Is trust a belief, observation, or state: Results from an active inference analysis of driver-automation transitions of control

Author:

Wei Ran1,McDonald Anthony D.2ORCID,Garcia Alfredo1,Mehta Ranjana K.1

Affiliation:

1. Texas A&M University, College Station, TX, USA

2. University of Wisconsin-Madison, Madison, WI, USA

Abstract

Transitions of control are an important safety concern for human-automation teams and automated vehicle safety. While trust and situation awareness have been observed to influence transitions of control in automated vehicles, there are few objective measurements, making these concepts difficult to operationalize in increasingly automated decision systems. In this study, we take a step towards quantifying trust by mapping latent driver beliefs extracted from an active inference-factor analysis model of driver behavior and cognitive dynamics to subjective responses to trust questionnaires. Our results show that subjective trust is primarily correlated with model parameters affecting perceptual evidence accumulation rate, and the same parameters are significantly correlated with driver age.

Funder

Division of Civil, Mechanical and Manufacturing Innovation

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Reference5 articles.

1. Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems

2. Engström J., Liu S.Y., Dinparastdjadid A., Simoiu C. (2022). Modeling road user response timing in naturalistic settings: A surprise-based framework (arXiv:2208.08651).arXiv.https://doi.org/10.48550/arXiv.2208.08651

3. How safe is automated driving? Human driver models for safety performance assessment

4. Modeling Driver Responses to Automation Failures With Active Inference

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