Trust and Distrust of Automated Parking in a Tesla Model X

Abstract

Objective: The present study aims to evaluate driver intervention behaviors during a partially automated parking task. Background: Cars with partially automated parking features are becoming widely available. Although recent research explores the use of automation features in partially automated cars, none have focused on partially automated parking. Recent incidents and research have demonstrated that drivers sometimes use partially automated features in unexpected, inefficient, and harmful ways. Method: Participants completed a series of partially automated parking trials with a Tesla Model X and their behavioral interventions were recorded. Participants also completed a risk-taking behavior test and a post-experiment questionnaire that included questions about trust in the system, likelihood of using the Autopark feature, and preference for either the partially automated parking feature or self-parking. Results: Initial intervention rates were over 50%, but declined steeply in later trials. Responses to open-ended questions revealed that once participants understood what the system was doing, they were much more likely to trust it. Trust in the partially automated parking feature was predicted by a model including risk-taking behaviors, self-confidence, self-reported number of errors committed by the Tesla, and the proportion of trials in which the driver intervened. Conclusion: Using partially automated parking with little knowledge of its workings can lead to high degree of initial distrust. Repeated exposure of partially automated features to drivers can greatly increase their use. Application: Short tutorials and brief explanations of the workings of partially automated features may greatly improve trust in the system when drivers are first introduced to partially automated systems.