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Many coastal communities around the world are threatened by a near-field (or local) tsunami that could inundate the low-lying areas in a matter of minutes after generation. The universal consensus amongst emergency agencies and academic researchers is that a safe evacuation requires an effective response, which is typically assessed by the evacuation time estimate (ETE). ETE is an integral component of community emergency evacuation planning, especially areas prone to tsunamis. This paper aims to investigate the ETE for pedestrian evacuation during a tsunami through two different approaches: (1) the deterministic Least-Cost Distance (LCD) model; and (2) the dynamic Agent-Based Model (ABM). Then, the comparison of the two models in their intrinsic characteristics, strengths and weaknesses, and its applicability was discussed based on methodology behind of the LCD model and ABM. The LCD model was conducted to generate a spatially distributed ETE map, visualizing vulnerable areas where the evacuation time would be insufficient for individuals to reach safety. The ABM investigated uncertainty during tsunami evacuations, such as population distribution, walking speed, and milling time. This paper provides insights into the differences between the LCD model and ABM in terms of methodology and application. It assists the academic researchers and emergency managers, evacuation planners, and decision makers to choose an appropriate method for modeling pedestrian evacuation during tsunami.
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This content will become publicly available on August 28, 2025
Multi-agent Modeling of Human Traffic Dynamics for Rapid Response to Public Emergency in Spatial Networks
Public emergencies pose catastrophic casualties and financial losses in densely populated areas, rendering communities such as cities, towns, and universities particularly susceptible due to their intricate environments and high pedestrian traffic. While simulation analysis offers a flexible and cost-effective approach to evaluating evacuation procedures, conventional evacuation models are often limited to specific scenarios and communities, overlooking the diverse range of emergencies and evacuee behaviors. Thus, there is an urgent need for an evacuation model capable of capturing complex structures of communities and modeling evacuee responses to various emergencies. This paper presents a novel approach to simulating responsive evacuation behaviors for multiple emergency situations in public communities through spatial network modeling and multi-agent modeling. Leveraging a community network framework adaptable to different community layouts based on map data, the proposed model employs a multi-agent approach to characterize responsive and decentralized evacuation decision-making. Experimental results show the model’s efficacy in representing pedestrian flow and pedestrians’ reactive behavior across various campuses based on real-world map data. Additionally, the case study highlights the potential of the proposed model to simulate pedestrian dynamics for a variety of heterogeneous emergencies. The proposed community evacuation model holds strong promise for evaluating evacuation policies and providing insights into resilient plans during public emergencies, thereby enhancing community safety.
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- Award ID(s):
- 2302834
- PAR ID:
- 10553720
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-5851-3
- Page Range / eLocation ID:
- 374 to 380
- Subject(s) / Keyword(s):
- Public Emergency Spatial Network Behavioral Responses Network Model Community Structure Community Networks Multi-agent Approach Network Of Agents Occurrence Of Hazards Evacuation Routes Hazardous Agents
- Format(s):
- Medium: X
- Location:
- Bari, Italy
- Sponsoring Org:
- National Science Foundation
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