Evacuation Model Considering the Restricted View of the Sign

doi:10.16182/j.issn1004731x.joss.21-0648

Abstract

Abstract:

In order to study the influence of restricted vision on the process of pedestrian evacuation, a cellular automata model of pedestrian evacuation under restricted vision is established. In the model, the evacuation space is divided into three different areas according to the field of view radius, pedestrians have different ways of moving in different areas. Different income parameters are defined to calculate the pedestrian movement income matrix and determine the target position of the pedestrian in the next time step. An evacuation scene is established to simulate the initial density of different pedestrians, the change of the field of view and the indicator signs in different areas, and the influence of these factors on the evacuation process of pedestrians are analyzed. The simulation results show that the greater the initial density of pedestrians, the longer the evacuation time will be. The larger the field of view radius will help pedestrians evacuate. When the field of view radius increases to a certain value, the effect of pedestrian evacuation is not obvious. There are signs in the room, the evacuation time for pedestrians should be significantly shorter than that without signs, and the evacuation efficiency of pedestrians when there are signs in the blind movement area is higher than that in the visible area of the wall.

Key words: cellular automata, restricted field of view, income parameter, indicator, pedestrian evacuation

CLC Number:

TP391.9

Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang. Evacuation Model Considering the Restricted View of the Sign[J]. Journal of System Simulation, 2022, 34(11): 2416-2424.

Figures/Tables 22

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Fig. 11

Fig. 12

Fig. 13

Fig. 14

Fig. 15

Fig. 16

Fig. 17

Fig. 18

Fig. 19

Fig. 20

Fig. 21

Fig. 22

References 13

[1]	钟少波, 余致辰, 杨永胜, 等. 基于社会力模型的机场人员疏散建模研究[J]. 系统仿真学报, 2018, 30(10): 3648-3656.
	Zhong Shaobo, Yu Zhichen, Yang Yongsheng, et al. Study on Evacuation Modeling of Airport Based on Social Force Model[J]. Journal of System Simulation, 2018, 30(10): 3648-3656.
[2]	Helbing D, Buznal L, Johansson A, et al. Self-organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions[J]. Transportation Science (S0041-1655), 2005, 39(1): 1-24.
[3]	Kirchner A, Schadschneider A. Simulation of Evacuation Processes Using a Bionics-inspired Cellular Automaton Model for Pedestrian Dynamics[J]. Physica A (S0378-4371), 2002, 312(1/2): 260-276.
[4]	李阳, 陈建忠, 张倩, 等. 考虑环境熟悉度的行人疏散模型研究[J]. 中国安全科学学报, 2016, 26(4): 168-174.
	Li Yang, Chen Jianzhong, Zhang Qian, et al. Research on Pedestrian Evacuation Model Considering Environmental Familiarity[J]. China Safety Science Journal, 2016, 26(4): 168-174.
[5]	宋英华, 张宇, 霍非舟, 等. 考虑避让行为的人员疏散元胞自动机模型研究[J]. 系统仿真学报, 2020, 32(6): 975-981.
	Song Yinghua, Zhang Yu, Huo Feizhou, et al. Study on Evacuation Cellular Automaton Model Considering Avoidance Behavior[J]. Journal of System Simulation, 2020, 32(6): 975-981.
[6]	Helbing D, Isobe M, Nagatani T, et al. Lattice Gas Simulation of Experimentally Studied Evacuation Dynamics[J]. Physical Review E (S2470-0045), 2003, 67: 1-4.
[7]	高国平, 管昌生. 考虑帮助行为的人员疏散元胞自动机模型[J]. 中国安全科学学报, 2018, 28(1): 56-61.
	Gao Guoping, Guan Changsheng. A Helping Behavior-considering Cellular Automaton Model for Evacuation from a Building[J]. China Safety Science Journal, 2018, 28(1): 56-61.
[8]	陈长坤, 孙华锴, 童蕴贺, 等. 基于元胞自动机的火源威胁下人员疏散模型[J]. 中国安全生产科学技术, 2020, 16(10): 47-52.
	Chen Changkun, Sun Huakai, Tong Yunhe, et al. Personnel Evacuation Model Under Fire Source Threat Based on Cellular Automata[J]. Journal of Safety Science and Technology, 2020, 16(10): 47-52.
[9]	徐福顺, 丁赛喆, 侯亚楠, 等. 考虑行人避障行为的元胞自动机模型[J]. 南京工业大学学报(自然科学版), 2021, 43(2): 247-254.
	Xu Fushun, Ding Saizhe, Hou Yanan, et al. Cellular Automata Model Considering Pedestrian Obstacle Avoidance Behavior[J]. Journal of Nanjing Tech University (Natural Science Edition), 2021, 43(2): 247-254.
[10]	岳昊, 邵春福, 关宏志, 等. 基于元胞自动机的行人视线受影响的疏散流仿真研究[J]. 物理学报, 2010, 59(7): 4499-4507.
	Yue Hao, Shao Chunfu, Guan Hongzhi, et al. Simulation of Pedestrian Evacuation Flow with Affected Visual Field Using Cellular Automata[J]. Acta Physica Sinica, 2010, 59(7): 4499-4507.
[11]	杨灿, 陈群, 陈璐. 考虑在能见度受限下行人跟随行为特性的建模与模拟[J]. 物理学报, 2019, 68(24): 81-95.
	Yang Can, Chen Qun, Chen Lu. Following Behaviors of Visibility-limited Pedestrians[J]. Acta Physica Sinica, 2019, 68(24): 81-95.
[12]	Geng Zhongfei, Li Xingli, Kuang Hua, et al. Effect of Uncertain Information on Pedestrian Dynamics under Adverse Sight Conditions[J]. Physica A (S0378-4371), 2019, 521: 681-691.
[13]	Li Xingli, Guo Fang, Kuang Hua, et al. An Extended Cost Potential Field Cellular Automaton Model for Pedestrian Evacuation Considering the Restriction of Visual Field[J]. Physica A (S0378-4371), 2019, 515: 47-56.

