Multi-agent Modeling of Human Traffic Dynamics for Rapid Response to Public Emergency in Spatial Networks

Xiaoru Shi, Hankang Lee, Hui Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024
PublisherIEEE Computer Society
Pages374-380
Number of pages7
ISBN (Electronic)9798350358513
DOIs
StatePublished - 2024
Event20th IEEE International Conference on Automation Science and Engineering, CASE 2024 - Bari, Italy
Duration: Aug 28 2024Sep 1 2024

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference20th IEEE International Conference on Automation Science and Engineering, CASE 2024
Country/TerritoryItaly
CityBari
Period8/28/249/1/24

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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