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An Improved Evacuation Guidance System Based on Ant Colony Optimization

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Intelligent and Evolutionary Systems

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 5))

Abstract

This paper proposes an evacuation guidance method for use in disaster situations. The method is based on ant colony optimization (ACO). We have implemented the method as ACO-based evacuation system in a simulator and examined the feasibility of the system. Since we cannot depend on the communication infrastructures with a disaster occurs, we make the system utilize mobile ad hoc network (MANET). We expect the ACO-based evacuation system produces quasi-optimized evacuation paths by the cooperation of multiple agents, while MANET provides communication between agents in the environment lacking of network infrastructure. Even though a number of ACO-based guidance systems have been developed, there are still some questions whether evacuees who follow the evacuation paths given by ACO are really safe. We examined how safe following these paths is by simulations, and found that they were not safe in some cases. As a result, in this paper, we propose an improved ACO-based evacuation system that equips deodorant pheromone to actively erase ACO pheromone traces when dangerous locations are found. Our simulation results show the use of deodorant pheromone can improve the safety level of the evacuation guidance system without degrading evacuation efficiency.

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Author information

Authors and Affiliations

  1. Department of Information Sciences, Tokyo University of Science, Tokyo, Japan

    Asuka Ohta, Hirotaka Goto, Tomofumi Matsuzawa, Munehiro Takimoto & Masayuki Takeda

  2. Department of Computer and Information Engineering, Nippon Institute of Technology, Saitama, Japan

    Yasushi Kambayashi

Authors
  1. Asuka Ohta
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  2. Hirotaka Goto
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  3. Tomofumi Matsuzawa
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  4. Munehiro Takimoto
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  5. Yasushi Kambayashi
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  6. Masayuki Takeda
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Corresponding author

Correspondence to Asuka Ohta .

Editor information

Editors and Affiliations

  1. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Kittichai Lavangnananda

  2. School of Computing and Informatics, Institut Teknologi Brunei, Gadong, Brunei Darussalam

    Somnuk Phon-Amnuaisuk

  3. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Worrawat Engchuan

  4. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Jonathan H. Chan

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© 2016 Springer International Publishing Switzerland

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Ohta, A., Goto, H., Matsuzawa, T., Takimoto, M., Kambayashi, Y., Takeda, M. (2016). An Improved Evacuation Guidance System Based on Ant Colony Optimization. In: Lavangnananda, K., Phon-Amnuaisuk, S., Engchuan, W., Chan, J. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-27000-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-27000-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26999-3

  • Online ISBN: 978-3-319-27000-5

  • eBook Packages: EngineeringEngineering (R0)

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