On the Modelling Crowd Dynamics From Scaling to Hyperbolic Macroscopic Models

Bellomo, Nicola; Dogbe, Christian

doi:10.1142/s0218202508003054

Cited by 170 publications

(110 citation statements)

References 28 publications

(20 reference statements)

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“…Optimization models gravitate to graphs to represent the paths available to pedestrian evacuees [59,60]. A graph is defined by a set of nodes representing rooms or decision points, and edges representing doors, corridors, or other paths connecting the spaces represented by nodes [61].…”

Section: Evacuation Optimizationmentioning

confidence: 99%

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Zhao

Winter

Tomko

2017

IJGI

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Abstract:The lonelier evacuees find themselves, the riskier become their wayfinding decisions. This research supports single evacuees in a dynamically changing environment with risk-aware guidance. It deploys the concept of decentralized evacuation, where evacuees are guided by smartphones acquiring environmental knowledge and risk information via exploration and knowledge sharing by peer-to-peer communication. Peer-to-peer communication, however, relies on the chance that people come into communication range with each other. This chance can be low. To bridge between people being not at the same time at the same places, this paper suggests information depositories at strategic locations to improve information sharing. Information depositories collect the knowledge acquired by the smartphones of evacuees passing by, maintain this information, and convey it to other passing-by evacuees. Multi-agent simulation implementing these depositories in an indoor environment shows that integrating depositories improves evacuation performance: It enhances the risk awareness and consequently increases the chance that people survive and reduces their evacuation time. For evacuating dynamic events, deploying depositories at staircases has been shown more effective than deploying them in corridors.

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Section: Evacuation Optimizationmentioning

confidence: 99%

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Zhao

Winter

Tomko

2017

IJGI

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“…As the escalation of theoretical and experimental studies, some researchers [10][11][12] discovered that first-order partial differential equations are always in an equilibrium state. In addition, the function of density and velocity cannot reflect the instantaneous changes in a crowd, which means that the first-order model is not capable of explaining some complex phenomena, such as stop-and-go waves and bottleneck clogging [13].…”

Section: Introductionmentioning

confidence: 99%

Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis

Zhou

Feng

et al. 2018

Sustainability

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Abstract:In recent years, accidents always happen in confined space such as metro stations because of congestion. Various researchers investigated the patterns of dense crowd behaviors in different scenarios via simulations or experiments and proposed methods for avoiding accidents. In this study, a classic continuum macroscopic model was applied to simulate the crowded pedestrian flow in typical scenarios such as at bottlenecks or with an obstacle. The Lax-Wendroff finite difference scheme and artificial viscosity filtering method were used to discretize the model to identify high-density risk areas. Furthermore, we introduced a contact crowding force test of the interactions among pedestrians at bottlenecks. Results revealed that in the most dangerous area, the individual on the corner position bears the maximum pressure in such scenarios is 90.2 N, and there is an approximate exponential relationship between crowding force and density indicated by our data. The results and findings presented in this paper can facilitate more reasonable and precise simulation models by utilizing crowding force and crowd density and ensure the safety of pedestrians in high-density scenarios.

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“…Traffic and pedestrian flow equations on the mesoscopic or kinetic level can be found for example in [35,33,29,20,14]. Macroscopic traffic and pedestrian flow equations involving equations for density and mean velocity of the flow are derived in [40,3,13,2,17,16,19] and [20,6]. The classical macroscopic traffic flow model based on scalar continuity equations is described in [37].…”

Section: Introductionmentioning

confidence: 99%

“…In [27,28,15,10] pedestrian traffic modeling with scalar conservation laws based on the solution of the eikonal equation have been presented and investigated, see again [5] for further developments and historical comments. Additionally, in [5,6], a variety of other macroscopic models are discussed.…”

Section: Introductionmentioning

confidence: 99%

Coupling Traffic Flow Networks to Pedestrian Motion

Borsche

Klar

Kühn

et al. 2013

Math. Models Methods Appl. Sci.

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In the present paper scalar macroscopic models for traffic and pedestrian flows are coupled and the resulting system is investigated numerically. For the traffic flow the classical Lighthill-Whitham model on a network of roads and for the pedestrian flow the Hughes model are used. These models are coupled via terms in the fundamental diagrams modeling an influence of the traffic and pedestrian flow on the maximal velocities of the corresponding models. Several physical situations, where pedestrians and cars interact, are investigated.

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On the Modelling Crowd Dynamics From Scaling to Hyperbolic Macroscopic Models

Cited by 170 publications

References 28 publications

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis

Coupling Traffic Flow Networks to Pedestrian Motion

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