步行设施内的行人行为微观仿真模型研究
|
摘要
随着人类社会文明的进步,长距离多方式的出行以及各种群体活动日益频繁,交通枢纽、体育场馆等大型步行设施在社会生活中的作用不断凸显。出于对行人安全性、高效性和舒适性的关注,旨在对步行设施的建设与运营方案进行评估、优化的微观行人仿真研究,成为当前行人研究领域的热点。本文遵循“步行设施特征分析微观行人仿真框架建立行人路径规划算法设计微观行走仿真模型研究设施交互模型研究仿真程序开发与应用”的研究脉络,专门面向大型步行设施开展了微观行人行为仿真模型研究。
论文梳理了行人行为微观仿真模型的研究现状,详细分析了基于力的模型、元胞自动机系列模型以及离散选择模型的基本原理和核心逻辑,重点指出了前者存在的局限性:基于线性加合的多因素作用合成机制。
论文针对大型多层步行设施具有的空间复杂、行人行为多样的特征,提出了由基本行走区域和运送设施构成的连续空间描述机制,设计出用于模拟行人行为的总体逻辑流程,论证了其在正常行走和紧急疏散两种典型情景下的适用性,最终建立了专用于大型步行设施的微观仿真研究框架。论文通过对行人行走的决策过程和单步动作进行分析,提出了基于“转向+调速”的动作描述机制和基于邻域作用原理的邻域决策模型。在该模型中,行人将内在动机。外部障碍等所有影响因素的整体作为决策依据,用邻域分析算法评估每一个可行方位的效用和可行距离,基于主观效用最大化原则驱动行人进行决策。论文提出了最短路径算法、自然路径算法和基于离散势能场的路径规划算法等三种算法,详细介绍了其执行流程、优点和适用性。论文设计了基本行走区域和运送设施之间的衔接机制,并建立了最常见的楼梯和自动扶梯的设施交互模型。
论文基于模型研究成果使用Visual C++ 2008开发了微观行人仿真软件原型RealWalker。该软件可以支持场景建模、仿真运行、参数配置、结果输出析构成的步行设施仿真分析的完整工作流程。最后,通过仿真算例验证了各个模型的有效性、模型间的协作能力以及模型在正常行走和紧急疏散情景下的适用性。
With the progress of human civilization, many long-distance multi-mode of travel as well as various group activities have become increasingly frequent. The pedestrian infrastructures such as transportation hubs and sports stadium highlight the significant role in social life. Based on consideration of pedestrian safety, efficiency and comfort, the microscopic pedestrian simulation aim to evaluate and optimize the construction and operation of walking facilities, which has become a hot research topic. This dissertation focuses on simulation model of pedestrian behavior in large-scale walking facilities. The architecture of this dissertation is: (1) Analysis of simulation research framework; (2) Path planning algorithm; (3) Walk simulation model; (4) Facility interactive model; (5) Simulation software development and application.
First, this dissertation reviews existing literature on pedestrian behavior simulation modeling. It systematically summarizes the main simulation models and analyses the basic principles, assumptions and the core algorithm of force-based model, the cellular automata simulation model and the discrete choice model. Moreover, this dissertation emphasizes the critical limitation of force-based model: the linear synthesis mechanism for effect factors. Based on the features of large-scale multi-layers walking facility such as complex spatial structure and a variety of pedestrian behaviors, a continuous spatial mechanism includes basic walk zone and transport facility is proposed. The pedestrian’s decision-making behavior is divided into macro, meso and micro three levels. The overall logic flow of pedestrian behavior and research framework is extracted. Moreover, their applicability in the normal operating and emergency evacuation is analyzed. The walk simulation model, path planning algorithm and facility interactive model are focused.
Through the analysis on single-step walk movement, a new description mechanism is proposed including direction changing and velocity adjusting. Analyzed pedestrian’s actual decision-making process, a bran-new walk decision-making model based on neighborhood impact principle is designed. Its core principle is: pedestrian’s decision is made according to his inner motivations and all information from his neighborhood. This model includes the description method, the analyse algorithm for neighborhood and the subjective utility calculation method for impact factors. This dissertation also designs three path planning algorithms based on diffirent elements, which are the Shortest Path Algorithm, the Natural Path Algorithm and the Discrete Potential Field-based Planning Algorithm. Their logic flow, advantages and applicability are introduced in detail. In order to modeling multi-layer space, this dissertation proposes an interactive mechanism and modeling method between basic walk zone and transport facility. For instance, a stairs model and escalator model are discussed.
Based on the above-mentioned research results, this dissertation finally develops a microscopic pedestrian simulation software prototype named RealWalker using Visual C++ 2008. The RealWalker can simulate the large-scale multi-layer walking facilities and support a complete workflow includes the scene construction, simulation execution, output and analysis. Finally, the simulation experiments verified the validity of each model, the ability of mutual cooperation of multi-models and the applicability in the normal operating and emergency evacuation.
