非常规突发情况下大规模人群疏散的不确定性研究
|
摘要
近年来,在全世界范围内具有灾难性后果的非常规突发事件时有发生,大规模群体疏散问题日益得到公共安全领域的高度重视。迄今为止,对于大规模人群疏散的微观或宏观模型研究已有很多,有力推动了非常规突发事件应急处置科技领域的发展。但是,关于非常规突发事件下大规模人群疏散的不确定性尚没有得到充分的认识。为了揭示非常规突发事件下大规模人群在疏散过程中所受到的诸多不确定因素的影响和作用模式,我们采用理论分析和数学建模相结合的方法,以非常规突发灾害为背景,从突发灾害、外部疏散引导以及大规模疏散人群这三个层面,研究影响大规模人群疏散的随机不确定性,从效率和风险的角度,为突发灾害应急疏散提供理论和技术支持。
在非常规突发灾害层面,首先对非常规灾害与常规灾害的随机性分析与预测进行了一些探讨。以常规灾害中的城市火灾为例,建立了基于城市火灾幂律分布特征的重特大火灾事故发生概率预测模型,而非常规灾害在时间和空间尺度上均具有更多的不确定性和复杂性。因此,涉及到非常规灾害相关参数的设置和分析时,主要以人为假定的形式进行。在对灾害扩散模式及危害程度进行合理假设的基础上,运用动态网络流方法,建立了一个综合考虑疏散优先级和灾害扩散一般模式的多源多汇(MSMD)大规模疏散模型,并运用CCRP算法进行了疏散规划的求解及对比。进一步提出并建立了“路径通行效率风险”(RTE风险)的概念及其定量评估框架模型,基于该模型获得的各路段在灾害发生后不同时刻的ITE风险值,可有效反映出疏散路网在灾害环境下,综合考虑了效率和风险之后“适合通行”程度的动态变化。
在疏散引导层面,一是研究了大规模人群疏散时极易出现的恐慌情绪的传播特征及其对疏散的影响。运用系统动力学方法,构建了一个大规模人群疏散的定性仿真模型,通过对模型实施各种不同的输入方案,发现了有无疏散引导时由于灾害氛围加剧而出现的恐慌受控或失控状况的变化规律,以及灾害氛围下人群中恐慌情绪的蔓延更多地是受到占主导地位情绪的作用。该定性仿真模型很好地揭示了疏散系统中关键要素之间的相互作用关系以及影响疏散中恐慌情绪传播的不确定性因素,并且再现了疏散出口处“快即是慢”的典型现象。二是结合疏散引导对大规模疏散风险进行了量化研究。提出了大规模人群流动特征密度的概念,并基于连续人群流动理论和相关经验公式,推导获得了影响大规模人群流动的一系列特征密度。基于所获得的特征密度,结合排队理论,建立了一个无限人流过桥模型,并通过计算相关的系统效率指标,获得了不同密度人群在不同疏散引导策略下的疏散效率变化特征。基于理论分析和排队模拟所获得的五个特征密度,提出了一个在大规模疏散中判断疏散策略能否提高疏散效率的“人群密度风险轴”,以人群密度风险轴上的三个区间代表大规模疏散时针对疏散策略有效性而言的三种不同特征的人流,即有效流、临界流和无效流,并通过疏散风险的合理数值匹配,对这个人群密度风险轴进行了定量诠释。
在大规模疏散人群层面,引入并量化了人群生理心理因素对大规模疏散的影响,建立并修正了大规模人群疏散路径选择的随机Markov模型,并基于Markov过程的概率描述,以CO毒气瞬时泄漏扩散为事故背景,详细分析了疏散人群在多种因素,尤其是生理和心理因素影响下的疏散不确定性。通过分析清空时间在相关参数作用下的变化规律,发现在单因素变化情况下,滞留人数的对数与疏散时间之间存在分段线性特征；清空时间随着初始疏散人数的增加呈现对数线性增加的规律,随着节点最大容量的增加呈现线性减小的规律。此外,徒步疏散情况下人员心理恐慌对疏散速度的修正,整体上对于疏散结果的影响不大,而毒气影响下的人员生理风险对疏散结果影响显著,必须在涉及诸如毒气泄漏等突发事故的大规模人群应急疏散中予以重点关注。
With the worldwide occurrence of unconventional emergencies in recent years, the problem of large-scale crowd evacuation has increasingly attached great importance to the field of public security. To date, there have been a lot of researches on the micro or macro evacuation models, bringing a strong impetus to the development of the field of emergency evacuation. However, the uncertainties of large-scale evacuation under unconventional emergencies have not yet been fully elucidated. In order to reveal the impact of various uncertain factors and their mode of action in the large-scale evacuation process, we combine theoretical analysis and mathematical modeling together to study the uncertainties which affect both the efficiency and risk of large-scale crowd evacuation. Under the background of unconventional emergency, three levels, namely the disaster environment, the external evacuation (rescue) guidance and the massive evacuees are focused on respectively to achieve our goals, aiming to provide some theoretical and technical support for the emergency evacuation under sudden disasters.
In the level of disasters, firstly we studied the difference of unconventional and conventional disasters on their randomness analysis and forecast. The unban fire is used as an example of conventional disasters and a probability prediction model of urban fire occurrence is established based on the power-law distribution characteristics of urban fires, while the unconventional disasters have more uncertainty and complexity in both temporal and spatial scales. Therefore, referring to some parameters of unconventional disasters, we mainly take the form of assumptions. Based on some reasonable assumptions of disaster spread and damage, we applied the dynamic network flow method to establish a multi-source multi-destination (MSMD) large-scale evacuation model, in which the evacuation priority and the general pattern of disaster spread have been comprehensively considered. Using CCRP algorithm, the evacuation planning has been solved and compared. Based on these analyses, we further proposed a concept of "route travelling efficiency risk"(RTE risk) and established its quantitative assessment framework. The value of RTE risk calculated by the framework for each road link in different moment after the disaster occurs can effectively reflect the dynamic change of the "appropriateness for travelling" of the evacuation road network in a disaster environment considering both efficiency and risk.
In the level of rescue guidance, we firstly studied the propagation characteristics of panic emotion which is prone to appear in the large-scale evacuation. Applying the system dynamics method, we built a qualitative simulation model of large-scale evacuation. According to the implementation of a series of scenarios with different input, it is found that the severity of disaster is exponentially positive correlated with the panic spread without rescue guidance. On the contrary, with rescue guidance, the panic spread can be effectively controlled and the effectiveness of rescue guidance is influenced by the leading emotion in the whole crowds. The qualitative simulation model well reveals the interactions between key elements of the evacuation system and the uncertainties in the spread of panic, and reproduces a well-known phenomenon-"fast is slow"-in crowd evacuation.
Secondly, we conducted quantitative research on the risk of large-scale evacuation integrated with the evacuation guidance. We proposed a concept of "characteristic densities" of large-scale crowd flow and deduced a series of characteristic crowd densities that affect the large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested. Based on the characteristic crowd densities, the queuing theory has been applied to simulate the crowd movement under a situation of infinite crowd flow crossing bridge in lines. The moving characteristics of the crowd and the effects of typical crowd density on rescue strategies have been studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in large-scale evacuation with three regions in the risk axle, i.e. the effective flow, the critical zone and the non-effective flow. Finally, through some rational hypotheses for the value of evacuation risk, the risk axle of crowd density is illustrated quantitatively.
In the level of massive evacuees, we introduced and quantified the impact of physiological and psychological factors on the large-scale evacuation, based on which we established and modified a random Markov route selection model of the evacuees. Under a background of instantaneous leakage and diffusion of CO poison gas, the uncertainties of evacuation process and results according to the probabilistic description of Markov process has been detailed analyzed. It is found that when single factor changes, the logarithm of left population presents piecewise linear characteristics with the evacuation time, the clearance time will increase logarithmic linearly with the increase of initial population and decrease linearly with the increase of node capacity. Besides, the modification of evacuation speed according to the degree of psychological panic in the situation of hiking evacuation has little influence on the overall evacuation results, while the personnel physiological risk under the atmosphere of poison gas, for example, can obviously affect the evacuation results and must be paid enough attention to in the large-scale emergency evacuation.
在非常规突发灾害层面,首先对非常规灾害与常规灾害的随机性分析与预测进行了一些探讨。以常规灾害中的城市火灾为例,建立了基于城市火灾幂律分布特征的重特大火灾事故发生概率预测模型,而非常规灾害在时间和空间尺度上均具有更多的不确定性和复杂性。因此,涉及到非常规灾害相关参数的设置和分析时,主要以人为假定的形式进行。在对灾害扩散模式及危害程度进行合理假设的基础上,运用动态网络流方法,建立了一个综合考虑疏散优先级和灾害扩散一般模式的多源多汇(MSMD)大规模疏散模型,并运用CCRP算法进行了疏散规划的求解及对比。进一步提出并建立了“路径通行效率风险”(RTE风险)的概念及其定量评估框架模型,基于该模型获得的各路段在灾害发生后不同时刻的ITE风险值,可有效反映出疏散路网在灾害环境下,综合考虑了效率和风险之后“适合通行”程度的动态变化。
在疏散引导层面,一是研究了大规模人群疏散时极易出现的恐慌情绪的传播特征及其对疏散的影响。运用系统动力学方法,构建了一个大规模人群疏散的定性仿真模型,通过对模型实施各种不同的输入方案,发现了有无疏散引导时由于灾害氛围加剧而出现的恐慌受控或失控状况的变化规律,以及灾害氛围下人群中恐慌情绪的蔓延更多地是受到占主导地位情绪的作用。该定性仿真模型很好地揭示了疏散系统中关键要素之间的相互作用关系以及影响疏散中恐慌情绪传播的不确定性因素,并且再现了疏散出口处“快即是慢”的典型现象。二是结合疏散引导对大规模疏散风险进行了量化研究。提出了大规模人群流动特征密度的概念,并基于连续人群流动理论和相关经验公式,推导获得了影响大规模人群流动的一系列特征密度。基于所获得的特征密度,结合排队理论,建立了一个无限人流过桥模型,并通过计算相关的系统效率指标,获得了不同密度人群在不同疏散引导策略下的疏散效率变化特征。基于理论分析和排队模拟所获得的五个特征密度,提出了一个在大规模疏散中判断疏散策略能否提高疏散效率的“人群密度风险轴”,以人群密度风险轴上的三个区间代表大规模疏散时针对疏散策略有效性而言的三种不同特征的人流,即有效流、临界流和无效流,并通过疏散风险的合理数值匹配,对这个人群密度风险轴进行了定量诠释。
在大规模疏散人群层面,引入并量化了人群生理心理因素对大规模疏散的影响,建立并修正了大规模人群疏散路径选择的随机Markov模型,并基于Markov过程的概率描述,以CO毒气瞬时泄漏扩散为事故背景,详细分析了疏散人群在多种因素,尤其是生理和心理因素影响下的疏散不确定性。通过分析清空时间在相关参数作用下的变化规律,发现在单因素变化情况下,滞留人数的对数与疏散时间之间存在分段线性特征；清空时间随着初始疏散人数的增加呈现对数线性增加的规律,随着节点最大容量的增加呈现线性减小的规律。此外,徒步疏散情况下人员心理恐慌对疏散速度的修正,整体上对于疏散结果的影响不大,而毒气影响下的人员生理风险对疏散结果影响显著,必须在涉及诸如毒气泄漏等突发事故的大规模人群应急疏散中予以重点关注。
With the worldwide occurrence of unconventional emergencies in recent years, the problem of large-scale crowd evacuation has increasingly attached great importance to the field of public security. To date, there have been a lot of researches on the micro or macro evacuation models, bringing a strong impetus to the development of the field of emergency evacuation. However, the uncertainties of large-scale evacuation under unconventional emergencies have not yet been fully elucidated. In order to reveal the impact of various uncertain factors and their mode of action in the large-scale evacuation process, we combine theoretical analysis and mathematical modeling together to study the uncertainties which affect both the efficiency and risk of large-scale crowd evacuation. Under the background of unconventional emergency, three levels, namely the disaster environment, the external evacuation (rescue) guidance and the massive evacuees are focused on respectively to achieve our goals, aiming to provide some theoretical and technical support for the emergency evacuation under sudden disasters.
