Enhancing Passenger Trust Toward Cooperative Autonomous Vehicles Using Simulated Augmented Reality Displays

Adoption of Fully Autonomous Vehicles (FAVs) depends on trust, which is defined as confidence in a vehicle's dependability, safety, and predictability. In cooperative driving scenarios, trust must exceed ego vehicles to include other autonomous vehicles and their coordination. This is challenged by unexpected multi-agent interactions, diminishing human control, and limited system transparency. We hypothesize that enhancing transparency by providing information about ego vehicles, other cooperative vehicles, and road conditions can foster trust. This is achieved by visualizing vehicle-to-everything (V2X) information via augmented reality (AR) interfaces. To test this in a safe environment, we conducted a within-subjects experiment in a Virtual Reality (VR) driving simulator with AR overlays. Participants experienced three interface concepts: (A) no transparency, (B) system-level transparency (ego vehicle intentions only), and (C) environment-level transparency (cooperation intentions, planned paths, and infrastructure). Results show that environment-level transparency, despite the higher cognitive workload, enhanced trust in both ego and cooperating FAVs.