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Information Sciences and Systems 2013 pp 295–303Cite as

Routing Emergency Evacuees with Cognitive Packet Networks

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 264))

Abstract

Providing optimal and safe routes to evacuees in emergency situations requires fast and adaptive algorithms. The common approaches are often too slow to converge, too complex, or only focus on one aspect of the problem, e.g. finding the shortest path. This paper presents an adaptation of the Cognitive Packet Network (CPN) concept to emergency evacuation problems. Using Neural Networks, CPN is able to rapidly explore a network and allocate overhead in proportion to the perceived likelihood of finding an optimal path there. CPN is also flexible, as it can operate with any user-defined cost function, such as congestion, path length, safety, or even compound metrics. We compare CPN with optimal algorithms such as Dijkstra’s Shortest Path using a discrete-event emergency evacuation simulator. Our experiments show that CPN reaches the performance of optimal path-finding algorithms. The resulting side-effect of such smart or optimal algorithms is in the greater congestion that is encountered along the safer paths; therefore we indicate how the quality of service objective used by CPN can also be used to avoid congestion for further improvements in evacuee exit times.

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Author information

Authors and Affiliations

  1. Intelligent Systems and Networks Group Department of Electrical and Electronic Engineering, Imperial College London, London, England

    Huibo Bi, Antoine Desmet & Erol Gelenbe

Authors
  1. Huibo Bi
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  2. Antoine Desmet
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  3. Erol Gelenbe
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Corresponding author

Correspondence to Huibo Bi .

Editor information

Editors and Affiliations

  1. Dept of Electrical and Electronics Eng, Imperial College, London, United Kingdom

    Erol Gelenbe

  2. Imperial College, London, United Kingdom

    Ricardo Lent

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© 2013 Springer International Publishing Switzerland

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Bi, H., Desmet, A., Gelenbe, E. (2013). Routing Emergency Evacuees with Cognitive Packet Networks. In: Gelenbe, E., Lent, R. (eds) Information Sciences and Systems 2013. Lecture Notes in Electrical Engineering, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-01604-7_29

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  • DOI: https://doi.org/10.1007/978-3-319-01604-7_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01603-0

  • Online ISBN: 978-3-319-01604-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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