In the level of disasters, firstly we studied the difference of unconventional and conventional disasters on their randomness analysis and forecast. The unban fire is used as an example of conventional disasters and a probability prediction model of urban fire occurrence is established based on the power-law distribution characteristics of urban fires, while the unconventional disasters have more uncertainty and complexity in both temporal and spatial scales. Therefore, referring to some parameters of unconventional disasters, we mainly take the form of assumptions. Based on some reasonable assumptions of disaster spread and damage, we applied the dynamic network flow method to establish a multi-source multi-destination (MSMD) large-scale evacuation model, in which the evacuation priority and the general pattern of disaster spread have been comprehensively considered. Using CCRP algorithm, the evacuation planning has been solved and compared. Based on these analyses, we further proposed a concept of "route travelling efficiency risk"(RTE risk) and established its quantitative assessment framework. The value of RTE risk calculated by the framework for each road link in different moment after the disaster occurs can effectively reflect the dynamic change of the "appropriateness for travelling" of the evacuation road network in a disaster environment considering both efficiency and risk.
In the level of rescue guidance, we firstly studied the propagation characteristics of panic emotion which is prone to appear in the large-scale evacuation. Applying the system dynamics method, we built a qualitative simulation model of large-scale evacuation. According to the implementation of a series of scenarios with different input, it is found that the severity of disaster is exponentially positive correlated with the panic spread without rescue guidance. On the contrary, with rescue guidance, the panic spread can be effectively controlled and the effectiveness of rescue guidance is influenced by the leading emotion in the whole crowds. The qualitative simulation model well reveals the interactions between key elements of the evacuation system and the uncertainties in the spread of panic, and reproduces a well-known phenomenon-"fast is slow"-in crowd evacuation.
Secondly, we conducted quantitative research on the risk of large-scale evacuation integrated with the evacuation guidance. We proposed a concept of "characteristic densities" of large-scale crowd flow and deduced a series of characteristic crowd densities that affect the large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested. Based on the characteristic crowd densities, the queuing theory has been applied to simulate the crowd movement under a situation of infinite crowd flow crossing bridge in lines. The moving characteristics of the crowd and the effects of typical crowd density on rescue strategies have been studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in large-scale evacuation with three regions in the risk axle, i.e. the effective flow, the critical zone and the non-effective flow. Finally, through some rational hypotheses for the value of evacuation risk, the risk axle of crowd density is illustrated quantitatively.
In the level of massive evacuees, we introduced and quantified the impact of physiological and psychological factors on the large-scale evacuation, based on which we established and modified a random Markov route selection model of the evacuees. Under a background of instantaneous leakage and diffusion of CO poison gas, the uncertainties of evacuation process and results according to the probabilistic description of Markov process has been detailed analyzed. It is found that when single factor changes, the logarithm of left population presents piecewise linear characteristics with the evacuation time, the clearance time will increase logarithmic linearly with the increase of initial population and decrease linearly with the increase of node capacity. Besides, the modification of evacuation speed according to the degree of psychological panic in the situation of hiking evacuation has little influence on the overall evacuation results, while the personnel physiological risk under the atmosphere of poison gas, for example, can obviously affect the evacuation results and must be paid enough attention to in the large-scale emergency evacuation.
引文
[1]韩智勇,翁文国,张维,等.重大研究计划“非常规突发事件应急管理研究”的科学背景、目标与组织管理[J].中国科学基金,2009(4)：215-220.
[2]池宏,祁明亮,计雷,等.城市突发公共事件应急管理体系研究.中国安防产品信息,2005(4)：42-51.
[3]U.S. Federal Response Plan and Links,2000. http://www.disasters.org/emgold/frp.htm
[4]Federal Emergency Response Plan January 2011. http://www.publicsafety.gc.ca/prg/em/ferp-eng.aspx
[5]薛澜,张强,钟开斌.危机管理转型期中国面临的挑战[M].北京：清华大学出版社,2003.
[6]赵林度.基于危机资源管理的城市安全应急网络研究[J].东南大学学报(哲学社会科学版),2004,6(4)：48-51.
[7]杨静,陈建明,赵红.应急管理中的突发事件分类分级研究[J].管理评论,2005,17(4)：37-43.
[8]Gow G.A. Disaster mitigation and communications research in Canada:towards a responsive innovation agenda [J]. International Journal of Emergency Management,4(2):122-140.
[9]王旭明.突发公共卫生事件应急管理[M].北京：军事医学科学出版社,2004.
[10]lakovou E, Douligeris C. An information management of hurricane disasters[J]. International Journal of Emergency Management,2001,2(3/4):243-262.
[11]McEntire D A. Searching for a holistic paradigm and policy guide:A proposal for the future of emergency management[J]. International Journal of Emergency Management, 2003,1(3):298-308.
[12]Dymon UJ. An analysis of emergency map symbology. International Journal of Emergency Management[J],2003,1(3):227-237.
[13]Berlin G N. Mathematical analysis of emergency ambulance location [J]. Socio-Economic Planning Sciences,1974,8(6):323-328.
[14]Zografos K, Nathanail T, Michalopoulos P. Analytical Framework for Minimizing Freeway: Incident Response Time[J]. Journal of Transportation Engineering,1993,119(4),535-549.
[15]Rahman S, Smith D K. Use of location-allocation models in health service development planning in developing nations[J]. European Journal of Operational Research,2000,123(3): 437-452.
[16]ReVelle C S, Eiselt H A, Location analysis:A synthesis and survey[J]. European Journal of Operational Research,2005,165(1):1-19.
[17]Daskin M S. A Maximum Expected Covering Location Model:Formulation, Properties and Heuristic Solution[J]. Transportation Science1983,17(1):48-70.
[18]Bianchi G, Church R L. Ahybridfleet model for emergency medical service system design[J]. Social Science & Medicine.1988,26(1):163-171.
[19]Akella M R, Batta R, Delmelle E M, et al. Base station location and channel allocation in a cellular network with emergency coverage requirements[J]. European Journal of Operational Research.2005,164(2):301-323.
[20]Benveniste R. Solving the Combined Zoning and Location Problem for Several Emergency Units[J]. The Journal of the Operational Research Society,1985,36(5):433-450.
[21]Jamil M, Baveja A, Batta R. The stochastic queue center problem[J], Computers & Operations Research,1999,26(14):1423-1436.
[22]刘春林.应急管理中的紧急物资调度的模型与方法研究[D]:[博士].东南大学,2000.
[23]Barbarosoglu G, Ozdamar L, Cevik A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations [J]. European Journal of Operational Research,2002,140(1):118-133.
[24]陈超.突发事件应急资源调度模型与算法研究[D]：[硕士].南京航空航天大学,2010.[25]杨继君,吴启迪,程艳,等.面向非常规突发事件的应对方案序贯决策[J].同济大学学报(自然科学版),2010,38(4)：619-624.
[26]李孟军,陈森,李本先,等.考虑失效路段恢复的动态应急资源车辆调度模型[J].计算机应用研究,2011,28(11)：4125-4128.
[27]马向南.城市燃气埋地管道泄漏事故应急资源调度的研究[D]：[硕士].首都经济贸易大学,2010.
[28]Larson R C, Franck E A. Evaluating dispatching consequences of automatic vehicle location in emergency services[J]. Computers & Operations Research,1978,5(1):11-30.
[29]魏国强,杨永清.应急资源布局评估与调整策略研究[J].计算机工程与应用,2011,47(28)：215-218.
[30]吴丹.化学工业园区重大危险源分级及应急资源评估[D]:[硕士].东北大学,2005.
[31]姚杰,计雷,池宏.突发事件应急管理中的动态博弈分析[J].管理评论,2005,17(3)：46-50.
[32]赵林度,程婷.基于城市危机关键控制点的应急管理模式研究[J].安全与环境学报,2008,8(5)：163-167.
[33]姚杰,池宏,计雷.带有潜变量的结构方程模型在突发事件应急管理中的应用[J].中国管理科学,2005,13(2)：44-50.
[34]张岩.非常规突发事件态势演化和调控机制研究[D]：[博士].中国科学技术大学,2011
[35]吕浩,王超.重大突发事件的扩散机理研究[J].武汉理工大学学报(信息与管理工程版),2006(09)：7.10.
[36]高惠瑛,刘明琼,蔡宗文,等.基于WEBGIS的地震灾情快速评估系统研究[J],2010,25(S0)：314-317.
[37]刘敏,汪明.森林火灾灾情快速预判模型.中国安全科学学报[J],2011,21(5)：59-65.
[38]王军,许世远,石纯,等.基于多源遥感影像的台风灾情动态评估——研究进展[J].自然灾害学报,2008,17(3)：22-28.
[39]Biass S, Frischknecht C, Bonadonna C. A fast GIS-based risk assessment for tephra fallout: the example of Cotopaxi volcano, Ecuador-Part Ⅱ:vulnerability and risk assessmen[J]. Natural Hazards,2012,64(1):615-639.
[40]侯琳,杨帆等.重大交通突发事件中的态势评估研究[J].交通信息与安全,2009,27(149)：67-73.
[41]钟琪,戚巍.基于态势管理的区域弹性评估模型研究[J].经济管理,2010(8)：32-37.
[42]郭文强,高晓光.基于变参数动态贝叶斯网的态势评估.计算机测量与控制,2010,18(8)：1856-1859.
[43]王发智.基于贝叶斯网络的交通突发事件态势评估技术[M]：[硕士].大连理工大学,2006.
[44]聂高众.地震应急基础数据库建设[J].地震,2002(3)：105.112.
[45]肖兰喜.GIS在山东省震后早期应急系统中的应用[J].灾害学,2002(3)：3541.
[46]Zografos K G, Vasilakis G M, Giannouli I M. Methodological framework for developing decision support systems (DSS) for hazardous materials emergency response operations[J]. Journal of Hazardous Materials,2000,71(1-3):503-521.
[47]Hernandez J Z, Serrano J M. Knowledge-based models for emergency management systems[J]. Expert Systems with Applications,2001,20(2):173-186.
[48]Subramaniam C, Kerpedjiev S. Dissemination of weather information to emergency managers:a decision support tool. Engineering Management J]. IEEE Transactions Engineering Management,1998,45(2):106-114.
[49]Wybo J L. FMIS:A decision support system for forest fire prevention and fighting[J]. Engineering Management, IEEE Transactions Engineering Management,1998,45(2):127-131.
[50]Gipps P G, Marksjo B. A Micro-Simulation Model for Pedestrian Flows[J]. Mathematics and Computers in Simulation.1985,27:95-105.
[51]Helbing D, Buzna L, Johansson A, et al. Self-organized pedestrian crowd dynamics: experiments, simulations and design solutions[J].Transportation Science,2005,39,1-24.
[52]Bierlaire M, Antonini G, Weber M. Behavioral dynamics for pedestrians. In:Axhausen, K. (Ed.), Moving Through Nets:The Physical and Social Dimensions of Travel. Elsevier,2003.
[53]Thompson P A, Marchant E W. Testing and application of the computer model'SIMULEX'. Fire Safety Journal,1995,24(2):149-166.
[54]Galea E R. Simulating evacuation and circulation in planes, trains, buildings and ships using the EXODUS software. In:Schreckenberg M, Sharma SD (eds) Pedestrian and Evacuation Dynamics. Springer, Berlin,2002:203-225.
[55]Klupfel H, Konig M. Simulation of the Evacuation of a Football Stadium Using the CA Model PedGo[C]. In:Proceedings of the 5th International Conference on Traffic and Granular Flow, Delft, Netherlands,2003. Traffic and Granular Flow'03,2005,423-428.
[56]Hobeika A G, Jamei B. MASSVAC:A Model for Calculating Evacuation Times under Natural Disaster [C]. In:Proceedings of the Conference on Emergency Planning, Simulation Series, San Diego, California,24-25 January,1998,15(1):23-28.
[57]Sheffi Y, Mahmassani H, Powell W. NETVAC:A transportation Network Evacuation Model. Center for Transportaion Studies, MIT,1980.
[58]袁建平,方正,卢兆明,等.城市灾时大范围人员应急疏散探讨[J].自然灾害学报,2005,14(6)：116—119.
[59]Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic[J]. Nature, 2000,407:487-490.
[60]赵来军,程晶晶.基于突变理论的非常规突发事件下个体行为状态研究[J].中国安全科学学报,2011(12)：14—19.
[61]张子民,李琦.应急撤离建模研究的现状、问题与发展趋势[J].中国安全科学学报,2008,18(10)：120-126.
[1]Fruin J J. Designing for Pedestrians:A level of service concept [R]. Washington: Transportation Research Board Business Office,1971,355:1-15
[2]Daamen W, Bovy P L, Hoogendoorn S P. Passenger route choice concerning level changes in railway stations [C]. Transportation Research Board Annual Meeting,2005:1-18. Washington DC:National Academy Press.
[3]Pauls J. The movement of people in buildings and design dolutions for means of Egress [J]. Fire Technology,1984,20:27-47.
[4]Caesar S, Gay Jane P, Giovanni T. Self-organized queuing and scale-free behavior in real escape panic [J], PNAS,2003,100(21):11947-11952.
[5]Couzin I D, Franks N R. Self-organized lane formation and optimized traffic flow in army ants. In:Biological Sciences [C]. London:Royal Society of London,2003,139-146.
[6]Fruin J J. Pedestrian Planning and Design.Metropolitan Association of Urban Designers and Environmental Planners [M]. New York:Inc,1971.63-64
[7]Thompson P A, Marchant E W. Computer and fluid modelling of evacuation. Safety Science,1995,18:277-289.
[8]Johansson A. Data-driven modeling of pedestrian crowds[D]:[Ph.D.]. Technische Universitat, Dresden,2009.
[9]Helbing D, Buzna L, Johansson A, Werner T. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions[J]. Transportation Science,2005,39(1):1-24.
[10]马剑.相向行人流自组织行为机理研究[D]：[博士].中国科学技术大学,2010.
[11]房志明.考虑火灾影响的人员疏散过程模型与实验研究[D]:[博士].中国科学技术大学,2012.
[12]Bryan J. "Human Behavior and Fire", In Fire Protection Handbook,19th Edition, Vol.1,Cote, A. (Ed.), National Fire Protection Association, pp.4.3-4.32,2003.
[13]Mintz A. No-Adaptive Group Behavior[J]. Journal of Abnormal and Social Psychology,1951,46:150-159.
[14]Kelley H, Condry J, Dahlke A, et al. Collective Behavior in a Simulated Panic Situation[J]. Journal of Experimental Social Psychology,1965,1:20-54.
[15]Proulx G. As of Year 2000, What Do We Know about Occupant Behavior in Fire?[C]. The Technical Basis for Performance Based Fire Regulations, United Engineering Foundation Conference, San Diego, January 7-11, pp.127-129,2001.
[16]Shields T J, Proulx G. The Science of Human Behavior:Past Research Endeavour, Current Developments and Fashioning a Research Agenda[J]. Fire safety science,2000,6:95-113.
[17]Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic[J]. Nature, 2000,407(6803):487-490.
[18]李嘉华,王月明,雷劲松.火灾时人的避难心理行为及建筑疏散设计[J].消防科学与技术,2004,23(1)：39-41.
[19]胡清梅.大型公共建筑环境中人群拥挤机理及群集行为特性的研究[D]：[硕士].北京交通大学,2006.
[20]祁晓霞.大型商场安全疏散研究[D]:[硕士].重庆大学,2006.
[21]王理达.地铁车站人群疏散行为仿真研究[D]：[硕士].北京交通大学,2006.
[22]Henderson L F. The Statistics of Crowd Fluids[J]. Nature,1971,229(5284):381-383.
[23]Henderson L F. On the fluid mechanics of human crowd motion[J]. Transportation Research, 1974,8(6):509-515.
[24]Okazaki S, Matsushita S. A study of simulation model for pedestrian movement with evacuation and queuing. Engineering For Crowd Safety, RA Smith, JF Dickie, Editors Elsevier (1993), pp.271-280.
[25]Helbing D, Molnar P. Social force model for pedestrian dynamics[J]. Physical review E, 1995,51(5):4282-4286.
[26]Teknomo K. Microscopic pedestrian flow dharacteristics:development of an image processing data collection and simulation model [D]:[Ph.D.].Sendai:Tohoku University,2002.
[27]Lakoba T I, Kaup D J. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution [J]. Simulation,2005,81 (5):339-352.
[28]Cruz F R B, Smith J M G, Queirozb D C. Service and Capacity Allocation in M/G/c/c State-dependent Queueing Networks[J]. Computers & Operations Research,2005,32(6):1545-1563.
[29]Cruz F R B, Smith J M G. Approximate Analysis of M/G/c/c State-dependent Queueing Networks[J]. Computers & Operations Research,2007,34(8):2332-2344.
[30]Osorio C, Bierlaire M. An Analytic Finite Capacity Queueing Network Model Capturing the Propagation of Congestion and Blocking[J]. European Journal of Operational Research, 2009,(196):996-1007.
[31]Cao S H, Yuan Z Z, Zhao D. Queuing Mechanism of Passengers at Exit Stairs of Urban Rail Transit[J]. Journal of Jilin University:Engineering and Technology Edition,2009,39(6): 1463-1468.
[32]陈绍宽,刘爽,肖雄.基于M/G/c/c模型的地铁车站楼梯通道疏散能力瓶颈分析[J].铁道学报,2012,34(1)：7.12.
[33]Hamacher H W, Tufekci S. On the use of lexicographic min cost flows in evacuation modelling[J]. Naval Research Logistics,1987,34:487-503.
[34]Dunn C. E, Newton D. Optimal routes in GIS and emergency planning applications [J]. Area,1992,24(3):259-267.
[35]Choi W, Hamacher H, Tufecki S. Modeling of building evacuation problems by network flows with side constraints [J]. European Journal of Operational Research,1988,35:98-110.
[36]Yamada T. A network of approach to a city emergency evacuation planning [J]. International Journal of Systems Science,1996,27(10):931-936.
[37]Hamacher H W, Tjandra S A. Mathematical modeling of evacuation problems:State of the art [J]. Pedestrian and Evacuation Dynamics,2001:227-266.
[38]Lu Q, Huang Y, Shekhar S. Evacuation Planning:A Capacity Constrained Routing Approach [C]. Proceedings of the First NSF/NIJ Symposium on Intelligence and Security Informatics,2003:111-125.
[39]Lu Q, George B, Shekhar S. Capacity Constrained Routing Algorithms for Evacuation Planning:A Summary of Results [J]. Lecture Notes in Computer Science,2005,3633:291-307.
[40]Kim S, George B, Shekhar S. Evacuation Route Planning:Scalable Heuristics [C]. In: Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, Article No.20, ACM GIS,2007.
[41]Henderson L. The statistics of crowd fluids[J]. Nature,1971,229:381-383.
[42]Hughes R L. The flow of large crowds of pedestrians [J]. Mathematics and Computers in Simulation,2000,53:367-370.
[43]Hughes R L. A Continuum Theory for The Flow of Pedestrians [J]. Transportation Research Part B,2002,36:507-535.
[44]Lee R C, Hughes R L. Exploring trampling and crushing in a crowd [J]. Journal of Transportation Engineering,2005,131 (8):575-582.
[45]Domencich T, McFadden D. Urban Travel Demand:A Behavioural Analysis [M]. Amsterdam:North-Holland Publishing Co,1975.23-25.
[46]Coleman J, Katz E, Menzel H. The Diffusion of an Innovation Among Physicians [J]. Sociometry,1957,20(4):253-270.
[47]Kisko T M, Francis R L. EVACNET+:a computer program to determine optimal building evacuation plans. [J]. Fire Safety Journal,1985,9(2):11-20.
[48]Sheffi Y, Mahmassani H, Powell W. NETVAC:A transportation Network Evacuation Modelp[R]. Center for Transportaion Studies, MIT,1980.
[49]Hobeika A G, Jamei B. MASSVAC:A Model for Calculating Evacuation Times under Natural Disaster [C]. In:Proceedings of the Conference on Emergency Planning, Simulation Series, San Diego, California,24-25 January,1998,15(1):23-28.
[50]Sheffi Y, Mahamassani H. A transportation network evacuation model [J].Transportation Research Part A,1982,16(3):2530-2537.
[51]Tufekci S, Kisko T. Regional Evacuation Modeling System REMS:A Decision Support System for Emergency Area Evacuation [J]. Computers and Industrial Engineering.1991,21(1): 89-93.
[52]Owen M, Galea E R, Lawrence P J. Advanced occupant behavioural features of the building EXODUS evacuation model [C]. In:Proceedings of the fifth international symposium,1997, 795-806.
[53]Kostreva M M, Lancaster L C. A comparison of two methodologies in Hazard I fire egress analysis [J]. Fire Technology,1998,34(3):227-243.
[54]Lo S M, Fang Z. A Spatial-Grid Evacuation Model for Buildings[J]. Journal of Fire Sciences,2000,18(5):376-394.
[55]Lo S M, Fang Z, Lin P, et al. An Evacuation Model:the SGEM Package. Fire Safety Journal,2004,39(3):169-190.
[56]Song W G, Yu Y F, Wang B H, et al. Evacuation behaviors at exit in CA model with force essentials:A comparison with social force model[J]. Physica A,2006,371(2):658-666.
[57]Thompson P A, Marehant E W. A computer model for the evacuation of large building populations[J]. Fire Safety Journal,1995,24:131-148.
[58]Thompson P A, Marchant E W. Testing and application of the computer model'SIMULEX'[J]. Fire Safety Journal,1995,24:149-166.
[59]Pelechano N, Badler N I. Modeling crowd and trained leader behavior during building[J]. IEEE Computer Graphics and Applications,2006,26(6)80-86.
[60]Cova T J, Johnson J P. A network flow model for lane-based evacuation routing[J]. Transportation Research Part A,2003,37:579-604.
[61]Tuydes H, Ziliaskopoulos A. Network Re-Design to Optimize Evacuation Contraflow[R]. Technical Report 04-4715, Proc.83rd Ann. Meeting of the Transportation Research Board,2004.
[62]Yuan F, Han L D. Evacuation modelingand operations using dynamic traffic assignment and most assignment and most desirable destination approaches[J]. Transportation Research Board,No.05-2401,2005
[63]Liu Y, Zou N, Chang G L. An integrated emergency evacuation system for real-time operations-a case study of Ocean City, Maryland under hurricane attacks [J]. Intelligent Transportation Systems,2005:464-469.
[64]Chiu Y C, Zheng H. Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups:model formulation and solution[J]. Transportation Research Part E:Logistics and Transportation Review,2007,43(6):710-736.
[65]Tufekci S. An Integrated Emergency Management Decision Support System for Hurricane Emergencies[J]. Safety Science,1995,20(1):39-48.
[66]肖国清,温丽敏,陈宝智,等.毒气泄漏时的最佳疏散路径[J].东北大学学报,2001,22(6)：674-677.
[67]袁媛,汪定伟,蒋忠中,等.考虑路线复杂度的应急疏散双目标路径选择模型[J].运筹与管-,2008,17(5)：73-79.
[68]袁媛,汪定伟.灾害扩散实时影响下的应急疏散路径选择模型[J].系统仿真学报,2008,20(6)：1563—1566.
[69]高自友,宋一凡,四兵锋.城市交通连续平衡网络设计理论与方法[M].中国铁道出版社,2000.
[70]叶永.城市重特大事故大规模人群疏散决策研究[M]:[硕士].东南大学,2010.
[71]Yi W, Ozdamar L. A dynamic logistics coordination model for evacuation and support in disaster response activities [J]. European Journal of Operational Research,2007,179(3): 1177-1193.
[72]Fiedrich F, Gehbauer F, Rickers U. Optimized resource allocation for emergency response after earthquake disasters[J]. Safety Science,2000,35(1-3):41-57.
[73]Young C J. Stochastic scheduling problems for minimizing tardy jobs with application to emergency vehicle dispatching on unreliable road networks[D]:[Ph.D.]. State University of New York at Buffalo,2003.
[74]Fraser-Mitchell J N. An object-oriented simulation (CRISP11) for fire risk assesment [C]. In: Proceedings of the Fourth International Symposium of Fire Safety Science,1994,793-804.
[75]Fraser-Mitchell J N. Modelling Human Behaviour Within the Fire Risk Assessment Tool CRISP[J]. Fire and matetials,1999,23:349-355.
[76]卢春霞.人群流动的波动性分析[J].中国安全科学学报,2006,16(2)：30-34.
[77]胡志莹,叶明海.大型社会活动人群拥挤事故防范系统研究[J].灾害学,2003,21(1)：108—112.
[78]寇丽平.群体性挤踏事件原因分析与预防研究[J].中国人民公安大学学报(社会科学版),2005,4(4)：16-22.
[79]Church R L, Cova T J. Mapping evacuation risk on transportation networks using a spatial optimization model[J]. Transportation Research Part C,2000,8:321-336.
[80]Qiang L, Xiang C, Jin C, et al. An evacuation risk assessment model for emergency traffic with consideration of urban hazard installations[J]. Chinese Science Bullitin,2009, 54:1000-1006.
[1]Bak P, Tang C, Wiesenfeld K. Self-organized criticality:an explanation of 1/f noise[J]. Physical Review Letter,1987,59:381-384.
[2]Hwa T, Kardar M. Fractals and self-organized criticality in dissipative dynamics[J]. Physica D,1989,38(1-3):198-202.
[3]于群,郭剑波.中国电网停电事故统计与自组织临界性特征[J].电力系统自动化,2006,30(2)：16-21.
[4]姚冶,姚令侃.流行病传播自组织临界性模型适用性探讨[J].灾害学,2008,23(3)：20-23.
[5]高召宁,姚令侃,杨庆华,等.基于SOC的活断层系与地震活动性关系的探讨[J].地震研究,2009,32(2)：119.124.
[6]Drossel B, Schwabl F. Self-organized critical forest-fire model[J]. Physical Review Letter,1992,69(11)：1629-1632.
[7]宋卫国,汪秉宏,舒立福,等.自组织临界性与森林火灾系统的宏观规律性[J].中国科学院研究生院学报,2003,20(2)：205-211.
[8]宋卫国,王强,王健,等.葫芦岛市城市火灾分布的特点及其对城市火险分析的启示[J].科技导报,2005,23(8)：35-37.
[9]Akkaya D A, Yucemen M S. Estimation of earthquake hazard based on extremes of local integral random functions[J]. Engineering Geology,2000,58(1):53-66.
[10]Katz R W, Parlange M B, Naveau P. Statistics of extremes in hydrology[J]. Advances in water resources,2002,25(8-12):1287-1304.
[11]Majumdar S N, Krapivsky P L. Extreme value statistics and traveling fronts:various applications[J]. Physica A,2003,318(1-2):161-170.
[12]景国勋,王卫敏,郝天轩.基于灰色BP网络的火灾事故预测[J].工业安全与环保,2008,34(2)：61—63.
[13]周爱桃,景古勋,孙纲,等.改进的灰色预测模型在火灾事故预测中的应用[J].中国安全生产科学技术,2006。2(1)：62-64.
[14]景国勋,王卫敏,刘秋菊.信息扩散理论在河南省火灾风险评估中的应用[J].工业安全与环保,2008,34(5)：62-64.
[15]杨立中,江大白.中国火灾与社会经济因素的关系[J].中果工程科学,2003,5(2)：62.67.
[16]Stanzer K B, Stenzel S. Uncertainties in modeling hazardous gas releases for emergency response[J]. Meteorologische Zeitschrift,2011,20(1):19-27.
[17]Ford L R, Fulkerson D R. Flows in networks[M]. Princeton University Press, Princeton, NJ.1962.
[18]Ford L R, Fulkerson D R. Constructing maximal dynamic flows from static flows[J]. Operations Research,1958,6:419-433.
[19]Klinz B, Woeginger G T. Minimum cost dynamic flows:the series-parallel case[J]. Networks,1995,43:153-162
[20]Kotnyek B.An annotated overview of dynamic network flows[R]. RaPPort de recherche 4936, INRIA SoPhia AntiPolis.2003:1-28.
[21]殷志宏.线性规划与网络流[M].兰州：兰州大学出版社,2003.
[22]Cormen T, Leiserson C, Rivest R, et al. Introduction to Algorithms[M]. MIT Press,2nd edition,2001.
[23]许添本,吕奖慧.地震救灾最小风险路径选择模式之建立与应用[J].国立台湾大学“台大工程”学刊,2003,85：33—48.
[24]Arrow K J. Exposition of the theory of choice under uncertainty[J]. Synthese, 1966,16(3-4):253-269
[25]Roberts F S. Measurement theory with applications to decision making, utility, and the social science[M]. Cambridge University Press,1984.
[1]Law K H, Dauber K, Pan X S. Computational Modeling of Nonadaptive Crowd Behaviors for Egress Analysis[R]. CIFE Seed Project Report, Stanford University,2005.
[2]Raafat R M, Chater N, Frith C. Herding in humans[J]. Trends in Cognitive Sciences,2009,13: 420-428.
[3]Saloma C, Perez G. Herding in real escape panic[J]. Pedestrian and Evacuation Dynamics,2007,5:471-479.
[4]Zhou S P, Chen D, Cai W T, et al. Crowd Modeling and Simulation Technologies[J]. ACM Transactions on Modeling and Computer Simulation.2010:Article No.20.
[5]Xue Y, Wei Y F, Tian H H, et al. Opinion Formation and Propagation Induced by Pedestrian Flow[J]. Pedestrian and evacuation dynamics,2010,2:371-379.
[6]Illera C, Fink M, Hinneberg H, et al. NO PANIC:'Escape and Panic in Buildings'—Architectural Basic Research in the Context of Security and Safety Research[J]. Pedestrian and Evacuation Dynamics,2010,3:733-742.
[7]Bosta S A. Crowd Management Based on Scientific Research to Prevent Crowd Panic and Disasters[J]. Pedestrian and Evacuation Dynamics,2011,15:741-746.
[8]Was J. Experiments on Evacuation Dynamics for Different Classes of Situations[J]. Pedestrian and Evacuation Dynamics,2010,:225-232.
[9]Qi M L, Chi H, Zhao H, et al. The current situation and the prospect of research on public emergency management[J]. Management Review,18(2006):35-45.
[10]Colin M. Henein and Tony White. Macroscopic effects of microscopic forces between agents in crowd models[J]. Physica A,2007,373:694-712.
[11]Jehn K A, Mannix E A. The dynamic nature of conflict:A longitudinal study of intragroup conflict and group performance[J]. Academy of Management Journal,2001,44:238-251.
[12]Kuipers B J. Qualitative simulation[J]. Artificial Intelligence,1986,29:289-338.
[13]Berleant D, Kuipers B J. Qualitative and quantitative simulation:bridging the gap[J]. Artificial Intelligence,1997,95:215-255.
[14]Quarantelli E L. Disaster related social behavior:Summary of 50 years of research findings[R]. Preliminary Paper #280, Disaster Research Center, University of Delaware,1999.
[15]Quarantelli E L. Research findings on organizational behavior in disasters and their applicability in developing countries[R]. Preliminary Paper#107, Disaster Research Center, University of Delaware,1986.
[16]Pan X S. Computational Modeling of Human and Social Behaviors for Emergency Egress Analysis[R]. CIFE Technical Report #165, Stanford University,2006:40-49.
[17]Helbing D, Farkas I J, Molnar P, et al. Simulation of pedestrian crowds in normal and evacuation situations[J]. Pedestrian and Evacuation Dynamics,2002:21-58.
[18]Zhang Y, Shao C X. Modelling and analyzing dynamic system of people urgent evacuation. Computer engineering and application,2005,12:198-201.
[19]Levins R. The qualitative analysis of partially specified system[J]. Annals of the New York Academy of Sciences,1974,231:123-138.
[20]Shao C X, Zhang Y, Zhang J T, et al. Qualitative prediction on group evacuation via feedback analysis[J]. Journal of system simulation,2005,17(4):978-981.
[21]Wang Q P. Advanced system dynamics[M]. Beijing:Tsinghua University Press,1994.
[22]Dambacher J M, Li H W and Rossignol P A. Qualitative predictions in model ecosystems[J]. Ecological modeling,2003,161:79-93.
[23]Richardson G P, Pugh A I. Introduction to system dynamics modeling with DYNAMO[M]. Productivity Press Inc.,1981.
