Editing Evacuation simulation (section)

== Classification of models ==
Modelling approaches in the field of evacuation simulation:
* Cellular automaton: discrete, microscopic models, where the pedestrian is represented by a cell state.  In this case both statics and dynamic floor fields (i.e., distance maps) are used to navigate agents toward exits moving from a cell to adjacent cells which can have different shapes.<ref>{{Cite journal |last=Burstedde |first=C |last2=Klauck |first2=K |last3=Schadschneider |first3=A |last4=Zittartz |first4=J |date=2001-06-15 |title=Simulation of pedestrian dynamics using a two-dimensional cellular automaton |url=https://www.sciencedirect.com/science/article/pii/S0378437101001418 |journal=Physica A: Statistical Mechanics and its Applications |volume=295 |issue=3 |pages=507–525 |doi=10.1016/S0378-4371(01)00141-8 |issn=0378-4371|arxiv=cond-mat/0102397 }}</ref><ref>{{Cite journal |last=Kirchner |first=Ansgar |last2=Schadschneider |first2=Andreas |date=2002-09-01 |title=Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics |url=https://www.sciencedirect.com/science/article/pii/S0378437102008579 |journal=Physica A: Statistical Mechanics and its Applications |volume=312 |issue=1 |pages=260–276 |doi=10.1016/S0378-4371(02)00857-9 |issn=0378-4371|arxiv=cond-mat/0203461 }}</ref><ref>{{Cite journal |last=Lovreglio |first=Ruggiero |last2=Ronchi |first2=Enrico |last3=[[Professor Daniel Nilsson|Nilsson]] |first3=Daniel |date=2015-11-15 |title=Calibrating floor field cellular automaton models for pedestrian dynamics by using likelihood function optimization |url=https://www.sciencedirect.com/science/article/pii/S0378437115006007 |journal=Physica A: Statistical Mechanics and its Applications |volume=438 |pages=308–320 |doi=10.1016/j.physa.2015.06.040 |issn=0378-4371|url-access=subscription }}</ref> There exist models for ship evacuation processes,<ref>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.</ref> bi-directional pedestrian flows,<ref>{{Cite journal|last1=Blue|first1=Victor|last2=Adler|first2=Jeffrey|date=1999-01-01|title=Cellular Automata Microsimulation of Bidirectional Pedestrian Flows|journal=Transportation Research Record: Journal of the Transportation Research Board|volume=1678|pages=135–141|doi=10.3141/1678-17|s2cid=110675891 |issn=0361-1981}}</ref> general models with bionics aspects<ref>{{Cite journal|last1=Kirchner|first1=Ansgar|last2=Schadschneider|first2=Andreas|title=Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics|journal=Physica A: Statistical Mechanics and Its Applications|volume=312|issue=1–2|pages=260–276|doi=10.1016/s0378-4371(02)00857-9|arxiv=cond-mat/0203461|bibcode=2002PhyA..312..260K|year=2002|s2cid=119465496 }}</ref>
* Agent-based models: microscopic models, where the pedestrian is represented by an agent. The agents can have human attributes besides the coordinates. Their behavior can integrate stochastic nature. There exist general models with spatial aspects of pedestrian steps<ref>{{Cite journal|last1=Wirth|first1=Ervin|last2=Szabó|first2=György|date=2017-06-14|title=Overlap-avoiding Tickmodel: an Agent- and GIS-Based Method for Evacuation Simulations|journal=Periodica Polytechnica Civil Engineering|language=en|volume=62|issue=1|pages=72–79|doi=10.3311/PPci.10823|issn=1587-3773|doi-access=free}}</ref>
* Social Force Model: continuous, microscopic model, based on equations from physics<ref>{{Cite journal|last=Helbing|first=Dirk|date=1995|title=Social force model for pedestrian dynamics|journal=Physical Review E|volume=51|issue=5|pages=4282–4286|doi=10.1103/physreve.51.4282|pmid=9963139 |arxiv=cond-mat/9805244|bibcode=1995PhRvE..51.4282H|s2cid=29333691 }}</ref>
* Queuing models: macroscopic models which are based on the graphical representation of the geometry. The movement of the persons is represented as a [[Flow network|flow]] on this [[Graph (discrete mathematics)|graph]].
* Particle swarm optimization models: microscopic model, based on a fitness function which minimizes some properties of the evacuation (distance between pedestrians, distance between pedestrians and exits)<ref>{{Cite journal|last1=Izquierdo|first1=J.|last2=Montalvo|first2=I.|last3=Pérez|first3=R.|last4=Fuertes|first4=V.S.|title=Forecasting pedestrian evacuation times by using swarm intelligence|journal=Physica A: Statistical Mechanics and Its Applications|volume=388|issue=7|pages=1213–1220|doi=10.1016/j.physa.2008.12.008|bibcode=2009PhyA..388.1213I|year=2009}}</ref>
* Fluid-dynamic models: continuous, macroscopic models, where large crowds are modeled with coupled, nonlinear, partial differential equations<ref>{{Cite journal|last=Hughes|first=Roger L.|date=2003-01-01|title=The flow of human crowds|journal=Annual Review of Fluid Mechanics|volume=35|issue=1|pages=169–182|doi=10.1146/annurev.fluid.35.101101.161136|issn=0066-4189|bibcode=2003AnRFM..35..169H}}</ref><ref>{{Citation |last=Gwynne |first=Steven M. V. |title=Employing the Hydraulic Model in Assessing Emergency Movement |date=2016 |work=SFPE Handbook of Fire Protection Engineering |pages=2115–2151 |editor-last=Hurley |editor-first=Morgan J. |url=https://doi.org/10.1007/978-1-4939-2565-0_59 |access-date=2024-02-03 |place=New York, NY |publisher=Springer |language=en |doi=10.1007/978-1-4939-2565-0_59 |isbn=978-1-4939-2565-0 |last2=Rosenbaum |first2=Eric R. |editor2-last=Gottuk |editor2-first=Daniel |editor3-last=Hall |editor3-first=John R. |editor4-last=Harada |editor4-first=Kazunori|url-access=subscription }}</ref>