Discrete element crowd model for pedestrian evacuation through an exit

Lin, Ping; Ma, Jian; Lo, Siuming

doi:10.1088/1674-1056/25/3/034501

Cited by 40 publications

(28 citation statements)

References 44 publications

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“…However, when the obstacle size and location of the column were varied, the outflow was less than the column free situation in some cases. These differing decisions about the performance of the architectural adjustments in an escape area have been noted by other researchers as well [4,5,17,27,[29][30][31][32][33][34][35][36][37]. In another study, Parisi and Patterson [40] adopted two simulation models to examine the effect of the length of the bottleneck after the exit and the distance of the exit to the lateral wall, on evacuation time.…”

Section: Simulations Of Crowd Egress At Bottlenecksmentioning

confidence: 89%

Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

Shi

Shiwakoti

et al. 2019

Physica A: Statistical Mechanics and its Applications

112

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Recent advances in bottleneck studies have highlighted that different architectural adjustments at the exit may reduce the probability of clogging at the exit thereby enhancing the outflow of the individuals. However, those studies are mostly limited to the controlled experiments with non-human organisms or predictions from simulation models. Complementary data with human subjects to test the model's prediction is limited in literature. This study aims to examine the effect of different geometrical layouts at the exit towards the pedestrian flow via controlled laboratory experiments with human participants. The experimental setups involve pedestrian flow through 14 different geometrical configurations that include different exit locations and obstacles near exit under normal and slow running conditions. It was found that corner exit performed better than middle exit under same obstacle condition. Further, it was observed that the effectiveness of obstacle is sensitive to its size and distance from the exit. Thus, with careful architectural adjustment within a standard escape area, a substantial increase in outflow under normal and slow running conditions could be achieved. However, it was also observed that placing the obstacle too close to the exit can reduce outflow under both normal and slow running conditions. Moreover, we could not observe "faster-is-slower" effect under slow running condition and instead noticed "faster-is-faster" effect. In addition, the power law fitted headway distribution demonstrated that any architectural configurations that enhanced the outflow have higher exponent value compared to the other configuration that negates the outflow. The findings from this paper demonstrate that there is a scope to adjust the architectural elements to optimize the maximum outflow at the egress point. Further, the output from the experiments can be used to develop and verify mathematical models intended to simulate crowd evacuation.From the data in Table 3, we could conclude that for normal walking situation, comparing with standard design ( s J  =2.67 Ped/s/m, S.D =  0.55 Ped/s/m), the most efficient setup is #11 (Corner exit,  =60 cm, D =100 cm) with 19.4% R. E. ( s J  =3.18 Ped/s/m, S.D =  0.34 Ped/s/m), and the least efficient geometry is #2 (Middle exit,  =60 cm, D =60 cm) with -10.6% R. E. ( s J  =2.38 Ped/s/m, S.D =  0.12 Ped/s/m). For slow running condition that is more representative of emergency evacuation condition, comparing with standard design ( s J  =3.37 Ped/s/m, S.D =  0.22 Ped/s/m), the most efficient setup was also #11 with 32.7% R. E. ( s J  =4.47 Ped/s/m, S.D =  0.19 Ped/s/m), and the least one turned into #5 (Middle exit,  =100 cm, D =60 cm) with -5.6% R. E. ( s J  =3.18 Ped/s/m, S.D =  0.08 Ped/s/m).

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Section: Simulations Of Crowd Egress At Bottlenecksmentioning

confidence: 89%

Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

Shi

Shiwakoti

et al. 2019

Physica A: Statistical Mechanics and its Applications

112

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“…It is remarkable that the system does not reach a freezing state such as the one reported in Refs. [26,41]. Recall that our simulations do not include any respect factor (see Ref.…”

Section: Fundamental Diagram In the Original Modelmentioning

confidence: 99%

A re-examination of the role of friction in the original Social Force Model

et al. 2020

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The fundamental diagram of pedestrian dynamics gives the relation between the density and the flow within a specific enclosure. It is characterized by two distinctive behaviors: the free-flow regime (for low densities) and the congested regime (for high densities). In the former, the flow is an increasing function of the density, while in the latter, the flow remains on hold or decreases. In this work, we perform numerical simulations of the pilgrimage at the entrance of the Jamaraat bridge (pedestrians walking along a straight corridor) and compare flow-density measurements with empirical measurements made by Helbing et al [1]. We show that under high density conditions, the basic Social Force Model (SFM) does not completely handle the fundamental diagram reported in empirical measurements. We use analytical techniques and numerical simulations to prove that with an appropriate modification of the friction coefficient (but sustaining the SFM) it is possible to attain behaviors which are in qualitative agreement with the empirical data. Other authors have already proposed a modification of the relaxation time in order to address this problem. In this work, we unveil the fact that our approach is analogous to theirs since both affect the same term of the reduced-in-units equation of motion. We show how the friction modification affects the pedestrian clustering structures throughout the transition from the free-flow regime to the congested regime. We also show that the speed profile, normalized by width and maximum velocity yields a universal behavior regardless of the corridor dimensions.

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“…It is triggered whenever a situation of tension worsens, slips or escapes from human control. Panic is defined as an intense fear triggered by the occurrence of a real or imaginary danger felt simultaneously by all individuals in a group, a crowd or a population, characterized by the regression of mentalities to an archaic and gregarious level, leading to primitive reactions of hopeless jumps, indiscriminate agitation of violence or collective suicide [5]. Nevertheless, discrepancies exist between the definition of triggering and propagation processes.…”

Section: Crowd Panicmentioning

confidence: 99%

“…Works belonging to this category incorporate the concept of social forces, where the model allows a mixture of sociopsychological and physical forces influencing the behaviors within a crowd [4]. Several models based on this approach have been developed so far, the latter proposes an adaptation and hybridization of the model of social forces with other models [5]. These models can reproduce certain phenomena observed in real crowds during panic movements, such as crowd oscillation in a narrow passage, arch formation in front of an exit, lane formation, etc.…”

Section: Introductionmentioning

confidence: 99%

A Social Bonds Integration Approach for Crowd Panic Simulation

Bouderbal¹,

Amamra

2019

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

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Crowd panic has incurred massive injuries and deaths throughout history; thus understanding it is particularly important in order to save human lives. Recently, numerous simulation methods have been contributed in order to provide insight into the design of evacuation planning strategies. In this paper, we integrate a social structure to the crowd mobility model for the purpose of investigating the influence of social bonds on collective behavior during panic. A macroscopic crowd panic model based on social science theories was integrated as an internal module to the microscopic mobility model. The resulting framework is tunable and permits the implementation of several panic scenarios. It is also designed to run in different situations for a better comprehension of panic-related phenomena. The results demonstrate the smoothness of our crowd flow model and the realism of evacuation during panic.

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Discrete element crowd model for pedestrian evacuation through an exit

Cited by 40 publications

References 44 publications

Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

A re-examination of the role of friction in the original Social Force Model

A Social Bonds Integration Approach for Crowd Panic Simulation

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