[24]Song W G, Yu Y F, Wang B H, et al. Evacuation behaviors at exit in CA model with force essentials:A comparison with social force model[J]. Physica A,2006,371:658-666.
[1]Rakesh S G, Barhal P K, Sasoh A, et al. Presence of shock wave like structures in pedestrian motion[C]. Shock Waves:Proceedings of the 24th International Symposium on Shock Waves, Beijing, China,2005:1297-1301.
[2]Smith R A. Density, velocity and flow relationships for closely packed crowds[J]. Safety Science,1995,18:321-327.
[3]Fang Z, Lo SM, Lu J A. On the relationship of crowd density and movement velocity[J]. Fire Safety Journal,2003,38:271-283.
[4]Zhen W, Mao L, Yuan Zh. Analysis of trample disaster and a case study-Mihong bridge fatality in China in 2004[J]. Safety Science,2008,46:1255-1270.
[5]Canetti E. Crowds and Power[M]. London:Phoenix Press,2000.
[6]Huang L, Wong S C, Zhang M P, et al. Revisiting Hughes'dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm [J]. Transportation Research Part B,2009,43:127-141.
[7]Xia Y H, Wong S C, Shu C W. Dynamic continuum pedestrian flow model with memory effect[J]. Physical Review E,2009,79(066113):1-8.
[8]Xia Y H, Wong S C, Zhang M P, et al. An efficient discontinuous Galerkin method on triangular meshes for a pedestrian flow model [J]. International Journal for Numerical Methods in Engineering,2008,76(3):337-350.
[9]Pan X H, Han C S, Dauber K, et al. Human and social behavior in computational modeling and analysis of egress[J]. Automation in Construction,2006,15(4):448-461.
[10]Henein C M, White T. Macroscopic effects of microscopic forces between agents in crowd models[J]. Physica A,2007,373:694-712.
[11]Burstedde C, Klauck K, Schadschneider A, et al. Simulation of pedestrian dynamics using a two-dimensional cellular automaton[J]. Physica A,2001,295(3-4):507-525.
[12]Dombroski M, Fischhoff B, Fischbeck P. Predicting emergency evacuation and sheltering behavior:A structured analytical approach[J]. Risk Analysis,2006,26(6):1675-1689.
[13]Ji X W, Weng W G, Fan W-Ch. Analyzing evacuation versus shelter-in-place strategies after a terrorist nuclear detonation[J]. Risk Analysis,2010,30(9):1315-1328.
[14]Ji X W, Weng W G, Fan W-Ch. Cellular automata-based systematic risk analysis approach for emergency response[J]. Risk Analysis,2008,28(5):1247-1260.
[15]Virkler M R, Elayadath S. Pedestrian speed-flow-density relationships. Transportation Research Record,1994,1438:51-58.
[16]Ran L J, Liu M. Effects of crowed people density, on crushing fatalities[J]. Journal of safety and environment,2007,7(4):135-138.
[17]Ando T, Ota H, Oki T. Forecasting the flow of people[J]. Railway Research Review,1988, 45:8-14.
[18]Togawa K. Study on Fire Escape based on the Observations of Multitude Currents[R]. Report No.4. Japan:Building Research Institute, Ministry of Construction,1955.
[19]Older S J. Pedestrians[R]. Department of Scientific and Industrial Research Laboratory, LN 275/SJO. Crowthome, England,1964.
[20]Polus A, Schafer J L, Ushpiz A. Pedestrian flow and level of service[J]. Journal of Transportation Engineering,1983,109(46):46-57.
[21]Predtechenskii V M, Milinski A I. Planning for Foot Traffic Flow in Buildings[M]. Moscow: Stroiizdat Publishers,1969.
[22]Lo S M, Fang Z, Lin P, Zhi G S. An evacuation model:The SGEM package[J]. Fire Safety Journal,2004, (39):169-190.
[23]Matthews L R. Cardiopulmonary Anatomy and Physiology[M]. Philadelphia:Lippincott Raven,1996.
[24]Thompson P A, Marchant E W. A computer model for the evacuation of large building populations[J]. Fire Safety Journal,1995, (24):131-148.
[25]Xu F, Wei D, Wei X. Analysis on the original data of crowd evacuation in public gathering places[J]. China Safety Science Journal,2008,18(4):137-145.
[26]Pheasant S, Haslegrave C M. Bodyspace:Anthropometry, Ergonomics, and the Design of Work (2nd Edition)[M]. USA:Taylor & Francis Inc.,2006.
[27]陆传赉.排队论(第二版)[M].北京：北京邮电大学出版社,2009.
[28]Medhi J. Stochastic models in queueing theory[M]. Amsterdam; Boston:Academic Press, 2003.
[29]Boardman N E. Cost-Benefit Analysis, Concepts and Practice (3rd edition)[M]. Upper Saddle River, NJ:Prentice Hall,2006.
[1]Hoogendoorn S P, Bovy P H L. Pedestrian route-choice and activity scheduling theory and models[J]. Transportation Research Part B,2004,38(2):169-190.
[2]Hoogendoom S P, Bovy P H L. Dynamic user-optimal assignment in continuous time andspace[J]. Transportation Research Part B,2004,38(7):571-592.
[3]Sime J D. An occupant response shelter escape time(ORSET)model[J]. Safety Science,2001,38(2):109-125.
[4]Shields T J, Boyce K E. A study of evacuation from large retail stores[J]. Fire Safety Journal, 2000,35:25-49.
[5]Ozel F. Time pressure and stress as a factor during emergency egress[J]. Safety Science, 2001,38(2):95-107.
[6]Kongsomsaksakul S, Yang C, Chen A. Shelter location-allocation model for flood evacuation planning[J]. Journal of the Eastern Asia Society for Transportation Studies,2005,6:4237-4252.
[7]Sheffi Y, Mahamassani H, Powell W B. A transportation network evacuation model[J]. Transportation Research Part A,1982:16A(3):209-218.
[8]Hazelton M L. Day-to-day variation in Markovian traffic assignment models[J]. Transportation Research Part B,2002,36:637-648.
[9]Ortuzar J, Willumsen L G. Modeling transport(2nd ed) [M]. New York:Wiley,1994.
[10]Carey M, McCartney M. An exit-flow model used in dynamic traffic assignment[J]. Computers & Operations Research,2004,3:1583-1602.
[11]Georgiadou P S, Papazoglou I A, Kiranoudis C T, et al. Modeling emergency evacuation for major hazard industrial sites[J]. Reliability Engineering & System Safety, 2007,92(10):1388-1402.
[12]熊大国.随机过程理论与应用[M].北京：国防工业出版社,1991.
[13]李剑峰.有毒重气扩散数值模拟与应急疏散关键技术研究[D]:[博士].南开大学,2008.
[14]Lan C J, Davis G A. Real-time estimation of turning movement proportions from partial counts on urban networks[J]. Transportation Research Part C,1999,7:305-327.
[15]杜建科.毒气泄漏过程及其危险区域分析[J].中国安全科学学报,2002,12(6)：55.59.
[16]Haber F. Funf Vortrange aus den jaren 1920-1923[M]. Berlin:Verlag von Julius Springer; 1924.
[17]Purser D A. Toxicity Assessment of Combustion Products. In:DiNenno PJ, Walton WD, eds. The SFPE Handbook of Fire Protection Engineering 3rd ed. Bethesda, MD:Society of Fire Protection Engineers; 2002.
[18]Chertkoff J M, Kushigian R H. Don't panic:The psychology of emergency egress and ingress[M]. Westport, Conn:Praeger,1999.
[19]肖国清,温丽敏,陈宝智,等.毒气泄漏时的最佳疏散路径[J].东北大学学报(自然科学版),2001,22(6)：613—616.
[20]王清.有毒有害气体防护技术[M].中国石化出版社,2007.
[2]池宏,祁明亮,计雷,等.城市突发公共事件应急管理体系研究.中国安防产品信息,2005(4)：42-51.
[3]U.S. Federal Response Plan and Links,2000. http://www.disasters.org/emgold/frp.htm
[4]Federal Emergency Response Plan January 2011. http://www.publicsafety.gc.ca/prg/em/ferp-eng.aspx
[5]薛澜,张强,钟开斌.危机管理转型期中国面临的挑战[M].北京：清华大学出版社,2003.
[6]赵林度.基于危机资源管理的城市安全应急网络研究[J].东南大学学报(哲学社会科学版),2004,6(4)：48-51.
[7]杨静,陈建明,赵红.应急管理中的突发事件分类分级研究[J].管理评论,2005,17(4)：37-43.
[8]Gow G.A. Disaster mitigation and communications research in Canada:towards a responsive innovation agenda [J]. International Journal of Emergency Management,4(2):122-140.
[9]王旭明.突发公共卫生事件应急管理[M].北京：军事医学科学出版社,2004.
[10]lakovou E, Douligeris C. An information management of hurricane disasters[J]. International Journal of Emergency Management,2001,2(3/4):243-262.
[11]McEntire D A. Searching for a holistic paradigm and policy guide:A proposal for the future of emergency management[J]. International Journal of Emergency Management, 2003,1(3):298-308.
[12]Dymon UJ. An analysis of emergency map symbology. International Journal of Emergency Management[J],2003,1(3):227-237.
[13]Berlin G N. Mathematical analysis of emergency ambulance location [J]. Socio-Economic Planning Sciences,1974,8(6):323-328.
[14]Zografos K, Nathanail T, Michalopoulos P. Analytical Framework for Minimizing Freeway: Incident Response Time[J]. Journal of Transportation Engineering,1993,119(4),535-549.
[15]Rahman S, Smith D K. Use of location-allocation models in health service development planning in developing nations[J]. European Journal of Operational Research,2000,123(3): 437-452.
[16]ReVelle C S, Eiselt H A, Location analysis:A synthesis and survey[J]. European Journal of Operational Research,2005,165(1):1-19.
[17]Daskin M S. A Maximum Expected Covering Location Model:Formulation, Properties and Heuristic Solution[J]. Transportation Science1983,17(1):48-70.
[18]Bianchi G, Church R L. Ahybridfleet model for emergency medical service system design[J]. Social Science & Medicine.1988,26(1):163-171.
[19]Akella M R, Batta R, Delmelle E M, et al. Base station location and channel allocation in a cellular network with emergency coverage requirements[J]. European Journal of Operational Research.2005,164(2):301-323.
[20]Benveniste R. Solving the Combined Zoning and Location Problem for Several Emergency Units[J]. The Journal of the Operational Research Society,1985,36(5):433-450.
[21]Jamil M, Baveja A, Batta R. The stochastic queue center problem[J], Computers & Operations Research,1999,26(14):1423-1436.
[22]刘春林.应急管理中的紧急物资调度的模型与方法研究[D]:[博士].东南大学,2000.
[23]Barbarosoglu G, Ozdamar L, Cevik A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations [J]. European Journal of Operational Research,2002,140(1):118-133.
[24]陈超.突发事件应急资源调度模型与算法研究[D]：[硕士].南京航空航天大学,2010.[25]杨继君,吴启迪,程艳,等.面向非常规突发事件的应对方案序贯决策[J].同济大学学报(自然科学版),2010,38(4)：619-624.
[26]李孟军,陈森,李本先,等.考虑失效路段恢复的动态应急资源车辆调度模型[J].计算机应用研究,2011,28(11)：4125-4128.
[27]马向南.城市燃气埋地管道泄漏事故应急资源调度的研究[D]：[硕士].首都经济贸易大学,2010.
[28]Larson R C, Franck E A. Evaluating dispatching consequences of automatic vehicle location in emergency services[J]. Computers & Operations Research,1978,5(1):11-30.
[29]魏国强,杨永清.应急资源布局评估与调整策略研究[J].计算机工程与应用,2011,47(28)：215-218.
[30]吴丹.化学工业园区重大危险源分级及应急资源评估[D]:[硕士].东北大学,2005.
[31]姚杰,计雷,池宏.突发事件应急管理中的动态博弈分析[J].管理评论,2005,17(3)：46-50.
[32]赵林度,程婷.基于城市危机关键控制点的应急管理模式研究[J].安全与环境学报,2008,8(5)：163-167.
[33]姚杰,池宏,计雷.带有潜变量的结构方程模型在突发事件应急管理中的应用[J].中国管理科学,2005,13(2)：44-50.
[34]张岩.非常规突发事件态势演化和调控机制研究[D]：[博士].中国科学技术大学,2011
[35]吕浩,王超.重大突发事件的扩散机理研究[J].武汉理工大学学报(信息与管理工程版),2006(09)：7.10.
[36]高惠瑛,刘明琼,蔡宗文,等.基于WEBGIS的地震灾情快速评估系统研究[J],2010,25(S0)：314-317.
[37]刘敏,汪明.森林火灾灾情快速预判模型.中国安全科学学报[J],2011,21(5)：59-65.
[38]王军,许世远,石纯,等.基于多源遥感影像的台风灾情动态评估——研究进展[J].自然灾害学报,2008,17(3)：22-28.
[39]Biass S, Frischknecht C, Bonadonna C. A fast GIS-based risk assessment for tephra fallout: the example of Cotopaxi volcano, Ecuador-Part Ⅱ:vulnerability and risk assessmen[J]. Natural Hazards,2012,64(1):615-639.
[40]侯琳,杨帆等.重大交通突发事件中的态势评估研究[J].交通信息与安全,2009,27(149)：67-73.
[41]钟琪,戚巍.基于态势管理的区域弹性评估模型研究[J].经济管理,2010(8)：32-37.
[42]郭文强,高晓光.基于变参数动态贝叶斯网的态势评估.计算机测量与控制,2010,18(8)：1856-1859.
[43]王发智.基于贝叶斯网络的交通突发事件态势评估技术[M]：[硕士].大连理工大学,2006.
[44]聂高众.地震应急基础数据库建设[J].地震,2002(3)：105.112.
[45]肖兰喜.GIS在山东省震后早期应急系统中的应用[J].灾害学,2002(3)：3541.
[46]Zografos K G, Vasilakis G M, Giannouli I M. Methodological framework for developing decision support systems (DSS) for hazardous materials emergency response operations[J]. Journal of Hazardous Materials,2000,71(1-3):503-521.
[47]Hernandez J Z, Serrano J M. Knowledge-based models for emergency management systems[J]. Expert Systems with Applications,2001,20(2):173-186.
[48]Subramaniam C, Kerpedjiev S. Dissemination of weather information to emergency managers:a decision support tool. Engineering Management J]. IEEE Transactions Engineering Management,1998,45(2):106-114.
[49]Wybo J L. FMIS:A decision support system for forest fire prevention and fighting[J]. Engineering Management, IEEE Transactions Engineering Management,1998,45(2):127-131.
[50]Gipps P G, Marksjo B. A Micro-Simulation Model for Pedestrian Flows[J]. Mathematics and Computers in Simulation.1985,27:95-105.
[51]Helbing D, Buzna L, Johansson A, et al. Self-organized pedestrian crowd dynamics: experiments, simulations and design solutions[J].Transportation Science,2005,39,1-24.
[52]Bierlaire M, Antonini G, Weber M. Behavioral dynamics for pedestrians. In:Axhausen, K. (Ed.), Moving Through Nets:The Physical and Social Dimensions of Travel. Elsevier,2003.
[53]Thompson P A, Marchant E W. Testing and application of the computer model'SIMULEX'. Fire Safety Journal,1995,24(2):149-166.
[54]Galea E R. Simulating evacuation and circulation in planes, trains, buildings and ships using the EXODUS software. In:Schreckenberg M, Sharma SD (eds) Pedestrian and Evacuation Dynamics. Springer, Berlin,2002:203-225.
[55]Klupfel H, Konig M. Simulation of the Evacuation of a Football Stadium Using the CA Model PedGo[C]. In:Proceedings of the 5th International Conference on Traffic and Granular Flow, Delft, Netherlands,2003. Traffic and Granular Flow'03,2005,423-428.
[56]Hobeika A G, Jamei B. MASSVAC:A Model for Calculating Evacuation Times under Natural Disaster [C]. In:Proceedings of the Conference on Emergency Planning, Simulation Series, San Diego, California,24-25 January,1998,15(1):23-28.
[57]Sheffi Y, Mahmassani H, Powell W. NETVAC:A transportation Network Evacuation Model. Center for Transportaion Studies, MIT,1980.
[58]袁建平,方正,卢兆明,等.城市灾时大范围人员应急疏散探讨[J].自然灾害学报,2005,14(6)：116—119.
[59]Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic[J]. Nature, 2000,407:487-490.
[60]赵来军,程晶晶.基于突变理论的非常规突发事件下个体行为状态研究[J].中国安全科学学报,2011(12)：14—19.
[61]张子民,李琦.应急撤离建模研究的现状、问题与发展趋势[J].中国安全科学学报,2008,18(10)：120-126.
[1]Fruin J J. Designing for Pedestrians:A level of service concept [R]. Washington: Transportation Research Board Business Office,1971,355:1-15
[2]Daamen W, Bovy P L, Hoogendoorn S P. Passenger route choice concerning level changes in railway stations [C]. Transportation Research Board Annual Meeting,2005:1-18. Washington DC:National Academy Press.
[3]Pauls J. The movement of people in buildings and design dolutions for means of Egress [J]. Fire Technology,1984,20:27-47.
[4]Caesar S, Gay Jane P, Giovanni T. Self-organized queuing and scale-free behavior in real escape panic [J], PNAS,2003,100(21):11947-11952.
[5]Couzin I D, Franks N R. Self-organized lane formation and optimized traffic flow in army ants. In:Biological Sciences [C]. London:Royal Society of London,2003,139-146.
[6]Fruin J J. Pedestrian Planning and Design.Metropolitan Association of Urban Designers and Environmental Planners [M]. New York:Inc,1971.63-64
[7]Thompson P A, Marchant E W. Computer and fluid modelling of evacuation. Safety Science,1995,18:277-289.
[8]Johansson A. Data-driven modeling of pedestrian crowds[D]:[Ph.D.]. Technische Universitat, Dresden,2009.
[9]Helbing D, Buzna L, Johansson A, Werner T. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions[J]. Transportation Science,2005,39(1):1-24.
[10]马剑.相向行人流自组织行为机理研究[D]：[博士].中国科学技术大学,2010.
[11]房志明.考虑火灾影响的人员疏散过程模型与实验研究[D]:[博士].中国科学技术大学,2012.
[12]Bryan J. "Human Behavior and Fire", In Fire Protection Handbook,19th Edition, Vol.1,Cote, A. (Ed.), National Fire Protection Association, pp.4.3-4.32,2003.
[13]Mintz A. No-Adaptive Group Behavior[J]. Journal of Abnormal and Social Psychology,1951,46:150-159.
[14]Kelley H, Condry J, Dahlke A, et al. Collective Behavior in a Simulated Panic Situation[J]. Journal of Experimental Social Psychology,1965,1:20-54.
[15]Proulx G. As of Year 2000, What Do We Know about Occupant Behavior in Fire?[C]. The Technical Basis for Performance Based Fire Regulations, United Engineering Foundation Conference, San Diego, January 7-11, pp.127-129,2001.
[16]Shields T J, Proulx G. The Science of Human Behavior:Past Research Endeavour, Current Developments and Fashioning a Research Agenda[J]. Fire safety science,2000,6:95-113.
[17]Helbing D, Farkas I, Vicsek T. Simulating dynamical features of escape panic[J]. Nature, 2000,407(6803):487-490.
[18]李嘉华,王月明,雷劲松.火灾时人的避难心理行为及建筑疏散设计[J].消防科学与技术,2004,23(1)：39-41.
[19]胡清梅.大型公共建筑环境中人群拥挤机理及群集行为特性的研究[D]：[硕士].北京交通大学,2006.
[20]祁晓霞.大型商场安全疏散研究[D]:[硕士].重庆大学,2006.
[21]王理达.地铁车站人群疏散行为仿真研究[D]：[硕士].北京交通大学,2006.
[22]Henderson L F. The Statistics of Crowd Fluids[J]. Nature,1971,229(5284):381-383.
[23]Henderson L F. On the fluid mechanics of human crowd motion[J]. Transportation Research, 1974,8(6):509-515.
[24]Okazaki S, Matsushita S. A study of simulation model for pedestrian movement with evacuation and queuing. Engineering For Crowd Safety, RA Smith, JF Dickie, Editors Elsevier (1993), pp.271-280.
[25]Helbing D, Molnar P. Social force model for pedestrian dynamics[J]. Physical review E, 1995,51(5):4282-4286.
[26]Teknomo K. Microscopic pedestrian flow dharacteristics:development of an image processing data collection and simulation model [D]:[Ph.D.].Sendai:Tohoku University,2002.
[27]Lakoba T I, Kaup D J. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution [J]. Simulation,2005,81 (5):339-352.
[28]Cruz F R B, Smith J M G, Queirozb D C. Service and Capacity Allocation in M/G/c/c State-dependent Queueing Networks[J]. Computers & Operations Research,2005,32(6):1545-1563.
[29]Cruz F R B, Smith J M G. Approximate Analysis of M/G/c/c State-dependent Queueing Networks[J]. Computers & Operations Research,2007,34(8):2332-2344.
[30]Osorio C, Bierlaire M. An Analytic Finite Capacity Queueing Network Model Capturing the Propagation of Congestion and Blocking[J]. European Journal of Operational Research, 2009,(196):996-1007.
[31]Cao S H, Yuan Z Z, Zhao D. Queuing Mechanism of Passengers at Exit Stairs of Urban Rail Transit[J]. Journal of Jilin University:Engineering and Technology Edition,2009,39(6): 1463-1468.
[32]陈绍宽,刘爽,肖雄.基于M/G/c/c模型的地铁车站楼梯通道疏散能力瓶颈分析[J].铁道学报,2012,34(1)：7.12.
[33]Hamacher H W, Tufekci S. On the use of lexicographic min cost flows in evacuation modelling[J]. Naval Research Logistics,1987,34:487-503.
[34]Dunn C. E, Newton D. Optimal routes in GIS and emergency planning applications [J]. Area,1992,24(3):259-267.
[35]Choi W, Hamacher H, Tufecki S. Modeling of building evacuation problems by network flows with side constraints [J]. European Journal of Operational Research,1988,35:98-110.
