This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two-level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post-vignette questions and essentially ask "Would you" or "Would you not" be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the "prior" and "posterior" sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%.

When operating under Visual Flight Rules, pilots primarily rely on visual scanning to avoid other aircraft and airborne collision threats. Records from the Federal Aviation Administration indicate that near encounters with unmanned aircraft are on the rise, reaching 1,761 reported unmanned aircraft system (UAS) sightings or near-misses in 2016. This study sought to assess the effectiveness of pilot visual detection of UAS platforms that were equipped with strobe lighting. A sample of 10 pilots flew a general aviation aircraft on a scripted series of five intercepts with a small UAS (sUAS) that was equipped with strobe lighting. Participants were asked to indicate when they visually detected the unmanned aircraft. Geolocation information for both the aircraft and sUAS platform was compared to assess visibility distance. Findings were used to evaluate the efficacy of daytime strobe lighting as a method to enhance pilot sUAS detection, visibility, and collision avoidance. Participants detected the unmanned aircraft during 7.7% of the intercepts. Due to a lack of data points, the authors were unable to conclusively determine if strobe lighting improved UAS visual detection. The authors recommend further research to explore the effectiveness of using sUAS-mounted strobe lights for nighttime visual detection.

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