Natural language processing for aviation safety: extracting knowledge from publicly-available loss of separation reports.

ABSTRACT:

Background

The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it is crucial to automatically analyse the losses of separation (LoSs) using tools able to extract meaningful and actionable information from safety reports. Current research in this field mainly exploits natural language processing (NLP) to categorise the reports,with the limitations that the considered categories need to be manually annotated by experts and that general taxonomies are seldom exploited.

Methods

To address the current gaps,authors propose to perform exploratory data analysis on safety reports combining state-of-the-

SUBMITTER: Buselli I 

PROVIDER: S-EPMC10445863 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature