MAAISep 3, 2019

Modelling Bushfire Evacuation Behaviours

arXiv:1909.00991v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses bushfire evacuation planning for Australian regional communities, but it is incremental as it builds on existing agent-based modeling and cognitive frameworks without introducing a new paradigm.

The paper tackled the problem of modeling bushfire evacuation behaviors by developing an agent-based model that integrates Belief-Desire-Intention cognitive models to simulate diverse human responses, aiming to improve evacuation strategies and community resilience.

Bushfires pose a significant threat to Australia's regional areas. To minimise risk and increase resilience, communities need robust evacuation strategies that account for people's likely behaviour both before and during a bushfire. Agent-based modelling (ABM) offers a practical way to simulate a range of bushfire evacuation scenarios. However, the ABM should reflect the diversity of possible human responses in a given community. The Belief-Desire-Intention (BDI) cognitive model captures behaviour in a compact representation that is understandable by domain experts. Within a BDI-ABM simulation, individual BDI agents can be assigned profiles that determine their likely behaviour. Over a population of agents their collective behaviour will characterise the community response. These profiles are drawn from existing human behaviour research and consultation with emergency services personnel and capture the expected behaviours of identified groups in the population, both prior to and during an evacuation. A realistic representation of each community can then be formed, and evacuation scenarios within the simulation can be used to explore the possible impact of population structure on outcomes. It is hoped that this will give an improved understanding of the risks associated with evacuation, and lead to tailored evacuation plans for each community to help them prepare for and respond to bushfire.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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