Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions

The micro-pedestrian simulation model represented by the cellular automata model is an important simulation model. Improvements in various aspects enable a better description of the various behaviors of pedestrians, such as pedestrian avoidance behavior, companion behavior, as well as transcendence behavior, waiting behavior and detour behavior. This paper takes the pedestrian detour behavior in the circle antipode experiment as the main entry point. The subdivision cellular automaton model is integrated into the prediction field to model and simulate the detour behavior. At the same time, it explores the degree of subdivision of the cell. Pedestrian heterogeneity and the influence of predicted field potential energy on the simulated pedestrian trajectory. Finally, based on the temporal and spatial indicators of pedestrian trajectory characteristics, the KS test and DTW method are used to evaluate the similarity of the trajectory distribution characteristics and time series characteristics with experimental samples, and evaluate and compare models with or without heterogeneity. The results show that the trajectory characteristics of heterogeneous pedestrians are closer to the experiment than homogeneous pedestrians.

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Effect of group behavior on pedestrian choice for vertical walking facilities

International Journal of Modern Physics B ◽

10.1142/s0217979220500563 ◽

2020 ◽

Vol 34 (07) ◽

pp. 2050056

Author(s):

Yongxing Li ◽

Wenjing Wu ◽

Xin Guo ◽

Yu Lin ◽

Shiguang Wang

Keyword(s):

Support Vector Machine ◽

Cellular Automata ◽

Simulation Model ◽

Choice Model ◽

Group Behavior ◽

Support Vector ◽

Floor Field ◽

The Mean ◽

Simulation Results ◽

Pedestrian Simulation

Analyzing the characteristics of group behavior, leader-follower model which adopts dynamic group floor field to represent the attraction in a group is used to model pedestrian group behavior. Pedestrian choice model of vertical walking facilities based on support vector machine (SVM) with the effect of group behavior is established. Fusing pedestrian choice model of vertical walking facilities and leader-follower model into a cellular automata (CA)-based pedestrian simulation model, we simulate the pedestrian choice process for vertical walking facilities with the effect of group behavior. The simulation results indicate that with the effect of group behavior, the choice results of some pedestrians are changed, and the efficiency of pedestrians passing is reduced. To some extent, the efficiency of pedestrians passing is improved with the mean distribution of luggage in each group.

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Pedestrian choice behavior analysis and simulation of ticket gate machine in rail transit station

International Journal of Modern Physics C ◽

10.1142/s012918311950027x ◽

2019 ◽

Vol 30 (04) ◽

pp. 1950027 ◽

Cited By ~ 1

Author(s):

Yongxing Li ◽

David Z.W. Wang ◽

Yanyan Chen ◽

Chengcheng Song ◽

Hongfei Jia ◽

...

Keyword(s):

Simulation Model ◽

Minimum Distance ◽

Choice Behavior ◽

Simulation Software ◽

Rail Transit ◽

Matlab Simulation ◽

Behavior Simulation ◽

Minimum Number ◽

Simulation Results ◽

Pedestrian Simulation

Considering pedestrian preferences for the minimum distance, the minimum number of queuing pedestrians and the shortest estimated time, three pedestrian choice strategies of ticket gate machine are proposed. Pedestrian choice strategies of ticket gate machine are added into pedestrian simulation model which is based on cellular automata, and pedestrian choice behavior simulation model of ticket gate machine is obtained. On the platform of MATLAB simulation software, pedestrian choice behavior is simulated. Simulation results indicate that choice strategies of ticket gate machine proposed in this paper describe pedestrian choice behavior well, and it needs to consider the ratio of bidirectional pedestrian generation rate in the process of setting ticket gate machines in the bidirectional passage.

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A microscopic pedestrian-simulation model and its application to intersecting flows

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2009.10.008 ◽

2010 ◽

Vol 389 (3) ◽

pp. 515-526 ◽

Cited By ~ 51

Author(s):

Ren-Yong Guo ◽

S.C. Wong ◽

Hai-Jun Huang ◽

Peng Zhang ◽

William H.K. Lam

Keyword(s):

Simulation Model ◽

Pedestrian Simulation

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Validation of an Agent-based Microscopic Pedestrian Simulation Model at the Pedestrian Walkway of Brooklyn Bridge

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118774182 ◽

2018 ◽

Vol 2672 (35) ◽

pp. 33-45 ◽

Cited By ~ 2

Author(s):

Mohamed Hussein ◽

Tarek Sayed

Keyword(s):

Simulation Model ◽

High Accuracy ◽

Video Data ◽

Model Parameters ◽

Actual Behavior ◽

Agent Based ◽

Optimum Model ◽

Using Data ◽

Brooklyn Bridge ◽

Pedestrian Simulation

The objective of this study is to validate a recently developed agent-based pedestrian simulation model, using data collected at the pedestrian walkway of Brooklyn Bridge. Video data were collected at the walkway and the trajectories of 294 pedestrians were extracted using computer vision. A genetic algorithm was applied to identify the optimum model parameters that minimize the error between the simulated and the actual trajectories of the calibration dataset. The simulation model was then applied to reproduce the trajectories of 214 pedestrians, considered for validation. The validation results showed that the model was capable of producing pedestrian trajectories with high accuracy, as the average location error between actual and simulated trajectories was for 0.32 m, while the average speed error was 0.06 m/s. Macroscopic results of the model were assessed by comparing the density–speed relationship in both actual data and the simulation. Finally, the accuracy of the model in reproducing the actual behavior of pedestrians during different interactions was evaluated. Results showed that the model was capable of handling these interactions with high accuracy, ranged between 79% and 100%.

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