Modelling of Pedestrian and Evacuation Dynamics

Chraibi, Mohcine; Schadschneider, Andreas; Tordeux, Antoine; Seyfried, Armin

doi:10.1007/978-3-642-27737-5_705-1

Cited by 31 publications

(21 citation statements)

References 85 publications

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“…From the figure, one can see that for the first period (1360 seconds and 970 seconds respectively) nobody exits the ward. It takes a certain amount of time for people to move, because the fire needs to be detected and notified, the fire alarm needs to be propagated and the staff needs to organize the evacuation of the patients [24][25][26][27][28]. This "pre-evacuation time" decreases if people are aware of what they are supposed to do in case of fire (if more fire drills are conducted in the ward, for instance), if the firefighting system and the fire alarm system are efficient and if they are working well.…”

Section: Simulation Resultsmentioning

confidence: 99%

Egress from a Hospital Ward During Fire Emergency

D’Orazio¹,

Grossi²,

Ursetta³

et al. 2020

IJSSE

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There are many issues in a hospital evacuation, related both to conditions of the patients and to building complexity. Moreover, as consequences of fire, there may be delays in surgeries and medical diagnosis, or interruption in treatment for both inpatient and outpatient. This work identifies and assesses problems that arise in the egress from the ward located at third floor of the Campus Bio-Medico University Hospital of Rome, using a simulation software. Moreover, we perform a comparison between simulation results and experimental results by means of a real fire drill. We have considered a maximum of 116 people in the ward to its maximum capacity. We have created three different fire scenarios: fire in the electrical room, in the kitchen room and in a patient room. The time needed to evacuate fully the ward was far behind the fire resistance time of the structures. More than that, there was an overcrowded area in the ward that acted as a bottleneck: the so-called "smoke proof filter"; this area is intended to separates the two near wards and, although built according to the Italian fire department regulation, it holds back people and beds.

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Section: Simulation Resultsmentioning

confidence: 99%

Egress from a Hospital Ward During Fire Emergency

D’Orazio¹,

Grossi²,

Ursetta³

et al. 2020

IJSSE

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“…Modelle zur Beschreibung von Fußgängerdynamik lassen sich auf ähnliche Weise klassifizieren wie Modelle für Straßenverkehr [5]. Man unterscheidet unter anderem zwischen makroskopischen und mikroskopischen Modellen.…”

Section: Modelle Für Fußgängerdynamikunclassified

“…Das Standardmodell in dieser Klasse ist das Bodenfeld‐Modell (Floor Field Model) [2,5]. Neben der Wunschbewegungsrichtung, die durch den Zielpunkt bestimmt ist, werden die Übergangswahrscheinlichkeiten auch durch die Bewegung der anderen Fußgänger bestimmt.…”

Section: Zellularautomatenunclassified

Menschen sicher leiten und evakuieren

Schadschneider

Seyfried

2021

Physik in unserer Zeit

Self Cite

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die Physik von Menschenströmen Menschen sicher leiten und evakuieren andreas sChadsChneider | armin seyFried Überfüllte Bahnhöfe und Züge, die Organisation von Großveranstaltungen oder die Evakuierung von Stadien oder Theatern: Wenn sich viele Menschen ansammeln, kann es zu Stau und Gedränge kommen. Dann ist die Stauforschung für den Fußgängerverkehr gefragt. Hier hat die Physik in den letzten zwanzig Jahren wichtige Beiträge geliefert. www.phiuz.de 5/2021 (52) Phys. unserer Zeit 249

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“…An alignment rule by itself is theoretically sufficient to generate collective motion (Leonard et al, 2012;Vicsek, Czirók, Ben-Jacob, Cohen, & Shochet, 1995), as is the combination of attraction and repulsion (Romanczuk, Couzin, & Schimansky-Geier, 2009). Among pedestrian models (Chraibi, Tordeux, Schadschneider, & Seyfried, 2018), the prominent Social Force model (Chen, Treiber, Kanagaraj, & Li, 2018;Helbing & Molnár, 1995;Hoogendoorn & Bovy, 2003) is predicated on attraction and repulsion forces and has convenient mathematical properties (Köster, Treml, & Gödel, 2013). The model successfully simulates key crowd scenarios (Boltes, Zhang, Tordeux, Schadschneider, & Seyfried, 2018;Chraibi et al, 2018) and can generate collective motion under certain conditions (Helbing, Farkas, & Vicsek, 2000;Helbing, Molnár, Farkas, & Bolay, 2001), but does not produce realistic human trajectories (Pelechano, Allbeck, & Badler, 2007) or generalize to novel situations without re-parameterization (Campanella, Hoogendoorn, & Daamen, 2009;Chen et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

The visual coupling between neighbors explains ‘flocking’ in human crowds

Dachner

Wirth

Richmond

et al. 2021

Preprint

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Patterns of collective motion or 'flocking' in birds, fish schools, and human crowds are believed to emerge from local interactions between individuals. Most models of collective motion attribute these interactions to hypothetical rules or forces, often inspired by physical systems, and described from an overhead view. We develop a visual model of human flocking from an embedded view, based on optical variables that actually govern pedestrian interactions. Specifically, people control their walking speed and direction by canceling the average optical expansion and angular velocity of their neighbors, weighted by visual occlusion. We test the model by simulating data from experiments with virtual crowds and real human 'swarms'. The visual model outperforms our previous overhead model and explains basic properties of physics-inspired models: 'repulsion' forces reduce to canceling optical expansion, 'attraction' forces to canceling optical contraction, and 'alignment' to canceling the combination of expansion/contraction and angular velocity. Critically, the neighborhood of interaction follows from Euclid's Law of perspective and the geometry of occlusion. We conclude that the local interactions underlying human flocking are a natural consequence of the laws of optics. Similar principles may apply to collective motion in other species.

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Modelling of Pedestrian and Evacuation Dynamics

Cited by 31 publications

References 85 publications

Egress from a Hospital Ward During Fire Emergency

Egress from a Hospital Ward During Fire Emergency

Menschen sicher leiten und evakuieren

The visual coupling between neighbors explains ‘flocking’ in human crowds

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