Impact of Passenger Group Dynamics on an Airport Evacuation Process Using an Agent-Based Model

Cheng, Lin; Reddy, Vikas; Fookes, Clinton; Yarlagadda, Prasad K.D.V.

doi:10.1109/csci.2014.111

Cited by 12 publications

(20 citation statements)

References 11 publications

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“…19 The same group may contribute to multiple slots. 20 Each data point is shown for ρ = ρ i , i.e., at the center of the density slot. intervals.…”

Section: Appendix B: Averages and Confidence Intervalsmentioning

confidence: 99%

“…19 Finally, we average over all groups to obtain the data shown in the figures. 20 By considering different groups as statistically independent, we define standard errors as σ i / √ n i , where σ i is the variance (of the average over groups) of the observable in the slot i, and n i is the number of groups observed in the slot. Only density slots that have data points from at least 100 groups were used to compute averages and confidence 17 This choice gives us reasonable density values provided that the usage pattern of the environment does not change in a time scale short with respect to T .…”

Section: Appendix B: Averages and Confidence Intervalsmentioning

confidence: 99%

“…In the last few years, a few models describing group dynamics have been introduced [11,[17][18][19] (see also [20] for a recent review of the field), but they often rely on a quite simplistic description of groups, both in their free-walking (or low-density, ρ → 0) behavior and in their reaction to growing density conditions. For example, a seminal work in the field is [11], which introduces a model describing pedestrian groups as abreast when freely walking, and bending to V and U formations in higher density conditions.…”

Section: Introductionmentioning

confidence: 99%

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Spatial-size scaling of pedestrian groups under growing density conditions

Zanlungo¹,

Brščić²,

Kanda³

2015

Phys. Rev. E

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We study the dependence on crowd density of the spatial size, configuration, and velocity of pedestrian social groups. We find that, in the investigated density range, the extension of pedestrian groups in the direction orthogonal to that of motion decreases linearly with the pedestrian density around them, both for two- and three-person groups. Furthermore, we observe that at all densities, three-person groups walk slower than two-person groups, and the latter are slower than individual pedestrians, the differences in velocities being weakly affected by density. Finally, we observe that three-person groups walk in a V-shaped formation regardless of density, with a distance between the pedestrians in the front and back again almost independent of density, although the configuration appears to be less stable at higher densities. These findings may facilitate the development of more realistic crowd dynamics models and simulators.

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“…19 The same group may contribute to multiple slots. 20 Each data point is shown for ρ = ρ i , i.e., at the center of the density slot. intervals.…”

Section: Appendix B: Averages and Confidence Intervalsmentioning

confidence: 99%

Section: Appendix B: Averages and Confidence Intervalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatial-size scaling of pedestrian groups under growing density conditions

Zanlungo¹,

Brščić²,

Kanda³

2015

Phys. Rev. E

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“…Noteworthy work in the aviation sector includes the work of Weiss et al [10], who developed an agent-based model for airport defense, and the work of Cheng et al [35] who created an agent-based model to evaluate the effect of group dynamics on passenger flow during an evacuation in an airport terminal. Moreover, Janssen et al [9] introduced a novel agent-based methodology combined with Monte Carlo simulations for security risk assessment.…”

Section: Agent-based Modelingmentioning

confidence: 99%

An Agent-Based Empirical Game Theory Approach for Airport Security Patrols

2020

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Airports are attractive targets for terrorists, as they are designed to accommodate and process large amounts of people, resulting in a high concentration of potential victims. A popular method to mitigate the risk of terrorist attacks is through security patrols, but resources are often limited. Game theory is commonly used as a methodology to find optimal patrol routes for security agents such that security risks are minimized. However, game-theoretic models suffer from payoff uncertainty and often rely solely on expert assessment to estimate game payoffs. Experts cannot incorporate all aspects of a terrorist attack in their assessment. For instance, attacker behavior, which contributes to the game payoff rewards, is hard to estimate precisely. To address this shortcoming, we proposed a novel empirical game theory approach in which payoffs are estimated using agent-based modeling. Using this approach, we simulated different attacker and defender strategies in an agent-based model to estimate game-theoretic payoffs, while a security game was used to find optimal security patrols. We performed a case study at a regional airport, and show that the optimal security patrol is non-deterministic and gives special emphasis to high-impact areas, such as the security checkpoint. The found security patrol routes are an improvement over previously found security strategies of the same case study.

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“…The influence of group dynamics on the behaviour of pedestrians and the differences between the behaviour of pedestrians walking in groups and single pedestrians have been presented in several recent works. We refer to [11,41,44,47,36]. In these works experimental studies as well as numerical experiments are presented In this work, we closely follow a procedure for interacting particle systems used, for example, in the description of coherent motion of animal groups such as schools of fish, flocks of birds or swarms of insects, see Ref.…”

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confidence: 99%

Particle methods for multi-group pedestrian flow

Mahato

Klar

Tiwari

2018

Applied Mathematical Modelling

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Abstract. We consider a multi-group microscopic model for pedestrian flow describing the behaviour of large groups. It is based on an interacting particle system coupled to an eikonal equation. Hydrodynamic multi-group models are derived from the underlying particle system as well as scalar multi-group models. The eikonal equation is used to compute optimal paths for the pedestrians. Particle methods are used to solve the equations on all levels of the hierarchy. Numerical test cases are investigated and the models and, in particular, the resulting evacuation times are compared for a wide range of different parameters.

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Impact of Passenger Group Dynamics on an Airport Evacuation Process Using an Agent-Based Model

Cited by 12 publications

References 11 publications

Spatial-size scaling of pedestrian groups under growing density conditions

Spatial-size scaling of pedestrian groups under growing density conditions

An Agent-Based Empirical Game Theory Approach for Airport Security Patrols

Particle methods for multi-group pedestrian flow

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