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Simulative Investigations of Crowd Evacuation by Incorporating Reinforcement Learning Scheme

Authors:

Nitinun Sinpan,

Pruk Sasithong,

Sushank Chaudhary,

Suvit Poomrittigul,

Lunchakorn WuttisittikulkijAuthors Info & Claims

ICACS '22: Proceedings of the 6th International Conference on Algorithms, Computing and Systems

Article No.: 1, Pages 1 - 5

https://doi.org/10.1145/3564982.3564983

Published: 30 January 2023 Publication History

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Abstract

Safe and effective evacuation is very essential to decrease casualties in an emergency event. The social force model is used to simulate the movement of evacuee and leader crowd evacuation with leader in an experimental area. The a-star algorithm is used to find the evacuation routes of each evacuee from the initial location to the exit. In this paper, we proposed the application of reinforcement learning to train the agent to become an evacuation leader via the Unity ML-Agents Toolkit. This model is tested in three scenarios: an evacuation without a leader, an evacuation with a leader, and an evacuation with randomly located agent. They are considered for comparison purposes to show the impact of an agent that tries to tell an exit to all evacuees in the experimental area. The experimental results show that the proposed crowd evacuation agent could effectively evacuate all evacuees in the experimental area.

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Cited By

Yaman M(2024)Effect of Classroom Arrangement on Fire Evacuation Scenarios in Educational BuildingsJournal of Architectural/Planning Research and Studies (JARS)10.56261/jars.v22.27128622:1(271286)Online publication date: 26-Dec-2024
https://doi.org/10.56261/jars.v22.271286
Chaudhary SSinpan NSasithong PKhichar Sla-Aiddee PLeelawat NParnianifard APoomrittigul SWuttisittikulkij L(2024)Proximal Policy Optimization for Crowd Evacuation in Complex Environments—A Metaverse Approach at Krung Thep Aphiwat Central Terminal, ThailandIEEE Access10.1109/ACCESS.2024.351515312(196969-196983)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3515153

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Simulative Investigations of Crowd Evacuation by Incorporating Reinforcement Learning Scheme
1. Computing methodologies

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cover image ACM Other conferences

ICACS '22: Proceedings of the 6th International Conference on Algorithms, Computing and Systems

September 2022

132 pages

ISBN:9781450397407

DOI:10.1145/3564982

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 January 2023

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ICACS 2022

ICACS 2022: 2022 The 6th International Conference on Algorithms, Computing and Systems

September 16 - 18, 2022

Larissa, Greece

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Cited By

Yaman M(2024)Effect of Classroom Arrangement on Fire Evacuation Scenarios in Educational BuildingsJournal of Architectural/Planning Research and Studies (JARS)10.56261/jars.v22.27128622:1(271286)Online publication date: 26-Dec-2024
https://doi.org/10.56261/jars.v22.271286
Chaudhary SSinpan NSasithong PKhichar Sla-Aiddee PLeelawat NParnianifard APoomrittigul SWuttisittikulkij L(2024)Proximal Policy Optimization for Crowd Evacuation in Complex Environments—A Metaverse Approach at Krung Thep Aphiwat Central Terminal, ThailandIEEE Access10.1109/ACCESS.2024.351515312(196969-196983)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3515153

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