Asim Siddiqui

The UK WTC9/11 Evacuation Study: An Overview of the Methodologies Employed and Some Preliminary Analysis

This paper briefly describes the methodologies employed in the collection and storage of first-hand accounts of evacuation experiences derived from face-to-face interviews with evacuees from the World Trade Center (WTC) Twin Towers complex on 11 September 2001 and the development of the High-rise Evacuation Evaluation Database (HEED). The main focus of the paper is to present a preliminary analysis of data derived from the evacuation of the North Tower.

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.

Understanding and Simulating Large Crowds

Simulation tools are often used to establish pedestrian and evacuee performance. The accuracy and reliability of such tools are dependent upon their ability to qualitatively and quantitatively capture the outcome of this performance. This paper investigates the relationship between the representation of low-level agent actions and the generation of reliable emergent, high-level conditions that can then be used to better understand the conditions that may develop in large crowds and mitigate against them. Data has been collected concerning the movement of pilgrims during the Hajj. This paper presents a simple framework for categorizing these real-world observations and then translating them into the simulated environment – extracting key information from the data collected to configure the simulation tool as required. Several scenarios are simulated using the buildingEXODUS model to test the impact of representing these observations to a greater or lesser degree. This enables the importance of low-level behaviours upon emergent conditions to be investigated, even when simulating large numbers of pilgrims attending the Hajj; i.e. in large crowds. The relationship between low-level agent actions and the high-level emergent conditions is investigated using analytical and simulation tools. This paper should help future researchers (1) identify and extract key factors from crowd data and then (2) appropriately configure simulation tools to represent agent behaviour and the subsequent emergent conditions produced (e.g. congestion, flow patterns, etc.).

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.