A Review of Building Evacuation Models - NIST Virtual Library

The purpose of this matrix is to model the sequence of first actions. “TS” is the time for the staff
to check certain areas/rooms of the building, which depends on the communication or
information events. Each corresponding behaviour/action is explained below:
• “Awareness” is the time interval beginning with the perception of the first cue to the time
that the person becomes aware of the evacuation situation
• “Response Time” is the average time interval to respond to the corresponding cue. The
model uses average times used by Levin which are 6 s for awake individuals and 10 s for
sleeping occupants.
• “Prepare” is the time interval allowing the occupant to dress and look for valuables. This
action depends on the weather and the geographical location.
• “Information” represents the time delay for occupants to seek for information and “inform
others” of the event.
Individual responses to hazards in the building (actual or suspected) depend on individual
specified parameters, external conditions, available information, and social relations among the
occupants. Most of these parameters vary with the changing environment of the evacuation.
ASERI uses Monte Carlo simulation techniques to analyze the outcome of a building evacuation
by stochastically altering individual responses while leaving the initial and boundary conditions
identical. By performing this type of simulation, mean egress times as well as corresponding
variances and confidence limits can be obtained. Such stochastic variables include individual
egress route choice and movement, the initial distribution of occupants throughout the building,
and individual parameters (size, walking speed, and reaction times).
Occupant movement: The movement of the occupants is defined by an individual walking
speed and the orientation of the corresponding velocity vector, resulting from the person’s
current position and intended exit/goal. Also, obstacles and other occupants affect movement.
ASERI takes note of individual body size by incorporating shoulder and chest width into the
model. From this, minimum inter-person distance and boundary layer from walls and obstacles
are used to move people throughout the building. Shoulder and chest width, certain behavioral
conditions, and walking speeds are entered as distributions or individual input, which affect the
mobility of the occupants. Different groups can be generated from these inputs, including those
occupants who are disabled (simulated by, for example a lower walking speed or a larger body
size to account for a wheelchair). ASERI allows the user to input persons with increased space
requirement, such as occupants carrying children, briefcases, or wheelchair mobile. Because of
these calculations, ASERI can model congestion, queuing, clustering, and merging of flows of
occupants.
Individual movement of the occupants is driven by their global (exit or refuge area) and local
(room exits, corners, etc.) goals. The local goals of the occupant change dynamically with the
environment and crowd conditions. There is no grid in the model upon which the occupants
move through. Instead the individual local goals of the occupants trigger movement, depending
upon the geometry of the building (interior doors, obstacles, corners, etc.). The developer has
explained the movement model as a sequential one with priority rules for movement.
Toxic effects of the smoke components slow walking speed, alter behavioral responses, and
change designated route plans. Individual incapacitation of the occupants is calculated by using
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