Because of recent technological advancements, a growing number of unmanned aircraft systems (UASs) are anticipated to occupy the U.S. National Airspace System (NAS) and operate side-by-side with human pilot controlled civil aircraft. UAS technology has transitioned to broader applications, including commercial, scientific, and expanded military use. There have been significant challenges concerning the safe and suitable integration of UASs with existing systems. The interaction between humans and increasingly automated systems is of concern to researchers. Additionally, the number of UAS sightings has increased significantly during the last few years. In this study, the research team compiled 7,400 reports of UAS sightings (2015–2018). The Latent Dirichlet Allocation (LDA) method was then applied to develop topics relevant to UAS sighting incidents. This study also developed an online interactive tool to show keywords associated with different topics. These interactive topic models can help policymakers establish new policies and regulations to address specific safety concerns.

由于最近的技术进步，预计将有越来越多的无人机系统（UAS）占据美国国家空域系统（NAS），并与人类飞行员控制的民用飞机并排运行。UAS技术已经过渡到更广泛的应用，包括商业，科学和扩大的军事用途。安全和适当地将UAS与现有系统集成存在重大挑战。人与日益自动化的系统之间的交互是研究人员关注的问题。此外，在过去几年中，目击无人机的数量大大增加。在这项研究中，研究小组收集了7,400份UAS目击报告（2015-2018年）。然后，使用潜在狄利克雷分配（LDA）方法来开发与UAS目击事件有关的主题。这项研究还开发了一种在线互动工具，以显示与不同主题相关的关键字。这些交互式主题模型可以帮助决策者建立新的政策和法规，以解决特定的安全问题。