[36]Yamada T. A network of approach to a city emergency evacuation planning [J]. International Journal of Systems Science,1996,27(10):931-936.
[37]Hamacher H W, Tjandra S A. Mathematical modeling of evacuation problems:State of the art [J]. Pedestrian and Evacuation Dynamics,2001:227-266.
[38]Lu Q, Huang Y, Shekhar S. Evacuation Planning:A Capacity Constrained Routing Approach [C]. Proceedings of the First NSF/NIJ Symposium on Intelligence and Security Informatics,2003:111-125.
[39]Lu Q, George B, Shekhar S. Capacity Constrained Routing Algorithms for Evacuation Planning:A Summary of Results [J]. Lecture Notes in Computer Science,2005,3633:291-307.
[40]Kim S, George B, Shekhar S. Evacuation Route Planning:Scalable Heuristics [C]. In: Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, Article No.20, ACM GIS,2007.
[41]Henderson L. The statistics of crowd fluids[J]. Nature,1971,229:381-383.
[42]Hughes R L. The flow of large crowds of pedestrians [J]. Mathematics and Computers in Simulation,2000,53:367-370.
[43]Hughes R L. A Continuum Theory for The Flow of Pedestrians [J]. Transportation Research Part B,2002,36:507-535.
[44]Lee R C, Hughes R L. Exploring trampling and crushing in a crowd [J]. Journal of Transportation Engineering,2005,131 (8):575-582.
[45]Domencich T, McFadden D. Urban Travel Demand:A Behavioural Analysis [M]. Amsterdam:North-Holland Publishing Co,1975.23-25.
[46]Coleman J, Katz E, Menzel H. The Diffusion of an Innovation Among Physicians [J]. Sociometry,1957,20(4):253-270.
[47]Kisko T M, Francis R L. EVACNET+:a computer program to determine optimal building evacuation plans. [J]. Fire Safety Journal,1985,9(2):11-20.
[48]Sheffi Y, Mahmassani H, Powell W. NETVAC:A transportation Network Evacuation Modelp[R]. Center for Transportaion Studies, MIT,1980.
[49]Hobeika A G, Jamei B. MASSVAC:A Model for Calculating Evacuation Times under Natural Disaster [C]. In:Proceedings of the Conference on Emergency Planning, Simulation Series, San Diego, California,24-25 January,1998,15(1):23-28.
[50]Sheffi Y, Mahamassani H. A transportation network evacuation model [J].Transportation Research Part A,1982,16(3):2530-2537.
[51]Tufekci S, Kisko T. Regional Evacuation Modeling System REMS:A Decision Support System for Emergency Area Evacuation [J]. Computers and Industrial Engineering.1991,21(1): 89-93.
[52]Owen M, Galea E R, Lawrence P J. Advanced occupant behavioural features of the building EXODUS evacuation model [C]. In:Proceedings of the fifth international symposium,1997, 795-806.
[53]Kostreva M M, Lancaster L C. A comparison of two methodologies in Hazard I fire egress analysis [J]. Fire Technology,1998,34(3):227-243.
[54]Lo S M, Fang Z. A Spatial-Grid Evacuation Model for Buildings[J]. Journal of Fire Sciences,2000,18(5):376-394.
[55]Lo S M, Fang Z, Lin P, et al. An Evacuation Model:the SGEM Package. Fire Safety Journal,2004,39(3):169-190.
[56]Song W G, Yu Y F, Wang B H, et al. Evacuation behaviors at exit in CA model with force essentials:A comparison with social force model[J]. Physica A,2006,371(2):658-666.
[57]Thompson P A, Marehant E W. A computer model for the evacuation of large building populations[J]. Fire Safety Journal,1995,24:131-148.
[58]Thompson P A, Marchant E W. Testing and application of the computer model'SIMULEX'[J]. Fire Safety Journal,1995,24:149-166.
[59]Pelechano N, Badler N I. Modeling crowd and trained leader behavior during building[J]. IEEE Computer Graphics and Applications,2006,26(6)80-86.
[60]Cova T J, Johnson J P. A network flow model for lane-based evacuation routing[J]. Transportation Research Part A,2003,37:579-604.
[61]Tuydes H, Ziliaskopoulos A. Network Re-Design to Optimize Evacuation Contraflow[R]. Technical Report 04-4715, Proc.83rd Ann. Meeting of the Transportation Research Board,2004.
[62]Yuan F, Han L D. Evacuation modelingand operations using dynamic traffic assignment and most assignment and most desirable destination approaches[J]. Transportation Research Board,No.05-2401,2005
[63]Liu Y, Zou N, Chang G L. An integrated emergency evacuation system for real-time operations-a case study of Ocean City, Maryland under hurricane attacks [J]. Intelligent Transportation Systems,2005:464-469.
[64]Chiu Y C, Zheng H. Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups:model formulation and solution[J]. Transportation Research Part E:Logistics and Transportation Review,2007,43(6):710-736.
[65]Tufekci S. An Integrated Emergency Management Decision Support System for Hurricane Emergencies[J]. Safety Science,1995,20(1):39-48.
[66]肖国清,温丽敏,陈宝智,等.毒气泄漏时的最佳疏散路径[J].东北大学学报,2001,22(6)：674-677.
[67]袁媛,汪定伟,蒋忠中,等.考虑路线复杂度的应急疏散双目标路径选择模型[J].运筹与管-,2008,17(5)：73-79.
[68]袁媛,汪定伟.灾害扩散实时影响下的应急疏散路径选择模型[J].系统仿真学报,2008,20(6)：1563—1566.
[69]高自友,宋一凡,四兵锋.城市交通连续平衡网络设计理论与方法[M].中国铁道出版社,2000.
[70]叶永.城市重特大事故大规模人群疏散决策研究[M]:[硕士].东南大学,2010.
[71]Yi W, Ozdamar L. A dynamic logistics coordination model for evacuation and support in disaster response activities [J]. European Journal of Operational Research,2007,179(3): 1177-1193.
[72]Fiedrich F, Gehbauer F, Rickers U. Optimized resource allocation for emergency response after earthquake disasters[J]. Safety Science,2000,35(1-3):41-57.
[73]Young C J. Stochastic scheduling problems for minimizing tardy jobs with application to emergency vehicle dispatching on unreliable road networks[D]:[Ph.D.]. State University of New York at Buffalo,2003.
[74]Fraser-Mitchell J N. An object-oriented simulation (CRISP11) for fire risk assesment [C]. In: Proceedings of the Fourth International Symposium of Fire Safety Science,1994,793-804.
[75]Fraser-Mitchell J N. Modelling Human Behaviour Within the Fire Risk Assessment Tool CRISP[J]. Fire and matetials,1999,23:349-355.
[76]卢春霞.人群流动的波动性分析[J].中国安全科学学报,2006,16(2)：30-34.
[77]胡志莹,叶明海.大型社会活动人群拥挤事故防范系统研究[J].灾害学,2003,21(1)：108—112.
[78]寇丽平.群体性挤踏事件原因分析与预防研究[J].中国人民公安大学学报(社会科学版),2005,4(4)：16-22.
[79]Church R L, Cova T J. Mapping evacuation risk on transportation networks using a spatial optimization model[J]. Transportation Research Part C,2000,8:321-336.
[80]Qiang L, Xiang C, Jin C, et al. An evacuation risk assessment model for emergency traffic with consideration of urban hazard installations[J]. Chinese Science Bullitin,2009, 54:1000-1006.
[1]Bak P, Tang C, Wiesenfeld K. Self-organized criticality:an explanation of 1/f noise[J]. Physical Review Letter,1987,59:381-384.
[2]Hwa T, Kardar M. Fractals and self-organized criticality in dissipative dynamics[J]. Physica D,1989,38(1-3):198-202.
[3]于群,郭剑波.中国电网停电事故统计与自组织临界性特征[J].电力系统自动化,2006,30(2)：16-21.
[4]姚冶,姚令侃.流行病传播自组织临界性模型适用性探讨[J].灾害学,2008,23(3)：20-23.
[5]高召宁,姚令侃,杨庆华,等.基于SOC的活断层系与地震活动性关系的探讨[J].地震研究,2009,32(2)：119.124.
[6]Drossel B, Schwabl F. Self-organized critical forest-fire model[J]. Physical Review Letter,1992,69(11)：1629-1632.
[7]宋卫国,汪秉宏,舒立福,等.自组织临界性与森林火灾系统的宏观规律性[J].中国科学院研究生院学报,2003,20(2)：205-211.
[8]宋卫国,王强,王健,等.葫芦岛市城市火灾分布的特点及其对城市火险分析的启示[J].科技导报,2005,23(8)：35-37.
[9]Akkaya D A, Yucemen M S. Estimation of earthquake hazard based on extremes of local integral random functions[J]. Engineering Geology,2000,58(1):53-66.
[10]Katz R W, Parlange M B, Naveau P. Statistics of extremes in hydrology[J]. Advances in water resources,2002,25(8-12):1287-1304.
[11]Majumdar S N, Krapivsky P L. Extreme value statistics and traveling fronts:various applications[J]. Physica A,2003,318(1-2):161-170.
[12]景国勋,王卫敏,郝天轩.基于灰色BP网络的火灾事故预测[J].工业安全与环保,2008,34(2)：61—63.
[13]周爱桃,景古勋,孙纲,等.改进的灰色预测模型在火灾事故预测中的应用[J].中国安全生产科学技术,2006。2(1)：62-64.
[14]景国勋,王卫敏,刘秋菊.信息扩散理论在河南省火灾风险评估中的应用[J].工业安全与环保,2008,34(5)：62-64.
[15]杨立中,江大白.中国火灾与社会经济因素的关系[J].中果工程科学,2003,5(2)：62.67.
[16]Stanzer K B, Stenzel S. Uncertainties in modeling hazardous gas releases for emergency response[J]. Meteorologische Zeitschrift,2011,20(1):19-27.
[17]Ford L R, Fulkerson D R. Flows in networks[M]. Princeton University Press, Princeton, NJ.1962.
[18]Ford L R, Fulkerson D R. Constructing maximal dynamic flows from static flows[J]. Operations Research,1958,6:419-433.
[19]Klinz B, Woeginger G T. Minimum cost dynamic flows:the series-parallel case[J]. Networks,1995,43:153-162
[20]Kotnyek B.An annotated overview of dynamic network flows[R]. RaPPort de recherche 4936, INRIA SoPhia AntiPolis.2003:1-28.
[21]殷志宏.线性规划与网络流[M].兰州：兰州大学出版社,2003.
[22]Cormen T, Leiserson C, Rivest R, et al. Introduction to Algorithms[M]. MIT Press,2nd edition,2001.
[23]许添本,吕奖慧.地震救灾最小风险路径选择模式之建立与应用[J].国立台湾大学“台大工程”学刊,2003,85：33—48.
[24]Arrow K J. Exposition of the theory of choice under uncertainty[J]. Synthese, 1966,16(3-4):253-269
[25]Roberts F S. Measurement theory with applications to decision making, utility, and the social science[M]. Cambridge University Press,1984.
[1]Law K H, Dauber K, Pan X S. Computational Modeling of Nonadaptive Crowd Behaviors for Egress Analysis[R]. CIFE Seed Project Report, Stanford University,2005.