论文梳理了行人行为微观仿真模型的研究现状,详细分析了基于力的模型、元胞自动机系列模型以及离散选择模型的基本原理和核心逻辑,重点指出了前者存在的局限性:基于线性加合的多因素作用合成机制。
论文针对大型多层步行设施具有的空间复杂、行人行为多样的特征,提出了由基本行走区域和运送设施构成的连续空间描述机制,设计出用于模拟行人行为的总体逻辑流程,论证了其在正常行走和紧急疏散两种典型情景下的适用性,最终建立了专用于大型步行设施的微观仿真研究框架。论文通过对行人行走的决策过程和单步动作进行分析,提出了基于“转向+调速”的动作描述机制和基于邻域作用原理的邻域决策模型。在该模型中,行人将内在动机。外部障碍等所有影响因素的整体作为决策依据,用邻域分析算法评估每一个可行方位的效用和可行距离,基于主观效用最大化原则驱动行人进行决策。论文提出了最短路径算法、自然路径算法和基于离散势能场的路径规划算法等三种算法,详细介绍了其执行流程、优点和适用性。论文设计了基本行走区域和运送设施之间的衔接机制,并建立了最常见的楼梯和自动扶梯的设施交互模型。
论文基于模型研究成果使用Visual C++ 2008开发了微观行人仿真软件原型RealWalker。该软件可以支持场景建模、仿真运行、参数配置、结果输出析构成的步行设施仿真分析的完整工作流程。最后,通过仿真算例验证了各个模型的有效性、模型间的协作能力以及模型在正常行走和紧急疏散情景下的适用性。
With the progress of human civilization, many long-distance multi-mode of travel as well as various group activities have become increasingly frequent. The pedestrian infrastructures such as transportation hubs and sports stadium highlight the significant role in social life. Based on consideration of pedestrian safety, efficiency and comfort, the microscopic pedestrian simulation aim to evaluate and optimize the construction and operation of walking facilities, which has become a hot research topic. This dissertation focuses on simulation model of pedestrian behavior in large-scale walking facilities. The architecture of this dissertation is: (1) Analysis of simulation research framework; (2) Path planning algorithm; (3) Walk simulation model; (4) Facility interactive model; (5) Simulation software development and application.
First, this dissertation reviews existing literature on pedestrian behavior simulation modeling. It systematically summarizes the main simulation models and analyses the basic principles, assumptions and the core algorithm of force-based model, the cellular automata simulation model and the discrete choice model. Moreover, this dissertation emphasizes the critical limitation of force-based model: the linear synthesis mechanism for effect factors. Based on the features of large-scale multi-layers walking facility such as complex spatial structure and a variety of pedestrian behaviors, a continuous spatial mechanism includes basic walk zone and transport facility is proposed. The pedestrian’s decision-making behavior is divided into macro, meso and micro three levels. The overall logic flow of pedestrian behavior and research framework is extracted. Moreover, their applicability in the normal operating and emergency evacuation is analyzed. The walk simulation model, path planning algorithm and facility interactive model are focused.
Through the analysis on single-step walk movement, a new description mechanism is proposed including direction changing and velocity adjusting. Analyzed pedestrian’s actual decision-making process, a bran-new walk decision-making model based on neighborhood impact principle is designed. Its core principle is: pedestrian’s decision is made according to his inner motivations and all information from his neighborhood. This model includes the description method, the analyse algorithm for neighborhood and the subjective utility calculation method for impact factors. This dissertation also designs three path planning algorithms based on diffirent elements, which are the Shortest Path Algorithm, the Natural Path Algorithm and the Discrete Potential Field-based Planning Algorithm. Their logic flow, advantages and applicability are introduced in detail. In order to modeling multi-layer space, this dissertation proposes an interactive mechanism and modeling method between basic walk zone and transport facility. For instance, a stairs model and escalator model are discussed.
Based on the above-mentioned research results, this dissertation finally develops a microscopic pedestrian simulation software prototype named RealWalker using Visual C++ 2008. The RealWalker can simulate the large-scale multi-layer walking facilities and support a complete workflow includes the scene construction, simulation execution, output and analysis. Finally, the simulation experiments verified the validity of each model, the ability of mutual cooperation of multi-models and the applicability in the normal operating and emergency evacuation.
引文
[1]高海波,陈辉,商蕾,等,微观交通仿真中的行人干扰模型.交通科技与经济, 2004, 4.
[2]孙智勇.信号交叉口人行横道的行人交通特性研究[硕士学位论文].北京:北京工业大学, 2004.
[3]孙智勇,葛书芳,荣建,等.行人交通的数据采集方法研究.北京工业大学学报, 2006, 6.
