Exploratory Analysis of Unmanned Aircraft Sightings using Text Mining Academic Article uri icon

abstract

  • 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.

published proceedings

  • Transportation Research Record: Journal of the Transportation Research Board

author list (cited authors)

  • Das, S

citation count

  • 2

complete list of authors

  • Das, Subasish

publication date

  • January 2021