AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

Analysis of species hyper-diversity in the tropical rain forests of Indonesia: the problem of non-observance

The main interest in the assessment of forest species diversity for conservation purposes is in the rare species. The main problem in the tropical rain forests is that most of the species are rare. Assessment of species diversity in the tropical rain forests is therefore often concerned with estimating that which is not observed in recorded samples. Statistical methodology is therefore required to try to estimate the truncated tail of the species frequency distribution, or to estimate the asymptote of species/diversity-area curves. A Horvitz-Thompson estimator of the number of unobserved (“virtual”) species in each species intensity class is proposed. The approach allows a definition of an extended definition of diversity, ( or generalised Renyi entropy). The paper presents a case study from data collected in Jambi, Sumatra, and the “extended diversity measure” is used on the species data.

[Book Review] A database of North American tertiary mammals

Review of: Janis, C.M., Scott, K.M., & Jacobs, L.L. (eds.) 1998. Evolution of Tertiary Mammals of North America Volume 1: Terrestrial Carnivores, Ungulates, and Ungulatelike Mammals, i-x, 1491. Cambridge University Press, Cambridge, UK. £165

An analysis of human behaviour during aircraft evacuation situations using the AASK v3.0 database

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. 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 is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

The AASK Database V3.0: a database of human experience during aircraft evacuation incidents

This paper describes recent developments with the Aircraft Accident Statistics and Knowledge (AASK) database. The AASK database is a repository of survivor accounts from aviation accidents developed by the Fire Safety Engineering Group of the University of Greenwich with support from the UK CAA. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. Access to the latest version of the database (AASK V3.0) is available over the Internet. AASK consists of information derived from both passenger and cabin crew interviews, information concerning fatalities and basic accident details. Also provided with AASK is the Seat Plan Viewer that graphically displays the starting locations of all the passengers - both survivors and fatalities - as well as the exits used by the survivors. Data entered into the AASK database is extracted from the transcripts supplied by the National Transportation Safety Board in the US and the Air Accident Investigation Branch in the UK. The quality and quantity of the data was very variable ranging from short summary reports of the accidents to boxes of individual accounts from passengers, crew and investigators. Data imported into AASK V3.0 includes information from 55 accidents and individual accounts from 1295 passengers and 110 crew.

Models and tools for an integrated European environmental management and decision support system, (IEEMDSS)

This work proceeds from the assumption that a European environmental information and communication system (EEICS) is already established. In the context of primary users (land-use planners, conservationists, and environmental researchers) we ask what use may be made of the EEICS for building models and tools which is of use in building decision support systems for the land-use planner. The complex task facing the next generation of environmental and forest modellers is described, and a range of relevant modelling approaches are reviewed. These include visualization and GIS; statistical tabulation and database SQL, MDA and OLAP methods. The major problem of noncomparability of the definitions and measures of forest area and timber volume is introduced and the possibility of a model-based solution is considered. The possibility of using an ambitious and challenging biogeochemical modelling approach to understanding and managing European forests sustainably is discussed. It is emphasised that all modern methodological disciplines must be brought to bear, and a heuristic hybrid modelling approach should be used so as to ensure that the benefits of practical empirical modelling approaches are utilised in addition to the scientifically well-founded and holistic ecosystem and environmental modelling. The data and information system required is likely to end up as a grid-based-framework because of the heavy use of computationally intensive model-based facilities.

Towards the sustainable use of Europe’s forests: a centre for European forest science! – Some missing catalytic elements?

The Symposium, “Towards the sustainable use of Europe’s forests”, with sub-title “Forest ecosystem and landscape research: scientific challenges and opportunities” lists three fundamental substantive areas of research that are involved: Forest management and practices, Ecosystem processes and functional ecology, and Environmental economics and sociology. This paper argues that there are essential catalytic elements missing! Without these elements there is great danger that the aimed-for world leadership in the forest sciences will not materialize. What are the missing elements? All the sciences, and in particular biology, environmental sciences, sociology, economics, and forestry have evolved so that they include good scientific methodology. Good methodology is imperative in both the design and analysis of research studies, the management of research data, and in the interpretation of research finding. The methodological disciplines of Statistics, Modelling and Informatics (“SMI”) are crucial elements in a proposed Centre of European Forest Science, and the full involvement of professionals in these methodological disciplines is needed if the research of the Centre is to be world-class. Distributed Virtual Institute (DVI) for Statistics, Modelling and Informatics in Forestry and the Environment (SMIFE) is a consortium with the aim of providing world-class methodological support and collaboration to European research in the areas of Forestry and the Environment. It is suggested that DVI: SMIFE should be a formal partner in the proposed Centre for European Forest Science.

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

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

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.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.