Impact of Monitoring Requests on Trust, Acceptance, Blame, and Praise of Autonomous Vehicles

Abstract

Vehicles with autonomous features are more prevalent in today’s society, though as the level of autonomation increases, so does the vehicle system’s control of the vehicle. As the driving control shifts from human to the vehicle system, concerns arise regarding the attribution of responsibility and blame following critical events (e.g., collisions or near-misses). In this work-in-progress study, we aim to understand how the public attributes blame and praise to both humans and autonomous vehicles (AVs) following critical events. In addition, we examine how an AI driving assistant that administers Monitoring Requests influences blame and praise attributions. Furthermore, we examine differences in acceptance, trust, and perceived anthropomorphism between an AV with and without an AI driving assistant. Preliminary results are provided followed by a discussion of the expected results and potential impact for research and legal issues.