A New Pathfinding Evacuation Decision-Making Algorithm in Buildings on Fire Based on Personality Traits

The current research gives a different aspect to pathfinding algorithms in forgetting about an optimum route and offering more value to the current psychological state of a person, which is crucial in not having an ideal simulator where people run where they should be running (optimal route). Still, instead, they move based on their personality traits and reactions. The proposed algorithm is derived from the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{*}$</tex> algorithm; it introduces a psychological model known as the OCEAN model or big five for the heterogeneous crowd in a multiagent system that allows decision-making in pathfinding. The OCEAN model has five positive and negative dimensions. To simulate them, we created ten videos in Unity, considering animations with people moving under fire in different scenarios; we used the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Psi *$</tex> algorithm in these simulations to calculate the optimal route. Initially, we evaluated ten different personality trait adjectives. Later, we applied an online survey to validate our model through perceptions of people; the adjectives for pathfinding were reduced to four different types of personality traits due to the limitation that pathfinding can visually offer in a simulator and the relationships that the participants found between said definitions and similar routes thrown by the system. The most relevant results highlight that the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A^{*}$</tex> algorithm always yields the optimal evacuation route. That algorithm was modified in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Psi *$</tex> to simulate routes that lose optimality but are close to possible routes that a person with a specific personality type would take. Due to the different reactions of the crowd, our proposal can represent a more approximate real-life scenario of a building on fire.

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Published
2024-10-16
DOI
https://doi.org/10.1109/cimps65195.2024.11095951
Primary Topic
Evacuation and Crowd Dynamics
Type
article
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article

A New Pathfinding Evacuation Decision-Making Algorithm in Buildings on Fire Based on Personality Traits

Guillermo Santamaría-Bonfil, Nuria Pelechano, José Alberto Hernández Aguilar, Peter Oropeza-Martínez
Evacuation and Crowd Dynamics
article

A New Pathfinding Evacuation Decision-Making Algorithm in Buildings on Fire Based on Personality Traits

Guillermo Santamaría-Bonfil, Nuria Pelechano, José Alberto Hernández Aguilar, Peter Oropeza-Martínez
article en

Abstract

The current research gives a different aspect to pathfinding algorithms in forgetting about an optimum route and offering more value to the current psychological state of a person, which is crucial in not having an ideal simulator where people run where they should be running (optimal route). Still, instead, they move based on their personality traits and reactions. The proposed algorithm is derived from the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{*}$</tex> algorithm; it introduces a psychological model known as the OCEAN model or big five for the heterogeneous crowd in a multiagent system that allows decision-making in pathfinding. The OCEAN model has five positive and negative dimensions. To simulate them, we created ten videos in Unity, considering animations with people moving under fire in different scenarios; we used the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Psi *$</tex> algorithm in these simulations to calculate the optimal route. Initially, we evaluated ten different personality trait adjectives. Later, we applied an online survey to validate our model through perceptions of people; the adjectives for pathfinding were reduced to four different types of personality traits due to the limitation that pathfinding can visually offer in a simulator and the relationships that the participants found between said definitions and similar routes thrown by the system. The most relevant results highlight that the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$A^{*}$</tex> algorithm always yields the optimal evacuation route. That algorithm was modified in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\Psi *$</tex> to simulate routes that lose optimality but are close to possible routes that a person with a specific personality type would take. Due to the different reactions of the crowd, our proposal can represent a more approximate real-life scenario of a building on fire.

Universidad Americana de Morelos (MX), Universidad Filadelfia de México (MX), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 61%
Evacuation and Crowd Dynamics
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