[4]彭丽英.信号控制交叉口行人交通特性的研究[硕士学位论文].长春:吉林大学, 2006.
[5]徐高.人群疏散的仿真研究[硕士学位论文].成都:西南交通大学, 2003.
[6]徐高.基于智能体技术的人员疏散仿真模型.西南交通大学学报, 2003, 6.
[7]宋卫国,于彦飞,陈涛.出口条件对人员疏散的影响及其分析.火灾科学, 2003, 4.
[8]宋卫国,于彦飞,范维澄,等.一种考虑摩擦与排斥的人员疏散元胞自动机模型.中国科学: E辑-工程科学-材料科学, 2005.
[9]宋卫国,于彦飞,张和平.某大型商贸中心的人员疏散性能化分析.中国工程科学, 2005, 10.
[10]宋卫国,于彦飞,张和平.基于智能体技术的人员群集流动动力学模型.沈阳建筑大学学报:自然科学版, 2005, 7.
[11]王平.大型公共建筑人员疏散性能化评估软件的开发[硕士学位论文].武汉:武汉大学, 2005.
[12]李伏京,方卫宁.磁悬浮车辆中人员紧急疏散的仿真研究.中国安全科学学报, 2005, 8.
[13]李伏京,方卫宁,胡清梅,等.地铁车辆安全疏散性能的仿真研究.系统仿真学报, 2006, 4.
[14]刘茂,王振.行人和疏散动力学研究现状及进展.安全与环境学报, 2006, 7.
[15]潘忠,王长波,谢步瀛.基于几何连续模型的人员疏散仿真.系统仿真学报, 2006, 8.
[16]沙云飞.人群疏散的微观仿真模型研究[博士学位论文].北京:清华大学, 2008.
[17]王华东.城市混合交通系统的建模方法与应用研究[博士学位论文].杭州:浙江大学, 2003.
[18]张晋.基于元胞自动机的城域混合交通流建模方法研究[博士学位论文].杭州:浙江大学, 2004.
[19]马征.公众聚集场所人员安全疏散性能化设计与评价[硕士学位论文].西安:西安建筑科技大学, 2004.
[20]孔留安,周爱桃,景国勋,等.人员疏散时间预测与分析.中国安全科学学报, 2005, 11.
[21]张培红,陈宝智.火灾时人员疏散的行为规律.东北大学学报:自然科学版, 2001, 22(1).
[22]张培红,刘丽珍.大型公共建筑物火灾时人员疏散行为规律研究评论推荐.中国安全科学学报, 2001, 11(2).
[23]张培红,黄晓燕,万欢欢,等.基于智能体技术的人员群集流动动力学模型.沈阳建筑大学学报:自然科学版, 2005, 21(4).
[24]周爱桃,景国勋,魏平儒,等. L型房间单元人员疏散探讨.中国安全科学学报, 2006, 8.
[25]赵建明,欧阳俊,方燕玲.广州市行人交通违规现象调查报告.中国科技论文在线, 2006. http://www.paper.edu.cn/downloadpaper.php?serial_number=200609-45.
[26]潘明阳,严飞,谢海燕.基于智能体与元胞自动机的智能交通仿真.交通运输工程学报, 2006, 6.
[27]杨建国,王兆安,李庆丰.混杂交通微观仿真初探.系统仿真学报, 2006, 6.
[28] S.A.H. AlGadhi, H.S. Mahmassani, R. Herman, A Speed-Concentration Relation for Bi-Directional Crowd Movements with Strong Interaction, In: Pedestrian and Evacuation Dynamics, M. Schreckenberg and S. D. Sharma (Eds), 2001: 3-4.
[29] Dirk Helbing. A Mathematical Model for the Behavior of Pedestrians. General Systems Science Foundation, 1991: 298-310.
[30] Dirk Helbing. Models for pedestrian behavior. Behavior Science, 1998(2): 89-101.
[31] Dirk Helbing. Related self-driven many particle systems. Rev Mod Phys, 2001, 73(4): 1067-1141.
[32] Helbing D, Molnar P. Self-Organization Phenomena in Pedestrian Crowds. F. Schweitzer (ed.) Self-Organization of Complex Structures: From Individual to Collective Dynamics, Gordon and Breach. London 1997: 569-577.
[33] Dirk Helbing. A fluid dynamic model for the movement of pedestrians. Complex Systems, 1992, 6 :391-415.
[34] Helbing D, Molnar P, Schweitzer F. Computer Simulation of Pedestrian Dynamics and trail Formation. Evolution of Natural Science (Sonderforschungsbereich 230. Stuttgart.), 1994: 229-234.
[35] Helbing D., Keltsch J., Molnar P. Modelling the evolution of human trail systems. Nature, 1997, 388: 47-50.
