Enhancing Evacuation Planning through Multi-Agent Simulation and Artificial Intelligence: Understanding Human Behavior in Hazardous Environments

TL;DR

This paper uses Multi-Agent Systems and AI to simulate human evacuation behavior in hazardous environments, aiming to improve evacuation strategies and safety planning.

Contribution

It introduces a simulation model based on MAS and AI techniques using NetLogo to better understand human responses during evacuations.

Findings

Enhanced understanding of human behavior in evacuation scenarios

Improved decision-making tools for emergency planners

Potential for more effective evacuation strategies

Abstract

This paper focuses on the crucial task of addressing the evacuation of hazardous places, which holds great importance for coordinators, event hosts, and authorities. To facilitate the development of effective solutions, the paper employs Artificial Intelligence (AI) techniques, specifically Multi-Agent Systems (MAS), to construct a simulation model for evacuation. NetLogo is selected as the simulation tool of choice due to its ability to provide a comprehensive understanding of human behaviour in distressing situations within hazardous environments. The primary objective of this paper is to enhance our comprehension of how individuals react and respond during such distressing situations. By leveraging AI and MAS, the simulation model aims to capture the complex dynamics of evacuation scenarios, enabling policymakers and emergency planners to make informed decisions and implement more efficient and effective evacuation strategies. This paper endeavours to contribute to the advancement of evacuation planning and ultimately improve the safety and well-being of individuals in hazardous places