Abstract
Lattice gas model is a kind of mature and convenient pedestrian simulation model. The original lattice gas model adopts discontinuous step length and finite moving directions to simulate crowd motion, which will lead to some unreasonable movements; besides, the transition probability used in this model is often manually designed and lacks the verification of realistic pedestrian trajectories. Based on an open pedestrian trajectory dataset, we first derived the relationship between local density and the distribution of pedestrian movements’ length and then proposed an extended lattice gas model considering the statistical characteristics of pedestrian movements, which extends the concept of transition probability in the original lattice gas model to distribution of pedestrian movements’ length in two perpendicular directions. The proposed model is applied to a scenario which is the same as the experiments of the open dataset, and the numerical results demonstrate that the proposed model can reproduce the fundamental diagrams and the transition probability of the experimental dataset well. This study is helpful to understand the statistical characteristics of pedestrian movements and can improve the applicability and accuracy of the lattice gas model.
Highlights
Lattice gas model is a kind of mature and convenient pedestrian simulation model. e original lattice gas model adopts discontinuous step length and finite moving directions to simulate crowd motion, which will lead to some unreasonable movements; besides, the transition probability used in this model is often manually designed and lacks the verification of realistic pedestrian trajectories
Based on an open pedestrian trajectory dataset, we first derived the relationship between local density and the distribution of pedestrian movements’ length and proposed an extended lattice gas model considering the statistical characteristics of pedestrian movements, which extends the concept of transition probability in the original lattice gas model to distribution of pedestrian movements’ length in two perpendicular directions. e proposed model is applied to a scenario which is the same as the experiments of the open dataset, and the numerical results demonstrate that the proposed model can reproduce the fundamental diagrams and the transition probability of the experimental dataset well. is study is helpful to understand the statistical characteristics of pedestrian movements and can improve the applicability and accuracy of the lattice gas model
An open dataset that contains a series of unidirectional pedestrian flow experiments is used here for supporting our analysis [40]. e fitting result shows that there are some statistical rules between pedestrian movements and local density, and we proposed an extended lattice gas model (LGM) for simulating pedestrian movements using statistical methods. e model incorporates these statistical rules, and the transition probability in LGM is extended from a giving drift strength D to probability density functions (PDF) of two-directional movements (Figure 4). e fundamental diagrams show that the proposed model can fit the numerical result of the original data well, and the transition probability figures imply that the model can reproduce the continuous step, unlimited heading direction, and reasonable transition probability
Summary
Where S method wisothueldsucorrvoeur nanddin→gr ajr(eta) who is inside the surrounding that local density calculation aisrethaeopfo→srit.ioInn of pedestrian j this study, we assumed that a pedestrian will consider all others within his/. Her visual field, so S is denoted by the front visual area. At a given local density, the length of pedestrian movements in each direction has some randomness, but from the statistical view, they may follow a certain distribution.
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