[36] Dirk Helbing. A mathematical model for the behavior of individuals in a social field. Journal of Mathematical Sociology , 1994 ,19 (3) :189-219.
[37] Helbing, D, Molnar, P, Social force model for pedestrian dynamics. Physical Review E, 1995, 51: 4282-4286.
[38] Helbing D, Schweitzer F, Keltsch J, et al. Active walker model for the formation of human and animal trail systems. Physical Review E, 1997, 56(3): 2527～2539.
[39] Helbing D, Farkas IJ, Vicsek T. Freezing by Heating in a Driven Mesoscopic System. PHYSICAL REVIEW LETTERS, 2000, 1.
[40] Dirk Helbing, Illés Farkas, Tamás Vicsek. Simulating dynamical features of escape panic. Nature, 2000, 9.
[41] Helbing D, Buzna Lubos, J Anders, et al. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. INFORMS Inst. for Operations Res. and the Management Sciences, Hanover, MD 21076, United States, 2005, 39(1): 1.
[42] Helbing D, J Anders, H Z Al-Abideen. Dynamics of crowd disasters: An empirical study. American Physical Society, College Park, MD 20740-3844, United States, 2007, 75(4): 046109.
[43] Hoogendoorn SP, Bovy PHL. Dynamic user-optimal assignment in continuous time and space. Transportation Research Part B: methodological, 2004, 38 (7): 571-592.
[44] Hoogendoorn SP, Bovy PHL. Simulation of Pedestrian Flows by Optimal Control and Differential Games. Optimal control applications & methods, 2003, 24(3): 153-172.
[45] Hoogendoorn SP, Bovy PHL. Pedestrian route-choice and activity scheduling theory and models. Transportation Research Part B: methodological, 2004, 38(2): 169-190.
[46] Winnie Daamen. Modelling Passenger Flows in Public Transport Facilities. Trail Thesis Series, The Netherlands TRAIL Research School, 2004, 6.
[47] Winnie Daamen, Serge P, Hoogendoorn. Research on pedestrian traffic flow in the Netherlands. Proceedings Walk 21 IV, Portland, Oregon, United States, 2003: 101-117.
[48] Hoogendoorn SP, Daamen W, Bovy PHL. Extracting microscopic pedestrian characteristics from video data. Transportation Research Board annual meeting, 2003: 1-15.
[49] Daamen W, Hoogendoorn SP, Bovy PHL. First-order Pedestrian Traffic Flow Theory. Transportation Research Board Annual Meeting, 2005: 1-14.
[50] Daamen W. SimPed: a pedestrian simulation tool for large pedestrian areas. Proceedings of the European Simulation Interoperability Workshop, London, 2002, 6.
[51] Blue V.J, Adler J.L. Using Cellular Automata Microsimulation to Model Pedestrian Movements. Proceedings of the 14th International Symposium on Transportation and Traffic Theory, 1999, 7: 235-254.
[52] Blue V.J, Adler J.L. Cellular Automata Microsimulation of Bi-Directional Pedestrian Flows. Transportation Research Record, Journal of the Transportation Research Board, 2000, 1678: 135-141.
[53] Blue V.J, Adler J.L, Modeling Four-Directional Pedestrian Movements. Transportation Research Record, 2000.
[54] Christian Gloor, Laurent Mauron, Kai Nagel. A pedestrian simulation for hiking in the Alps. The Swiss Transportation Research Conference, 2003.
[55] Christian Gloora, Duncan Cavens, Eckart Lange, et al. A pedestrian simulation for very large scale applications. Multi-Agenten-Systeme in der Geographie, Klagenfurter Geographische Schriften, 23, 2003, 10.
[56] Cavens D, Gloor C, Illenberger J, et al. Distributed intelligence in pedestrian simulations. ETH Zürich, Switzerland, 2003.
[57] Duncan Cavens, Eckart Lange, Willy Schmid, Virtual Alpine Landscapes and Autonomous Agents. Buhmann, E. and Ervin, S. (eds.), Trends in Landscape Modelling, Wichmann Verlag, Heidelberg, 2003.
[58] Christian Gloor, Pascal Stucki, Kai Nagel, Hybrid techniques for pedestrian simulations. Lecture Notes in Computer Science, Cellular Automata: 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004, Amsterdam, The Netherlands, 2004, 10: 25-28.
[59] Christian Gloor, Kai Nagel, A Message Based Framework for Real World Mobility Simulations. The 17th International Conference on Computer Animation & Social Agens, 2004.
[60] Gianluca Antonini, Michel Bierlaire, Mats Weber. Simulation of Pedestrian Behaviour using a Discrete Choice Model Calibrated on Actual Motion Data. Proceedings of the Swiss Transport Research Conference (STRC), 2004[2004-03-24~26].
