scholarly journals Simulating Crowd Evacuation in a Social Force Model with Iterative Extended State Observer

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Juan Wei ◽  
Wenjie Fan ◽  
Zhongyu Li ◽  
Yangyong Guo ◽  
Yuanyuan Fang ◽  
...  
Keyword(s):  
State Observer ◽  
Extended State Observer ◽  
Force Model ◽  
Social Force ◽  
Extended State ◽  
Social Force Model ◽  
External Interference ◽  
The Social ◽  
Crowd Evacuation ◽  
Improved Model

Due to the interaction and external interference, the crowds will constantly and dynamically adjust their evacuation path in the evacuation process to achieve the purpose of rapid evacuation. The information from previous process can be used to modify the current evacuation control information to achieve a better evacuation effect, and iterative learning control can achieve an effective prediction of the expected path within a limited running time. In order to depict this process, the social force model is improved based on an iterative extended state observer so that the crowds can move along the optimal evacuation path. First, the objective function of the optimal evacuation path is established in the improved model, and an iterative extended state observer is designed to get the estimated value. Second, the above model is verified through simulation experiments. The results show that, as the number of iterations increases, the evacuation time shows a trend of first decreasing and then increasing.

A social force evacuation model considering the effect of emergency signs

SIMULATION ◽  
2017 ◽  
Vol 94 (8) ◽  
pp. 723-737 ◽  
Author(s):  
Zhilu Yuan ◽  
Hongfei Jia ◽  
Linfeng Zhang ◽  
Lei Bian
Keyword(s):  
Visual Field ◽  
Movement Direction ◽  
Force Model ◽  
Herd Behavior ◽  
Security Risk ◽  
Social Force ◽  
Social Force Model ◽  
Evacuation Time ◽  
The Social ◽  
Improved Model

In this paper, we investigate the effect of emergency signs on evacuation dynamics under smoke conditions. We assume that in a smoky hall the visual field of pedestrians is limited to a certain range, and they do not know the exact location of the exit. In this kind of evacuation process, we analyze the influence of emergency signs on movement direction and speed, and the herd behavior of pedestrians. In the analysis, we divide the emergency signs into two types: the wall signs (WS) and the ground signs (GS). Then, we analyze the variation of pedestrian behavior when they encounter the WS, the GS, and the exit in the evacuation process. Combined with the analysis results, we build our improved model based on the social force model. In the simulation, we study the evacuation process in the case of WS and GS. According to the result of the simulation, we consider that the effect of the emergency signs on herd behavior and the desired speed is an important factor to improve evacuation efficiency. We find that, from the perspective of evacuation time, the evacuation in the case of WS is more efficient, but from the perspective of the interaction between pedestrians, the evacuation in the case of GS presents less security risk. Finally, we explore how to design a mixed layout scheme of WS and GS.

Research of Crowd Evacuation Simulation Based on the Machine Learning

2017 ◽  
Vol 14 (1) ◽  
pp. 815-820 ◽  
Author(s):  
Baoxi Liu ◽  
Yanbin Han ◽  
Hao Zhang ◽  
Xin Qin
Keyword(s):  
Machine Learning ◽  
Learning Ability ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Evacuation Simulation ◽  
The Social ◽  
Close Relationship ◽  
Improved Model ◽  
Evacuation Route

A majority of existing evacuation models overlooked the pedestrian’s social relationship and their learning ability. In this paper, we made two improvements base on the social force model. First, a new force called group relationship force was added to the social force model. Pedestrians who have close relationship could gather into a group and walk together. Second, the machine learning was introduced to the improved social force model to represent pedestrian’s learning and cognitive ability. In the improved model, pedestrians could store the evacuation route to the knowledge base, and next time they can choose a best path to evacuate according to their knowledge. Simulation results show that the new method could better to avoid obstacles and save evacuation time. Furthermore, this improved model is applied to the simulation system of Ji’nan Springs Plaza for predictive evacuation experiments.

miSFM: On combination of Mutual Information and Social Force Model towards simulating crowd evacuation

2015 ◽  
Vol 168 ◽  
pp. 529-537 ◽  
Author(s):  
Mingliang Xu ◽  
Yunpeng Wu ◽  
Pei Lv ◽  
Hao Jiang ◽  
Mingxuan Luo ◽  
...  
Keyword(s):  
Mutual Information ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Crowd Evacuation

scholarly journals SPECIFICATION OF THE SOCIAL FORCE PEDESTRIAN MODEL BY EVOLUTIONARY ADJUSTMENT TO VIDEO TRACKING DATA

2007 ◽  
Vol 10 (supp02) ◽  
pp. 271-288 ◽  
Author(s):  
ANDERS JOHANSSON ◽  
DIRK HELBING ◽  
PRADYUMN K. SHUKLA
Keyword(s):  
Large Scale ◽  
Optimal Parameter ◽  
Video Tracking ◽  
Urban Environments ◽  
Force Model ◽  
Tracking Data ◽  
Social Force ◽  
Social Force Model ◽  
Video Recordings ◽  
The Social

Based on suitable video recordings of interactive pedestrian motion and improved tracking software, we apply an evolutionary optimization algorithm to determine optimal parameter specifications for the social force model. The calibrated model is then used for large-scale pedestrian simulations of evacuation scenarios, pilgrimage, and urban environments.

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