Evaluating and enhancing user trust in urban air mobility autonomous passenger systems

Abstract

Urban Air Mobility (UAM) is an emerging and disruptive technology which promises a significant increase in transportation network capacity, through means of Passenger Air Vehicles (PAVs). Successful implementation of these aerial vehicles, however, is largely dependent on acceptance and eventual use by the general public. This dissertation, conducted in two phases, aimed to interpret decision and motivation factors for individuals to use and trust this novel transportation technology. In the first phase of the research study, a survey of 407 respondents in the United States provided perceptions and expectations of on-demand PAVs and autonomous aerial transportation concepts. Both the Technology Adoption Life Cycle Model and Technology Acceptance Model were used as constructs to characterize technology adopter profiles and rates of adoption. Key results, in which half of the respondents had prior familiarity with PAVs, indicated that all respondents expected additional in-flight safety feedback (i.e., displays relating to current and projected flight operations) beyond the level of safety standards found in conventional aircraft (i.e., seatbelts, air quality). Participants also indicated that PAVs are not perceived as an immediate replacement for daily trips and that in-cabin noise, which is often cited as a concern with community PAV acceptance, was not a crucial deterrent to ridership. Respondents characterized as earlier adopters of PAVs were more trusting of PAV technology, willing to pay more to ride, report shorter daily commutes, and riskier in their overall general behaviors. Later PAV adopters required more feedback in-flight and a pilot on-board to consider riding. Leveraging the insights gained from the first phase of the research study, the second phase focused on addressing critical human factors for building passenger trust, particularly in the absence of a human pilot. Virtual PAV flight simulations were conducted to evaluate how different in-cabin human-machine interface (HMI) designs affected passenger trust in the aircraft and in-cabin display, situation awareness, and pilot preferences. Forty participants, equally split between early and late technology adopters, completed two simulated flights: a baseline flight without an HMI in use, and a second flight featuring one of four HMI types: information, audio, video with a professionally dressed remote pilot, or video with a casually dressed remote pilot. Results indicated that participants exposed to the professionally dressed remote operator reported significantly higher trust in the aircraft, trust in the HMI, and demonstrated higher situation awareness. Trust and situation awareness were not significantly influenced by technology adopter profile. Participants also stated a preference for the presence of an audible or visible remote operator, particularly among late technology adopters. These findings suggest that human-centered HMI designs, especially those that include visual cues of professionalism, can meaningfully improve passenger trust in autonomous air taxis. Overall, this dissertation contributes to both theory and practice by advancing understanding of technology adoption in the context of UAM and by identifying actionable design strategies for fostering passenger trust in autonomous PAVs. By bridging adoption theory with applied human factors research, the findings provide a roadmap for stakeholders to anticipate user needs, mitigate barriers to acceptance, and support the safe and successful integration of PAVs into future transportation systems.