How can design help enhance trust calibration in public autonomous vehicles?
This addresses the challenge of integrating autonomous vehicles into cities by improving trust calibration for passengers, though it appears incremental as it builds on existing design tools.
The study tackled the problem of calibrating trust in public autonomous vehicles to ensure safe and positive experiences, focusing on passenger interactions to enhance system trustworthiness and data accuracy.
Trust is a multilayered concept with critical relevance when it comes to introducing new technologies. Understanding how humans will interact with complex vehicle systems and preparing for the functional, societal and psychological aspects of autonomous vehicles' entry into our cities is a pressing concern. Design tools can help calibrate the adequate and affordable level of trust needed for a safe and positive experience. This study focuses on passenger interactions capable of enhancing the system trustworthiness and data accuracy in future shared public transportation.