The Delegation-Level Choice of an Automated Vehicle: An Analysis by Structural Equation Modeling

Abstract

Automated vehicles (AVs) are a form of emerging technology that includes several possible automation levels. These levels are so different that it is possible to speak of different automated subsystems in which the individual switches between an active operator and a passive user. The first aim of this study was to predict the delegation level of acceptance that people are willing to hand to an AV. The second aim was to test the specific influence of trust on each delegation level of an AV. We then constructed a predictive model based on the theory of planned behavior by adding some specific modifications. For instance, we included the measured variable delegation-level acceptance, replaced specific attitudes with trust, and added technophilia (enthusiasm about new technologies) to reinforce the predictive power. The results, based on responses provided by 2,708 French participants to a two-part questionnaire, showed a parsimonious and well-established predictive model of delegation-level acceptance and highlighted that trust is significantly different according to delegation level.

Acknowledgments

The authors are grateful for this research opportunity.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The Fornell-Larcker criterion (FL criterion) is a rule to assess discriminant validity. The FL criterion is a decision rule based on a comparison between the squared construct correlations and the average variance extracted (AVE). The discriminant validity (DV) between two latent variables is calculated by comparing the convergent validity (CV) of each construct with the square of the correlations between these constructs. The rule is as follows: DV is ensured if the CV > Correlation². Table 6 showed the matrix with the squared construct correlations on the off-diagonal and the AVE’s on the main diagonal.

Additional information

Funding

This research was supported by grants from the National Research Agency in the context of the AUTOCONDUCT project [ANR-16-CE22-0007].

Notes on contributors

Marlène Bel

Marlène Bel is a researcher in Educational Sciences and Social Psychology. She specializes in the acceptance of new mobility technologies. The main object of the research concerns the prediction of the use of innovative technologies via the construction of models and their testing by structural equation modeling.

Stéphanie Coeugnet

Stéphanie Coeugnet is a researcher in Ergonomics, with expertise in prospective studies, co-design, and assessment of new solutions and Human-Machine Interfaces. Her favorite topic concerns the energy transition. She leads a research department on the topic of new mobility solutions and shared energy Solutions.