[61] Gianluca Antonini, Michel Bierlaire. Capturing interactions in pedestrian walking behavior in a discrete choice framework. The 6th Swiss Transport Research Conference, 2006[2006-03-15~17].
[62] Okazaki S. A Study of Pedestrian Movement in Architectural Space, Part 1: Pedestrian Movement by the Application on of Magnetic Models. Trans. of A.I.J, 1979.
[63] Okazaki S, Matsushita S. A study of simulation model for pedestrian movement with evacuation and queuing. Proceeding of the International Conference on Engineering for Crowd Safety, 1993: 271-280.
[64] Teknomo Kardi, Yasushi Takeyama, Hajime Inamura. Review on Microscopic Pedestrian Simulation Model. Proceedings Japan Society of Civil Engineering Conference, Morioka, Japan, 2000, 3.
[65] Kardi Teknomo. Microscopic Pedestrian Flow Characteristics: Development of an Image Processing Data Collection and Simulation Model[博士学位论文]. School of Information Sciences, Tohoku University, Japan, 2002.
[66] Juri Tolujew, Felix Alcalá. A MESOSCOPIC APPROACH TO MODELING AND SIMULATION OF PEDESTRIAN TRAFFIC FLOWS. Proceedings 18th European Simulation Multiconference Graham Horton(c) SCS Europe, 2004.
[67] AndréHanisch, Juri Tolujew, Klaus Richter, et al. ONLINE SIMULATION OF PEDESTRIAN FLOW IN PUBLIC BUILDINGS, Proceedings of the 2003 Winter Simulation Conference, 2003.
[68] Srihari Narasimhan, Hans-Joachim Bungartz. A Framework for A Graph- and Queuing System-Based Pedestrian Simulation. MSV 2006, Las Vegas, Nevada, USA, 2006[2006-06-26~29].
[69] Guo R Y, H J Huang. A mobile lattice gas model for simulating pedestrian evacuation. Physica A: Statistical Mechanics and its Applications, 2008, 387(2-3): 580-586.
[70] Ronald N, L Sterling. Modelling pedestrian behaviour using the BDI architecture. Proceedings of the 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2005.
[71] Zhang PeiHong, Huang XiaoYan, Wan HuanHuan, et al. Agent-based model for crowd flow dynamics. Journal of Shenyang Jianzhu University (Natural Science), 2005, 21(4): 358.
[72] Ronald N, L Sterling, M Kirley. Evaluating JACK sim for agent-based modelling of pedestrians. Proceedings of the 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2006.
[73] J Izquierdo, I Montalvo, R Pérez, et al. Forecasting pedestrian evacuation times by using swarm intelligence. Physica A: Statistical Mechanics and its Applications, 2009, 388(7): 1213-1220.
[74] Lewin K. Field Theory in social Science. Harper, NewYork 1951.
[75] Fang W, L Yang, W Fan. Simulation of bi-direction pedestrian movement using a cellular automata model. Physica A: Statistical Mechanics And Its Applications, 2003, 321(3-4): 633-640.
[76] Li, J., L.H. Yang, and D.L. Zhao, Simulation of bi-direction pedestrian movement in corridor. Physica A: Statistical Mechanics And Its Applications, 2005, 354: 619-628.
[77] Weifeng Y, T Kang Hai. A novel algorithm of simulating multi-velocity evacuation based on cellular automata modeling and tenability condition. Physica A: Statistical Mechanics and its Applications, 2007, 379(1): 250-262.
[78] Ronald N, M Kirley. Pedestrian modelling: A comparative study using agent-based cellular automata. Reading, United Kingdom: Springer Verlag, Heidelberg, D-69121, Germany, 2006.
[79] Xu X, W G Song, H Y Zheng. Discretization effect in a multi-grid egress model. Physica A: Statistical Mechanics and its Applications, 2008, 387(22): 5567-5574.
[80] Liu Shaobo, Yang Lizhong, Fang Tingyong Liu, et al. Evacuation from a classroom considering the occupant density around exits. Physica A: Statistical Mechanics and its Applications, 2009, 388(9): 1921-1928.
[81] EXODUS INTRODUCTION, http://fseg.gre.ac.uk/exodus/.
[82] http://www.legion.com/.
[83] http://www.crowddynamics.com/.
[84] http://www.simwalk.com/.
[85] Kretz T, Grunebohm A, Kessel A, et al. Upstairs walking speed distributions on a long stairway. Safety Science, 2008, 46(1): 72-78.
[86] Lee J.Y.S, Lam W.H.K. Variation of walking speeds on a unidirectional walkway and on a bidirectional stairway. 2006, (1982): 122.
[87]中华人民共和国国家标准. GB10000-88.中国成年人人体尺寸, 1989.
[2]孙智勇.信号交叉口人行横道的行人交通特性研究[硕士学位论文].北京:北京工业大学, 2004.
