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Simulative Investigations of Crowd Evacuation by Incorporating Reinforcement Learning Scheme

Published: 30 January 2023 Publication History

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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  • (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

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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
        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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        Published: 30 January 2023

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        Author Tags

        1. Crowd Evacuation
        2. Evacuation Leader
        3. Reinforcement Learning
        4. Social Force Model

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        • (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

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