Simulations of Evacuation by an Extended Floor Field CA Model

Nishinari, Katsuhiro; Kirchner, Ansgar; Namazi, Alireza; Schadschneider, Andreas

doi:10.1007/3-540-28091-x_40

Cited by 32 publications

(33 citation statements)

References 8 publications

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“…In a cellular automata model, pedestrians must decide at each time step to move to one of four cells (in a Neumann neighborhood) or eight cells (in a Moore neighborhood) [7]. In Fig.…”

Section: Previous Modelmentioning

confidence: 99%

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Implementation of Simulation Environment for Exhaustive Analysis of Huge-Scale Pedestrian Flow

Yamashita

Okada

Noda

2013

SICE Journal of Control, Measurement, and System Integration

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: This paper describes implementation of a pedestrian simulation environment to carry out an exhaustive analysis of huge-scale pedestrian flow. Our environment consists of the CrowdWalk pedestrian simulator and the PRACTIS simulation controller. CrowdWalk has three pedestrian movement models that are based on a one-dimensional space model. PRACTIS carries out an exhaustive and efficient analysis in a cluster environment to support effective decisionmaking, enabling pedestrians to be guided according to various criteria. The authors apply CrowdWalk and PRACTIS in a firework festival to verify their guidance planning, and examine some case studies.

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“…In a cellular automata model, pedestrians must decide at each time step to move to one of four cells (in a Neumann neighborhood) or eight cells (in a Moore neighborhood) [7]. In Fig.…”

Section: Previous Modelmentioning

confidence: 99%

“…Further, the expected velocity EV l (t) of link l at time t is determined by the speed functions (6) and (7), and the expected density ED l (t) of link l. The expected density ED l (t) is denoted as ρ in (6) and (7). Each pedestrian moves based on the expected velocity EV l (t) of link l.…”

Section: Expected Density Modelmentioning

confidence: 99%

Implementation of Simulation Environment for Exhaustive Analysis of Huge-Scale Pedestrian Flow

Yamashita

Okada

Noda

2013

SICE Journal of Control, Measurement, and System Integration

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“…We chose Kirchner model as our base model. His original model (Kircher et al 2002) and some variations (Nishinari et al 2005) have demonstrated the ability to capture different pedestrian behaviors discussed in the previous section while being computationally efficient. First, we will describe the basic features of the floor field model and, then, describe how we improved the model.…”

Section: Floor Field Modelmentioning

confidence: 99%

A 3d Indoor Pedestrian Simulator Using a Spatial DBMS

Kim

Chulmin

2010

Proceedings of the 2nd International Conference on Agents and Artificial Intelligence

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Most crowd simulation models for pedestrian dynamics are based on analytical approach using experimental settings without being related to real world data. In order for the models to be adapted to real world applications such as fire evacuation or warning systems, some technical aspects first must be resolved. First, the base data should represent the 3D indoor model which contains semantic information of each space. Second, in order to communicate with the indoor localization sensors to capture the real time pedestrians and to store the simulation results for later uses, the data should be in a DBMS instead of files. The purpose of this paper is two folds. One is to suggest a DBMS-based 3D modeling approach for pedestrian simulations. The other is to improve the existing floor field based pedestrian model by modifying the dynamic field. We illustrated the data construction processes and simulations using the proposed DBMS approach and the enhanced pedestrian model.

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“…In cellular atuomata (CA) models, an agent is assigned a grid of the cell. Shapes of the cell are usually square [5][6][7] or hexagonal [8,9]. To make the space in CA more flexible, multigrid models [10,11] are developed by assigning pedestrians in small 3 × 3 grids.…”

Section: Introductionmentioning

confidence: 99%

Simulation of pedestrian single-lane movement by a biped model

2018

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In most existing pedestrian dynamic models, agents are modeled as sliding or jumping objects. As a kind of bipedal creature, however, this assumption makes it difficult to include some important human walking characteristics in the models, such as the periodicity of stepping, the adjustment of step frequency and step length, and the change of personal space within the same step cycle. To take these characteristics into consideration, a "Biped Model" is developed to simulate pedestrian locomotion by physical step rather than by time step. The model consists of two components: the stepping simulator and the adjustment of velocity for each step. Simulation results show that the velocity-density relations are consistent with the empirical data. Stable stop-and-go waves are simulated with a critical density. Furthermore, with the considering of biped movement, the lock-step phenomenon is reproduced. The model provides new possibilities to study crowd behavior while considering personal bipedal mechanics.

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Simulations of Evacuation by an Extended Floor Field CA Model

Cited by 32 publications

References 8 publications

Implementation of Simulation Environment for Exhaustive Analysis of Huge-Scale Pedestrian Flow

Implementation of Simulation Environment for Exhaustive Analysis of Huge-Scale Pedestrian Flow

A 3d Indoor Pedestrian Simulator Using a Spatial DBMS

Simulation of pedestrian single-lane movement by a biped model

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