社会行为驱动的疏散仿真方法研究

doi:10.16182/j.issn1004731x.joss.17-CACIS004

系统仿真学报 ›› 2020, Vol. 32 ›› Issue (1): 130-141.doi: 10.16182/j.issn1004731x.joss.17-CACIS004

社会行为驱动的疏散仿真方法研究

邓媛媛, 郑利平, 蔡瑞文

合肥工业大学计算机与信息学院VCC实验室,安徽合肥 230009

收稿日期:2017-05-10 修回日期:2017-07-25 发布日期:2020-01-17
作者简介:邓媛媛(1992-),女,安徽合肥,硕士生,研究方向为可视化与仿真;郑利平(1978-),男,湖北麻城,博士,教授,研究方向为可视化与仿真。
基金资助:
国家重点研发计划(2016YFC0800100),安徽省科技强警项目(1704d0802177)

Research on Evacuation Simulation Method Considering Social Behavior

Deng Yuanyuan, Zheng Liping, Cai Ruiwen

VCC Laboratory, School of Computer and Information, Hefei University of Technology, Hefei 230009, China

Received:2017-05-10 Revised:2017-07-25 Published:2020-01-17

摘要/Abstract

摘要： 在紧急疏散场景中,个人具有的典型社会属性会对其疏散行为产生影响。将个体对环境的熟悉程度和个体所属团队这2种社会因素引入并应用到人群疏散仿真中,提出一种疏散仿真方法。利用RVO库的实时避碰技术模拟人群的动态运动过程,通过添加局部目标点以及对局部目标点的选择机制来动态模拟人群不同的社会行为。通过对不同熟悉度的人群以及不同团队数量的人群进行仿真实验,实验结果表明环境熟悉程度和团队因素对疏散时间存在一定影响,仿真结果具有较高真实性。

关键词: 疏散仿真, 环境熟悉度, 团队, RVO2(Reciprocal Velocity Obstacle)

Abstract: In an emergency evacuation scenario, the typical social attributes of an individual impact their evacuation behavior. Two kinds of social factors, such as individual familiarity to the environment and the individual group, are introduced and applied in crowd evacuation simulation. An evacuation simulation method is proposed. The real-time collision avoidance technique of RVO library is used to simulate the dynamic motion of the population. The local target points and its selection mechanism are used to simulate the different social behaviors of the population. Experiments show that the familiarity to the environment and group factors have influence on the evacuation time. Experiments show that the method can achieve better simulation results.

Key words: evacuation simulation, familiarity with the environment, group, RVO2(Reciprocal Velocity Obstacle)

中图分类号:

TP391.9

邓媛媛, 郑利平, 蔡瑞文. 社会行为驱动的疏散仿真方法研究[J]. 系统仿真学报, 2020, 32(1): 130-141.

Deng Yuanyuan, Zheng Liping, Cai Ruiwen. Research on Evacuation Simulation Method Considering Social Behavior[J]. Journal of System Simulation, 2020, 32(1): 130-141.

参考文献

[1] 黄希发, 王科俊, 张磊, 等. 基于个体能力差异的人员疏散微观模型研究[J]. 中国安全生产科学技术, 2009, 5(5): 72-77.
Huang Xifa, Wang Kejun, Zhang Lei, et al.Study on a microscopic model of pedestrian evacuation based on different individual capacity[J]. Journal of Safety Science and Technology, 2009, 5(5): 72-77.
[2] 王林. 基于生理特征的异质人群仿真方法[D]. 合肥: 合肥工业大学, 2014.
Wang Lin.Research on Heterogeneous Crowd Behaviors Simulation Based on Physiological Characteristics[D]. Hefei: Hefei University of Technology, 2014.
[3] Reynolds C W.Flocks, herds and schools: A distributed behavioral model[C]. Siggraph 1987, New York, USA, ACM, 1987, 21(4): 25-34.
[4] Helbing D, Molnár P.Social force model for pedestrian dynamics[J]. Physical Review E Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics (S1063-651), 1998, 51(5): 4282-4293.
[5] Bera A, Kim S, Manocha D.Efficient trajectory extraction and parameter learning for data-driven crowd simulation[C]. Graphics Interface Conference. Halifax, NS, Camada : Canadian Information Processing Society. 2015: 65-72.
[6] Berg J V D, Lin M, Manocha D. Reciprocal Velocity Obstacles for real-time multi-agent navigation[C]. IEEE International Conference on Robotics and Automation. NEW YORK: IEEE, 2008: 1928-1935.
[7] Kaup D J, Clarke T L, Oleson R, et al.Introducing age-based parameters into simulations of crowd dymanics[C]. Simulation Conference, 2008. Wsc. NEW YORK: IEEE, 2008: 895-902.
[8] Pan X, Han C S, Dauber K, et al.A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations[J]. AI & SOCIETY(S0951-5666), 2007, 22(2): 113-132.
[9] Sivers I V, Templeton A, Köster G, et al.Humans do not Always Act Selfishly: Social Identity and Helping in Emergency Evacuation Simulation[J]. Transportation Research Procedia(S2352-1465), 2014, 2: 585-593.
[10] Tsai J, Fridman N, Bowring E, et al.ESCAPES- Evacuation Simulation with Children, Authorities, Parents, Emotions, and Social comparison[C]. AAMAS’11, Taiwan, International Foundation for Autonomous Agents and Multiagent Systems, 2011, 457-464.
[11] Chu M L, Parigi P, Law K, et al.Modeling social behaviors in an evacuation simulator[J]. Computer Animation & Virtual Worlds(S1546-4261), 2014, 25(3/4): 373-382.
[12] 黄杨昱, 胡伟, 袁国栋. 基于全局路径规划的相互速度障碍物人群疏散方法[J]. 计算机应用, 2013, 33(6): 1753-1758.
Huang Yangyu, Hu Wei, Yuan Guodong.Global path planning based reciprocal velocity, obstacles method for crowd evacuation[J]. Journal of Computer Applications, 2013, 33(6): 1753-1758.
[13] 巫志勇. 在陌生环境下的人群疏散仿真[D]. 广州: 中山大学, 2010.
Wu Zhiyong.Pedestrians Evacuation Simulation in Unacquainted Environment[D]. Guangzhou: Sun Yat-sen University, 2010.
[14] Fiorini P.Motion planning in dynamic environments using velocity obstacles[J]. International Journal of Robotics Research(S0278-3649), 1998, 17(7): 760-772.
[15] 段凡丁. 关于最短路径的SPFA快速算法[J]. 西南交通大学学报, 1994, 29(2): 207-212.
Duan Fanding.A Faster Algorithm for Shortest-Path- SPFA[J]. Journal of Southwest Jiaotong University, 1994, 29(2): 207-212.
[16] Zhao Z, Zhang Y J, Feng X, et al.An analysis of herding behavior in security analysts’ networks[J]. Physica A Statistical Mechanics & Its Applications(S0378-4371), 2014, 413: 116-124.
[17] Mehmood R, Bie R, Dawood H, et al.Fuzzy Clustering by Fast Search and Find of Density Peaks[C]. International Conference on Identification, Information, and Knowledge in the Internet of Things. NEW YORK; IEEE, 2016: 258-261.

社会行为驱动的疏散仿真方法研究

Research on Evacuation Simulation Method Considering Social Behavior

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