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Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

Galea, Edwin R., Finney, Kate M., Dixon, Andrew J., Siddiqui, Asim ORCID: 0000-0003-1090-871X and Cooney, David P. (2006) Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents. Journal of Aircraft, 43 (5). pp. 1272-1281. ISSN 0021-8669 (Print), 1533-3868 (Online) (doi:10.2514/1.19388)

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Abstract

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

Item Type: Article
Uncontrolled Keywords: AASK, survivable aviation accidents, evacuation procedure, aviation safety
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Fire Safety Engineering Group
School of Computing & Mathematical Sciences > Department of Computer Science
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/979

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