When and How to Explain: Designing Human-Machine Interfaces for Pilotless Urban Air Mobility

Urban Air Mobility (UAM) is expected to operate without onboard pilots, raising concerns about passenger trust in automation. Building on findings from autonomous vehicle (AV) research, this study investigates whether explanation-based human-machine interfaces (HMIs) can enhance trust in UAM. We developed a virtual simulation with five conditions, varying the type (how vs. how+why) and timing (pre-event vs. post-event) of system-generated explanations. A baseline condition with no explanation was also included. Participants will experience multiple UAM issue events (e.g., fog, gusts), during which trust, transparency, and competence are measured. We anticipate that both how and why explanations will increase trust, with why and pre-event explanations expected to have stronger effects. Our findings will inform the design of explainable UAM systems that foster psychological comfort and acceptance.