Evacuation simulation is a method to determine evacuation times for areas, buildings, or vessels. It is based on the simulation of crowd dynamics and pedestrian motion. The number of evacuation software have been increased dramatically in the last 25 years.[1][2] One of the latest survey indicate the existence of over 70 pedestrian evacuation models.[3] Today there are two conferences dedicated to this subject: "Pedestrian Evacuation Dynamics" and "Human Behavior in Fire".[4][5]

The distinction between buildings, ships, and vessels on the one hand and settlements and areas on the other hand is important for the simulation of evacuation processes. In the case of the evacuation of a whole district, the transport phase (see emergency evacuation) is usually covered by queueing models (see below).

Pedestrian evacuation simulation are popular in the fire safety design of building when a performance based approach is used.[6] Simulations are not primarily methods for optimization. To optimize the geometry of a building or the procedure with respect to evacuation time, a target function has to be specified and minimized. Accordingly, one or several variables must be identified which are subject to variation.

Classification of models

Modelling approaches in the field of evacuation simulation:

Simulation of evacuations

Buildings (train stations, sports stadia), ships, aircraft, tunnels, and trains are similar concerning their evacuation: the persons are walking towards a safe area. In addition, persons might use slides or similar evacuation systems and for ships the lowering of life-boats.[18]

Tunnels

Tunnels are unique environments with their own specific characteristics: underground spaces, unknown to users, no natural light, etc. which affect different aspects of evacuees behaviours such as pre-evacuation times (e.g. occupants' reluctance to leave the vehicles), occupant–occupant and occupant–environment interactions, herding behaviour and exit selection.

Ships

Four aspects are particular for ship evacuation:

Ship motion and/or abnormal floating position may decrease the ability to move. This influence has been investigated experimentally and can be taken into account by reduction factors.

The evacuation of a ship is divided into two separate phases: assembly phase and embarkation phase.

Aircraft

The American Federal Aviation Administration requires that aircraft have to be able to be evacuated within 90 seconds. This criterion has to be checked before approval of the aircraft.

The 90-second rule requires the demonstration that all passengers and crew members can safely abandon the aircraft cabin in less than 90 seconds, with half of the usable exits blocked, with the minimum illumination provided by floor proximity lighting, and a certain age-gender mix in the simulated occupants.

The rule was established in 1965 with 120 seconds, and has been evolving over the years to encompass the improvements in escape equipment, changes in cabin and seat material, and more complete and appropriate crew training.