[2]Raafat R M, Chater N, Frith C. Herding in humans[J]. Trends in Cognitive Sciences,2009,13: 420-428.
[3]Saloma C, Perez G. Herding in real escape panic[J]. Pedestrian and Evacuation Dynamics,2007,5:471-479.
[4]Zhou S P, Chen D, Cai W T, et al. Crowd Modeling and Simulation Technologies[J]. ACM Transactions on Modeling and Computer Simulation.2010:Article No.20.
[5]Xue Y, Wei Y F, Tian H H, et al. Opinion Formation and Propagation Induced by Pedestrian Flow[J]. Pedestrian and evacuation dynamics,2010,2:371-379.
[6]Illera C, Fink M, Hinneberg H, et al. NO PANIC:'Escape and Panic in Buildings'—Architectural Basic Research in the Context of Security and Safety Research[J]. Pedestrian and Evacuation Dynamics,2010,3:733-742.
[7]Bosta S A. Crowd Management Based on Scientific Research to Prevent Crowd Panic and Disasters[J]. Pedestrian and Evacuation Dynamics,2011,15:741-746.
[8]Was J. Experiments on Evacuation Dynamics for Different Classes of Situations[J]. Pedestrian and Evacuation Dynamics,2010,:225-232.
[9]Qi M L, Chi H, Zhao H, et al. The current situation and the prospect of research on public emergency management[J]. Management Review,18(2006):35-45.
[10]Colin M. Henein and Tony White. Macroscopic effects of microscopic forces between agents in crowd models[J]. Physica A,2007,373:694-712.
[11]Jehn K A, Mannix E A. The dynamic nature of conflict:A longitudinal study of intragroup conflict and group performance[J]. Academy of Management Journal,2001,44:238-251.
[12]Kuipers B J. Qualitative simulation[J]. Artificial Intelligence,1986,29:289-338.
[13]Berleant D, Kuipers B J. Qualitative and quantitative simulation:bridging the gap[J]. Artificial Intelligence,1997,95:215-255.
[14]Quarantelli E L. Disaster related social behavior:Summary of 50 years of research findings[R]. Preliminary Paper #280, Disaster Research Center, University of Delaware,1999.
[15]Quarantelli E L. Research findings on organizational behavior in disasters and their applicability in developing countries[R]. Preliminary Paper#107, Disaster Research Center, University of Delaware,1986.
[16]Pan X S. Computational Modeling of Human and Social Behaviors for Emergency Egress Analysis[R]. CIFE Technical Report #165, Stanford University,2006:40-49.
[17]Helbing D, Farkas I J, Molnar P, et al. Simulation of pedestrian crowds in normal and evacuation situations[J]. Pedestrian and Evacuation Dynamics,2002:21-58.
[18]Zhang Y, Shao C X. Modelling and analyzing dynamic system of people urgent evacuation. Computer engineering and application,2005,12:198-201.
[19]Levins R. The qualitative analysis of partially specified system[J]. Annals of the New York Academy of Sciences,1974,231:123-138.
[20]Shao C X, Zhang Y, Zhang J T, et al. Qualitative prediction on group evacuation via feedback analysis[J]. Journal of system simulation,2005,17(4):978-981.
[21]Wang Q P. Advanced system dynamics[M]. Beijing:Tsinghua University Press,1994.
[22]Dambacher J M, Li H W and Rossignol P A. Qualitative predictions in model ecosystems[J]. Ecological modeling,2003,161:79-93.
[23]Richardson G P, Pugh A I. Introduction to system dynamics modeling with DYNAMO[M]. Productivity Press Inc.,1981.
[24]Song W G, Yu Y F, Wang B H, et al. Evacuation behaviors at exit in CA model with force essentials:A comparison with social force model[J]. Physica A,2006,371:658-666.
[1]Rakesh S G, Barhal P K, Sasoh A, et al. Presence of shock wave like structures in pedestrian motion[C]. Shock Waves:Proceedings of the 24th International Symposium on Shock Waves, Beijing, China,2005:1297-1301.
[2]Smith R A. Density, velocity and flow relationships for closely packed crowds[J]. Safety Science,1995,18:321-327.
[3]Fang Z, Lo SM, Lu J A. On the relationship of crowd density and movement velocity[J]. Fire Safety Journal,2003,38:271-283.
[4]Zhen W, Mao L, Yuan Zh. Analysis of trample disaster and a case study-Mihong bridge fatality in China in 2004[J]. Safety Science,2008,46:1255-1270.
[5]Canetti E. Crowds and Power[M]. London:Phoenix Press,2000.
[6]Huang L, Wong S C, Zhang M P, et al. Revisiting Hughes'dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm [J]. Transportation Research Part B,2009,43:127-141.
[7]Xia Y H, Wong S C, Shu C W. Dynamic continuum pedestrian flow model with memory effect[J]. Physical Review E,2009,79(066113):1-8.
[8]Xia Y H, Wong S C, Zhang M P, et al. An efficient discontinuous Galerkin method on triangular meshes for a pedestrian flow model [J]. International Journal for Numerical Methods in Engineering,2008,76(3):337-350.
[9]Pan X H, Han C S, Dauber K, et al. Human and social behavior in computational modeling and analysis of egress[J]. Automation in Construction,2006,15(4):448-461.
[10]Henein C M, White T. Macroscopic effects of microscopic forces between agents in crowd models[J]. Physica A,2007,373:694-712.
[11]Burstedde C, Klauck K, Schadschneider A, et al. Simulation of pedestrian dynamics using a two-dimensional cellular automaton[J]. Physica A,2001,295(3-4):507-525.
[12]Dombroski M, Fischhoff B, Fischbeck P. Predicting emergency evacuation and sheltering behavior:A structured analytical approach[J]. Risk Analysis,2006,26(6):1675-1689.
[13]Ji X W, Weng W G, Fan W-Ch. Analyzing evacuation versus shelter-in-place strategies after a terrorist nuclear detonation[J]. Risk Analysis,2010,30(9):1315-1328.
[14]Ji X W, Weng W G, Fan W-Ch. Cellular automata-based systematic risk analysis approach for emergency response[J]. Risk Analysis,2008,28(5):1247-1260.
[15]Virkler M R, Elayadath S. Pedestrian speed-flow-density relationships. Transportation Research Record,1994,1438:51-58.
[16]Ran L J, Liu M. Effects of crowed people density, on crushing fatalities[J]. Journal of safety and environment,2007,7(4):135-138.
[17]Ando T, Ota H, Oki T. Forecasting the flow of people[J]. Railway Research Review,1988, 45:8-14.
[18]Togawa K. Study on Fire Escape based on the Observations of Multitude Currents[R]. Report No.4. Japan:Building Research Institute, Ministry of Construction,1955.
[19]Older S J. Pedestrians[R]. Department of Scientific and Industrial Research Laboratory, LN 275/SJO. Crowthome, England,1964.
[20]Polus A, Schafer J L, Ushpiz A. Pedestrian flow and level of service[J]. Journal of Transportation Engineering,1983,109(46):46-57.
[21]Predtechenskii V M, Milinski A I. Planning for Foot Traffic Flow in Buildings[M]. Moscow: Stroiizdat Publishers,1969.
[22]Lo S M, Fang Z, Lin P, Zhi G S. An evacuation model:The SGEM package[J]. Fire Safety Journal,2004, (39):169-190.
[23]Matthews L R. Cardiopulmonary Anatomy and Physiology[M]. Philadelphia:Lippincott Raven,1996.
[24]Thompson P A, Marchant E W. A computer model for the evacuation of large building populations[J]. Fire Safety Journal,1995, (24):131-148.
[25]Xu F, Wei D, Wei X. Analysis on the original data of crowd evacuation in public gathering places[J]. China Safety Science Journal,2008,18(4):137-145.
[26]Pheasant S, Haslegrave C M. Bodyspace:Anthropometry, Ergonomics, and the Design of Work (2nd Edition)[M]. USA:Taylor & Francis Inc.,2006.
[27]陆传赉.排队论(第二版)[M].北京：北京邮电大学出版社,2009.
[28]Medhi J. Stochastic models in queueing theory[M]. Amsterdam; Boston:Academic Press, 2003.
[29]Boardman N E. Cost-Benefit Analysis, Concepts and Practice (3rd edition)[M]. Upper Saddle River, NJ:Prentice Hall,2006.
[1]Hoogendoorn S P, Bovy P H L. Pedestrian route-choice and activity scheduling theory and models[J]. Transportation Research Part B,2004,38(2):169-190.
[2]Hoogendoom S P, Bovy P H L. Dynamic user-optimal assignment in continuous time andspace[J]. Transportation Research Part B,2004,38(7):571-592.
[3]Sime J D. An occupant response shelter escape time(ORSET)model[J]. Safety Science,2001,38(2):109-125.
[4]Shields T J, Boyce K E. A study of evacuation from large retail stores[J]. Fire Safety Journal, 2000,35:25-49.
[5]Ozel F. Time pressure and stress as a factor during emergency egress[J]. Safety Science, 2001,38(2):95-107.
[6]Kongsomsaksakul S, Yang C, Chen A. Shelter location-allocation model for flood evacuation planning[J]. Journal of the Eastern Asia Society for Transportation Studies,2005,6:4237-4252.
[7]Sheffi Y, Mahamassani H, Powell W B. A transportation network evacuation model[J]. Transportation Research Part A,1982:16A(3):209-218.
[8]Hazelton M L. Day-to-day variation in Markovian traffic assignment models[J]. Transportation Research Part B,2002,36:637-648.
[9]Ortuzar J, Willumsen L G. Modeling transport(2nd ed) [M]. New York:Wiley,1994.
[10]Carey M, McCartney M. An exit-flow model used in dynamic traffic assignment[J]. Computers & Operations Research,2004,3:1583-1602.
[11]Georgiadou P S, Papazoglou I A, Kiranoudis C T, et al. Modeling emergency evacuation for major hazard industrial sites[J]. Reliability Engineering & System Safety, 2007,92(10):1388-1402.
[12]熊大国.随机过程理论与应用[M].北京：国防工业出版社,1991.
[13]李剑峰.有毒重气扩散数值模拟与应急疏散关键技术研究[D]:[博士].南开大学,2008.
[14]Lan C J, Davis G A. Real-time estimation of turning movement proportions from partial counts on urban networks[J]. Transportation Research Part C,1999,7:305-327.
[15]杜建科.毒气泄漏过程及其危险区域分析[J].中国安全科学学报,2002,12(6)：55.59.
[16]Haber F. Funf Vortrange aus den jaren 1920-1923[M]. Berlin:Verlag von Julius Springer; 1924.
[17]Purser D A. Toxicity Assessment of Combustion Products. In:DiNenno PJ, Walton WD, eds. The SFPE Handbook of Fire Protection Engineering 3rd ed. Bethesda, MD:Society of Fire Protection Engineers; 2002.
[18]Chertkoff J M, Kushigian R H. Don't panic:The psychology of emergency egress and ingress[M]. Westport, Conn:Praeger,1999.
[19]肖国清,温丽敏,陈宝智,等.毒气泄漏时的最佳疏散路径[J].东北大学学报(自然科学版),2001,22(6)：613—616.
[20]王清.有毒有害气体防护技术[M].中国石化出版社,2007.