[1]	Jianxu Zhang, Shuai Hu, Hongyi Jin. Modeling of Traffic Flow Velocity Control Strategy for Human-machine Mixed Driving at Signalized Intersections [J]. Journal of System Simulation, 2022, 34(8): 1697-1709.
[2]	Yangsheng Jiang, Sichen Wang, Kuan Gao, Meng Liu, Zhihong Yao. Cellular Automata Model of Mixed Traffic Flow Composed of Intelligent Connected Vehicles’ Platoon [J]. Journal of System Simulation, 2022, 34(5): 1025-1032.
[3]	Li Xinli, Zou Changming, Yang Guotian, Liu He. Research of Super-resolution Processing of Invoice Image Based on Generative Adversarial Network [J]. Journal of System Simulation, 2021, 33(6): 1307-1314.
[4]	Liu Zhanhong, Yang Xiujian, Wu Xiangji, Huang Zhen. Modeling and Simulation of Car Following in Fog Based on Cellular Automata [J]. Journal of System Simulation, 2021, 33(10): 2399-2410.
[5]	Liu Zongyang, Zhou Chunhui, Zhao Junnan, Xiao Jinli, Gan Langxiong. Modeling and Simulation of Channel Passage Capacity Based on Cellular Automata [J]. Journal of System Simulation, 2021, 33(10): 2478-2487.
[6]	Song Yinghua, Zhang Yu, Huo Feizhou, Lü Wei, Ma Yaping. Study on Evacuation Cellular Automaton Model Considering Avoidance Behavior [J]. Journal of System Simulation, 2020, 32(6): 975-981.
[7]	Xing Zhiwei, Xu Mingyi, Luo Xiao, Luo Qian. Simulation and Optimization of Aircraft Sliding Path [J]. Journal of System Simulation, 2020, 32(2): 323-331.
[8]	Sun Di, Zhou Jin, Gao Xueying, Jiao Ting, Zhao Lixian. Simulation Research on Pedestrian Evacuation Path Selection in the Metro Station [J]. Journal of System Simulation, 2019, 31(9): 1819-1826.
[9]	Liu Haijiang, Xu Qingqing, Tang Da. Optimization Simulation Analysis of Process Parameters on Sunroof Roller Hemming Quality of Car [J]. Journal of System Simulation, 2019, 31(6): 1223-1231.
[10]	Kong Hongshan, Yu Bin. An Improved Algorithm of VIRE Based on BP Neural Network [J]. Journal of System Simulation, 2018, 30(9): 3586-3595.
[11]	Xing Zhiwei, Li Shijiao, Tang Yunxiao, Luo Qian. Airport Surface Traffic Simulation Based on Agent-Cellular Automaton [J]. Journal of System Simulation, 2018, 30(3): 857-865.
[12]	Lu Yingbo, Qian Xiaochao, Chen Wei, He Shu, Lu Zhifeng. Research on Construction Method of Data-Driven Equipment Effectiveness Evaluation Model [J]. Journal of System Simulation, 2018, 30(12): 4587-4595.
[13]	Xie Shiqin, Zhao Tianzhong, Wang Wei, Shi Jingjing. Study on Fusion Algorithms of GF-2 Satellite Image [J]. Journal of System Simulation, 2017, 29(11): 2742-2747.
[14]	Ding Jianfei, Si Guangya, Shi Yafeng, Liu Yi. Visualization of Multi-dimensional Effectiveness Indicator of Weapon System of SystemsBased on Fusion Manifold Learning [J]. Journal of System Simulation, 2017, 29(10): 2373-2383.
[15]	Hou Kun, Li Zhilong, Feng Yuchao, Chen Yi. Circular Space-filling Algorithm for Hierarchical Data Visualization [J]. Journal of System Simulation, 2016, 28(9): 2035-2041.