References

  1. ^ Kuligowski, Erica D.; Peacock, Richard D.; Hoskins, Bryan L. (2010-11-01). "A Review of Building Evacuation Models, 2nd Edition". NIST.
  2. ^ Gwynne, S.; Galea, E. R.; Owen, M.; Lawrence, P. J.; Filippidis, L. (1999-11-01). "A review of the methodologies used in the computer simulation of evacuation from the built environment". Building and Environment. 34 (6): 741–749. doi:10.1016/S0360-1323(98)00057-2. ISSN 0360-1323.
  3. ^ Lovreglio, Ruggiero; Ronchi, Enrico; Kinsey, Michael J. (2020-05-01). "An Online Survey of Pedestrian Evacuation Model Usage and Users". Fire Technology. 56 (3): 1133–1153. doi:10.1007/s10694-019-00923-8. ISSN 1572-8099.
  4. ^ "Pedestrian and Evacuation Dynamics | Collective Dynamics". collective-dynamics.eu. Retrieved 2024-02-03.
  5. ^ "Human Behaviour in Fire Symposium 2015". www.intersciencecomms.co.uk. Retrieved 2024-02-03.
  6. ^ Kuligowski, Erica D. (2016), Hurley, Morgan J.; Gottuk, Daniel; Hall, John R.; Harada, Kazunori (eds.), "Computer Evacuation Models for Buildings", SFPE Handbook of Fire Protection Engineering, New York, NY: Springer, pp. 2152–2180, doi:10.1007/978-1-4939-2565-0_60, ISBN 978-1-4939-2565-0, retrieved 2024-02-03
  7. ^ Burstedde, C; Klauck, K; Schadschneider, A; Zittartz, J (2001-06-15). "Simulation of pedestrian dynamics using a two-dimensional cellular automaton". Physica A: Statistical Mechanics and its Applications. 295 (3): 507–525. arXiv:cond-mat/0102397. doi:10.1016/S0378-4371(01)00141-8. ISSN 0378-4371.
  8. ^ Kirchner, Ansgar; Schadschneider, Andreas (2002-09-01). "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics". Physica A: Statistical Mechanics and its Applications. 312 (1): 260–276. arXiv:cond-mat/0203461. doi:10.1016/S0378-4371(02)00857-9. ISSN 0378-4371.
  9. ^ Lovreglio, Ruggiero; Ronchi, Enrico; Nilsson, Daniel (2015-11-15). "Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization". Physica A: Statistical Mechanics and its Applications. 438: 308–320. doi:10.1016/j.physa.2015.06.040. ISSN 0378-4371.
  10. ^ Meyer-König, T., Klüpfel, H., & Schreckenberg, M. (2002). Assessment and analysis of evacuation processes on passenger ships by microscopic simulation. Schreckenberg and Sharma [2], 297-302.
  11. ^ Blue, Victor; Adler, Jeffrey (1999-01-01). "Cellular Automata Microsimulation of Bidirectional Pedestrian Flows". Transportation Research Record: Journal of the Transportation Research Board. 1678: 135–141. doi:10.3141/1678-17. ISSN 0361-1981. S2CID 110675891.
  12. ^ Kirchner, Ansgar; Schadschneider, Andreas (2002). "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics". Physica A: Statistical Mechanics and Its Applications. 312 (1–2): 260–276. arXiv:cond-mat/0203461. Bibcode:2002PhyA..312..260K. doi:10.1016/s0378-4371(02)00857-9. S2CID 119465496.
  13. ^ Wirth, Ervin; Szabó, György (2017-06-14). "Overlap-avoiding Tickmodel: an Agent- and GIS-Based Method for Evacuation Simulations". Periodica Polytechnica Civil Engineering. 62 (1): 72–79. doi:10.3311/PPci.10823. ISSN 1587-3773.
  14. ^ Helbing, Dirk (1995). "Social force model for pedestrian dynamics". Physical Review E. 51 (5): 4282–4286. arXiv:cond-mat/9805244. Bibcode:1995PhRvE..51.4282H. doi:10.1103/physreve.51.4282. PMID 9963139. S2CID 29333691.
  15. ^ Izquierdo, J.; Montalvo, I.; Pérez, R.; Fuertes, V.S. (2009). "Forecasting pedestrian evacuation times by using swarm intelligence". Physica A: Statistical Mechanics and Its Applications. 388 (7): 1213–1220. Bibcode:2009PhyA..388.1213I. doi:10.1016/j.physa.2008.12.008.
  16. ^ Hughes, Roger L. (2003-01-01). "The flow of human crowds". Annual Review of Fluid Mechanics. 35 (1): 169–182. Bibcode:2003AnRFM..35..169H. doi:10.1146/annurev.fluid.35.101101.161136. ISSN 0066-4189.
  17. ^ Gwynne, Steven M. V.; Rosenbaum, Eric R. (2016), Hurley, Morgan J.; Gottuk, Daniel; Hall, John R.; Harada, Kazunori (eds.), "Employing the Hydraulic Model in Assessing Emergency Movement", SFPE Handbook of Fire Protection Engineering, New York, NY: Springer, pp. 2115–2151, doi:10.1007/978-1-4939-2565-0_59, ISBN 978-1-4939-2565-0, retrieved 2024-02-03
  18. ^ Evacuation Modelling using FDS+Evac, PathFinder, STEPS and Unity3D, retrieved 2024-02-03

Literature

Categories