[3]孙智勇,葛书芳,荣建,等.行人交通的数据采集方法研究.北京工业大学学报, 2006, 6.
[4]彭丽英.信号控制交叉口行人交通特性的研究[硕士学位论文].长春:吉林大学, 2006.
[5]徐高.人群疏散的仿真研究[硕士学位论文].成都:西南交通大学, 2003.
[6]徐高.基于智能体技术的人员疏散仿真模型.西南交通大学学报, 2003, 6.
[7]宋卫国,于彦飞,陈涛.出口条件对人员疏散的影响及其分析.火灾科学, 2003, 4.
[8]宋卫国,于彦飞,范维澄,等.一种考虑摩擦与排斥的人员疏散元胞自动机模型.中国科学: E辑-工程科学-材料科学, 2005.
[9]宋卫国,于彦飞,张和平.某大型商贸中心的人员疏散性能化分析.中国工程科学, 2005, 10.
[10]宋卫国,于彦飞,张和平.基于智能体技术的人员群集流动动力学模型.沈阳建筑大学学报:自然科学版, 2005, 7.
[11]王平.大型公共建筑人员疏散性能化评估软件的开发[硕士学位论文].武汉:武汉大学, 2005.
[12]李伏京,方卫宁.磁悬浮车辆中人员紧急疏散的仿真研究.中国安全科学学报, 2005, 8.
[13]李伏京,方卫宁,胡清梅,等.地铁车辆安全疏散性能的仿真研究.系统仿真学报, 2006, 4.
[14]刘茂,王振.行人和疏散动力学研究现状及进展.安全与环境学报, 2006, 7.
[15]潘忠,王长波,谢步瀛.基于几何连续模型的人员疏散仿真.系统仿真学报, 2006, 8.
[16]沙云飞.人群疏散的微观仿真模型研究[博士学位论文].北京:清华大学, 2008.
[17]王华东.城市混合交通系统的建模方法与应用研究[博士学位论文].杭州:浙江大学, 2003.
[18]张晋.基于元胞自动机的城域混合交通流建模方法研究[博士学位论文].杭州:浙江大学, 2004.
[19]马征.公众聚集场所人员安全疏散性能化设计与评价[硕士学位论文].西安:西安建筑科技大学, 2004.
[20]孔留安,周爱桃,景国勋,等.人员疏散时间预测与分析.中国安全科学学报, 2005, 11.
[21]张培红,陈宝智.火灾时人员疏散的行为规律.东北大学学报:自然科学版, 2001, 22(1).
[22]张培红,刘丽珍.大型公共建筑物火灾时人员疏散行为规律研究评论推荐.中国安全科学学报, 2001, 11(2).
[23]张培红,黄晓燕,万欢欢,等.基于智能体技术的人员群集流动动力学模型.沈阳建筑大学学报:自然科学版, 2005, 21(4).
[24]周爱桃,景国勋,魏平儒,等. L型房间单元人员疏散探讨.中国安全科学学报, 2006, 8.
[25]赵建明,欧阳俊,方燕玲.广州市行人交通违规现象调查报告.中国科技论文在线, 2006. http://www.paper.edu.cn/downloadpaper.php?serial_number=200609-45.
[26]潘明阳,严飞,谢海燕.基于智能体与元胞自动机的智能交通仿真.交通运输工程学报, 2006, 6.
[27]杨建国,王兆安,李庆丰.混杂交通微观仿真初探.系统仿真学报, 2006, 6.
[28] S.A.H. AlGadhi, H.S. Mahmassani, R. Herman, A Speed-Concentration Relation for Bi-Directional Crowd Movements with Strong Interaction, In: Pedestrian and Evacuation Dynamics, M. Schreckenberg and S. D. Sharma (Eds), 2001: 3-4.
[29] Dirk Helbing. A Mathematical Model for the Behavior of Pedestrians. General Systems Science Foundation, 1991: 298-310.
[30] Dirk Helbing. Models for pedestrian behavior. Behavior Science, 1998(2): 89-101.
[31] Dirk Helbing. Related self-driven many particle systems. Rev Mod Phys, 2001, 73(4): 1067-1141.
[32] Helbing D, Molnar P. Self-Organization Phenomena in Pedestrian Crowds. F. Schweitzer (ed.) Self-Organization of Complex Structures: From Individual to Collective Dynamics, Gordon and Breach. London 1997: 569-577.
[33] Dirk Helbing. A fluid dynamic model for the movement of pedestrians. Complex Systems, 1992, 6 :391-415.
[34] Helbing D, Molnar P, Schweitzer F. Computer Simulation of Pedestrian Dynamics and trail Formation. Evolution of Natural Science (Sonderforschungsbereich 230. Stuttgart.), 1994: 229-234.
[35] Helbing D., Keltsch J., Molnar P. Modelling the evolution of human trail systems. Nature, 1997, 388: 47-50.
