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Graph and Analytical Models for Emergency Evacuation

Author

Listed:
  • Antoine Desmet

    (Intelligent Systems and Networks, Department of Electrical and Electronic Engineering, Imperial College, London SW7 2BT, UK)

  • Erol Gelenbe

    (Intelligent Systems and Networks, Department of Electrical and Electronic Engineering, Imperial College, London SW7 2BT, UK)

Abstract

Cyber-Physical-Human Systems (CPHS) combine sensing, communication and control to obtain desirable outcomes in physical environments for human beings, such as buildings or vehicles. A particularly important application area is emergency management. While recent work on the design and optimisation of emergency management schemes has relied essentially on discrete event simulation, which is challenged by the substantial amount of programming or reprogramming of the simulation tools and by the scalability and the computing time needed to obtain useful performance estimates, this paper proposes an approach that offers fast estimates based on graph models and probability models. We show that graph models can offer insight into the critical areas in an emergency evacuation and that they can suggest locations where sensor systems are particularly important and may require hardening. On the other hand, we also show that analytical models based on queueing theory can provide useful estimates of evacuation times and for routing optimisation. The results are illustrated with regard to the evacuation of a real-life building.

Suggested Citation

  • Antoine Desmet & Erol Gelenbe, 2013. "Graph and Analytical Models for Emergency Evacuation," Future Internet, MDPI, vol. 5(1), pages 1-10, February.
    • Handle: RePEc:gam:jftint:v:5:y:2013:i:1:p:46-55:d:23698
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    References listed on IDEAS

    as
    1. Bakuli, David L. & MacGregor Smith, J., 1996. "Resource allocation in state-dependent emergency evacuation networks," European Journal of Operational Research, Elsevier, vol. 89(3), pages 543-555, March.
    2. Erol Gelenbe, 2003. "Sensible decisions based on QoS," Computational Management Science, Springer, vol. 1(1), pages 1-14, December.
    3. MacGregor Smith, J., 1991. "State-dependent queueing models in emergency evacuation networks," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 373-389, December.
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    Cited by:

    1. Huibo Bi, 2014. "Routing Diverse Evacuees with the Cognitive Packet Network Algorithm," Future Internet, MDPI, vol. 6(2), pages 1-20, April.
    2. Qing Han, 2013. "Managing Emergencies Optimally Using a Random Neural Network-Based Algorithm," Future Internet, MDPI, vol. 5(4), pages 1-20, October.
    3. Erol Gelenbe & Fang-Jing Wu, 2013. "Future Research on Cyber-Physical Emergency Management Systems," Future Internet, MDPI, vol. 5(3), pages 1-19, June.

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