A Review of Building Evacuation Models - NIST Virtual Library

A.21 Egress Complexity Model
Developer: H.A. Donegan, University of Ulster, UK
Purpose of the model: The purpose of this model is to provide results on egress uncertainty
related to the building and provide a measure of complexity of the building structure 89, 90 . This is
not a traditional egress model in that it does not calculate egress times for a certain population,
but instead uses an entropy probability to simulate the expected information content, and in turn,
the complexity of the floor plan. This model is considered to be a macroscopic model, which
focuses on evacuation routes and the population as a whole, instead of individual elements
(microscopic).
Availability to the public for use: Unknown.
Modeling method: This is a movement model/partial behavioral model
Structure of model: This is a coarse network system. Each compartment (room, stairwell, or
area that can be occupied) is labeled as a node. Arcs are then drawn between the nodes on the
floor plan.
Perspective of model and occupant: This model is not a traditional evacuation model with
occupants traveling throughout the building from initial starting points in order to calculate an
evacuation time. This model uses the probabilities of acquiring knowledge (or not) to calculate
the complexity of the space. The model views the occupants (if at all) in more of a global
manner. There are not individual characteristics given to each person that would make them
unique in an evacuation.
The occupants have a semi-individual view of the building because of the fact that they can
backtrack due to a lack of acquiring information. They are simulated as having an unfamiliar
view of the building. On the other hand, in the basic model, the occupants only have one exit to
choose from (all networks are trees).
Occupant behavior: The model is labeled as not simulating behavior.
Occupant movement: The concept of entropy is used in thermodynamics to describe a measure
of disorganization of a physical system. In 1948, the name or label of entropy was adopted by
Shannon as a measure of uncertainty 91 . Shannon entropy is expressed by the following equation:
H(p(x) | x ∈ X) = -∑ p(x) log 2 p(x) where the summation is over x and p(x) is the probability
distribution on a finite set X. The Shannon entropy (the expected information content) which is
used by this Egress Complexity model, is the equation above given that ∑ p(x) = 1.
This model focuses on the concept of “acquiring knowledge with respect to egress.” Throughout
the simulation, knowledge is gained by achieving positive movement along an arc from one node
to another. This type of movement is used to simulate acquiring one packet of knowledge on
one information step and is labeled as a positive instance. If an arc is backtracked, knowledge is
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