[36] Dirk Helbing. A mathematical model for the behavior of individuals in a social field. Journal of Mathematical Sociology , 1994 ,19 (3) :189-219.
[37] Helbing, D, Molnar, P, Social force model for pedestrian dynamics. Physical Review E, 1995, 51: 4282-4286.
[38] Helbing D, Schweitzer F, Keltsch J, et al. Active walker model for the formation of human and animal trail systems. Physical Review E, 1997, 56(3): 2527～2539.
[39] Helbing D, Farkas IJ, Vicsek T. Freezing by Heating in a Driven Mesoscopic System. PHYSICAL REVIEW LETTERS, 2000, 1.
[40] Dirk Helbing, Illés Farkas, Tamás Vicsek. Simulating dynamical features of escape panic. Nature, 2000, 9.
[41] Helbing D, Buzna Lubos, J Anders, et al. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. INFORMS Inst. for Operations Res. and the Management Sciences, Hanover, MD 21076, United States, 2005, 39(1): 1.
[42] Helbing D, J Anders, H Z Al-Abideen. Dynamics of crowd disasters: An empirical study. American Physical Society, College Park, MD 20740-3844, United States, 2007, 75(4): 046109.
[43] Hoogendoorn SP, Bovy PHL. Dynamic user-optimal assignment in continuous time and space. Transportation Research Part B: methodological, 2004, 38 (7): 571-592.
[44] Hoogendoorn SP, Bovy PHL. Simulation of Pedestrian Flows by Optimal Control and Differential Games. Optimal control applications & methods, 2003, 24(3): 153-172.
[45] Hoogendoorn SP, Bovy PHL. Pedestrian route-choice and activity scheduling theory and models. Transportation Research Part B: methodological, 2004, 38(2): 169-190.
[46] Winnie Daamen. Modelling Passenger Flows in Public Transport Facilities. Trail Thesis Series, The Netherlands TRAIL Research School, 2004, 6.
[47] Winnie Daamen, Serge P, Hoogendoorn. Research on pedestrian traffic flow in the Netherlands. Proceedings Walk 21 IV, Portland, Oregon, United States, 2003: 101-117.
[48] Hoogendoorn SP, Daamen W, Bovy PHL. Extracting microscopic pedestrian characteristics from video data. Transportation Research Board annual meeting, 2003: 1-15.
[49] Daamen W, Hoogendoorn SP, Bovy PHL. First-order Pedestrian Traffic Flow Theory. Transportation Research Board Annual Meeting, 2005: 1-14.
[50] Daamen W. SimPed: a pedestrian simulation tool for large pedestrian areas. Proceedings of the European Simulation Interoperability Workshop, London, 2002, 6.
[51] Blue V.J, Adler J.L. Using Cellular Automata Microsimulation to Model Pedestrian Movements. Proceedings of the 14th International Symposium on Transportation and Traffic Theory, 1999, 7: 235-254.
[52] Blue V.J, Adler J.L. Cellular Automata Microsimulation of Bi-Directional Pedestrian Flows. Transportation Research Record, Journal of the Transportation Research Board, 2000, 1678: 135-141.
[53] Blue V.J, Adler J.L, Modeling Four-Directional Pedestrian Movements. Transportation Research Record, 2000.
[54] Christian Gloor, Laurent Mauron, Kai Nagel. A pedestrian simulation for hiking in the Alps. The Swiss Transportation Research Conference, 2003.
[55] Christian Gloora, Duncan Cavens, Eckart Lange, et al. A pedestrian simulation for very large scale applications. Multi-Agenten-Systeme in der Geographie, Klagenfurter Geographische Schriften, 23, 2003, 10.
[56] Cavens D, Gloor C, Illenberger J, et al. Distributed intelligence in pedestrian simulations. ETH Zürich, Switzerland, 2003.
[57] Duncan Cavens, Eckart Lange, Willy Schmid, Virtual Alpine Landscapes and Autonomous Agents. Buhmann, E. and Ervin, S. (eds.), Trends in Landscape Modelling, Wichmann Verlag, Heidelberg, 2003.
[58] Christian Gloor, Pascal Stucki, Kai Nagel, Hybrid techniques for pedestrian simulations. Lecture Notes in Computer Science, Cellular Automata: 6th International Conference on Cellular Automata for Research and Industry, ACRI 2004, Amsterdam, The Netherlands, 2004, 10: 25-28.
[59] Christian Gloor, Kai Nagel, A Message Based Framework for Real World Mobility Simulations. The 17th International Conference on Computer Animation & Social Agens, 2004.
[60] Gianluca Antonini, Michel Bierlaire, Mats Weber. Simulation of Pedestrian Behaviour using a Discrete Choice Model Calibrated on Actual Motion Data. Proceedings of the Swiss Transport Research Conference (STRC), 2004[2004-03-24~26].
