

Johannes Kraus ◽

David Scholz ◽

Martin Baumann

Keyword(s):

Personality Traits ◽

User Interfaces ◽

Structural Equation ◽

Interpersonal Trust ◽

A Priori ◽

Self Esteem ◽

Equation Modeling ◽

Automated Driving ◽

Final Model ◽

Trust In Automation

Objective This paper presents a comprehensive investigation of personality traits related to trust in automated vehicles. A hierarchical personality model based on Mowen’s (2000) 3M model is explored in a first and replicated in a second study. Background Trust in automation is established in a complex psychological process involving user-, system- and situation-related variables. In this process, personality traits have been viewed as an important source of variance. Method Dispositional variables on three levels were included in an exploratory, hierarchical personality model (full model) of dynamic learned trust in automation, which was refined on the basis of structural equation modeling carried out in Study 1 (final model). Study 2 replicated the final model in an independent sample. Results In both studies, the personality model showed a good fit and explained a large proportion of variance in trust in automation. The combined evidence supports the role of extraversion, neuroticism, and self-esteem at the elemental level; affinity for technology and dispositional interpersonal trust at the situational level; and propensity to trust in automation and a priori acceptability of automated driving at the surface level in the prediction of trust in automation. Conclusion Findings confirm that personality plays a substantial role in trust formation and provide evidence of the involvement of user dispositions not previously investigated in relation to trust in automation: self-esteem, dispositional interpersonal trust, and affinity for technology. Application Implications for personalization of information campaigns, driver training, and user interfaces for trust calibration in automated driving are discussed.

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