[61] Gianluca Antonini, Michel Bierlaire. Capturing interactions in pedestrian walking behavior in a discrete choice framework. The 6th Swiss Transport Research Conference, 2006[2006-03-15~17].
[62] Okazaki S. A Study of Pedestrian Movement in Architectural Space, Part 1: Pedestrian Movement by the Application on of Magnetic Models. Trans. of A.I.J, 1979.
[63] Okazaki S, Matsushita S. A study of simulation model for pedestrian movement with evacuation and queuing. Proceeding of the International Conference on Engineering for Crowd Safety, 1993: 271-280.
[64] Teknomo Kardi, Yasushi Takeyama, Hajime Inamura. Review on Microscopic Pedestrian Simulation Model. Proceedings Japan Society of Civil Engineering Conference, Morioka, Japan, 2000, 3.
[65] Kardi Teknomo. Microscopic Pedestrian Flow Characteristics: Development of an Image Processing Data Collection and Simulation Model[博士学位论文]. School of Information Sciences, Tohoku University, Japan, 2002.
[66] Juri Tolujew, Felix Alcalá. A MESOSCOPIC APPROACH TO MODELING AND SIMULATION OF PEDESTRIAN TRAFFIC FLOWS. Proceedings 18th European Simulation Multiconference Graham Horton(c) SCS Europe, 2004.
[67] AndréHanisch, Juri Tolujew, Klaus Richter, et al. ONLINE SIMULATION OF PEDESTRIAN FLOW IN PUBLIC BUILDINGS, Proceedings of the 2003 Winter Simulation Conference, 2003.
[68] Srihari Narasimhan, Hans-Joachim Bungartz. A Framework for A Graph- and Queuing System-Based Pedestrian Simulation. MSV 2006, Las Vegas, Nevada, USA, 2006[2006-06-26~29].
[69] Guo R Y, H J Huang. A mobile lattice gas model for simulating pedestrian evacuation. Physica A: Statistical Mechanics and its Applications, 2008, 387(2-3): 580-586.
[70] Ronald N, L Sterling. Modelling pedestrian behaviour using the BDI architecture. Proceedings of the 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2005.
[71] Zhang PeiHong, Huang XiaoYan, Wan HuanHuan, et al. Agent-based model for crowd flow dynamics. Journal of Shenyang Jianzhu University (Natural Science), 2005, 21(4): 358.
[72] Ronald N, L Sterling, M Kirley. Evaluating JACK sim for agent-based modelling of pedestrians. Proceedings of the 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2006.
[73] J Izquierdo, I Montalvo, R Pérez, et al. Forecasting pedestrian evacuation times by using swarm intelligence. Physica A: Statistical Mechanics and its Applications, 2009, 388(7): 1213-1220.
[74] Lewin K. Field Theory in social Science. Harper, NewYork 1951.
[75] Fang W, L Yang, W Fan. Simulation of bi-direction pedestrian movement using a cellular automata model. Physica A: Statistical Mechanics And Its Applications, 2003, 321(3-4): 633-640.
[76] Li, J., L.H. Yang, and D.L. Zhao, Simulation of bi-direction pedestrian movement in corridor. Physica A: Statistical Mechanics And Its Applications, 2005, 354: 619-628.
[77] Weifeng Y, T Kang Hai. A novel algorithm of simulating multi-velocity evacuation based on cellular automata modeling and tenability condition. Physica A: Statistical Mechanics and its Applications, 2007, 379(1): 250-262.
[78] Ronald N, M Kirley. Pedestrian modelling: A comparative study using agent-based cellular automata. Reading, United Kingdom: Springer Verlag, Heidelberg, D-69121, Germany, 2006.
[79] Xu X, W G Song, H Y Zheng. Discretization effect in a multi-grid egress model. Physica A: Statistical Mechanics and its Applications, 2008, 387(22): 5567-5574.
[80] Liu Shaobo, Yang Lizhong, Fang Tingyong Liu, et al. Evacuation from a classroom considering the occupant density around exits. Physica A: Statistical Mechanics and its Applications, 2009, 388(9): 1921-1928.
[81] EXODUS INTRODUCTION, http://fseg.gre.ac.uk/exodus/.
[82] http://www.legion.com/.
[83] http://www.crowddynamics.com/.
[84] http://www.simwalk.com/.
[85] Kretz T, Grunebohm A, Kessel A, et al. Upstairs walking speed distributions on a long stairway. Safety Science, 2008, 46(1): 72-78.
[86] Lee J.Y.S, Lam W.H.K. Variation of walking speeds on a unidirectional walkway and on a bidirectional stairway. 2006, (1982): 122.
[87]中华人民共和国国家标准. GB10000-88.中国成年人人体尺寸, 1989.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |