突发事件下应急交通疏散研究
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摘要
近年来，国内外灾害性突发事件时有发生，既有自然灾害，如地震、台风、泥石流、洪水等，也有人为灾害，如恐怖袭击、化学泄漏等，这些灾害对人民的生命安全造成了极大威胁，国内外政府和相关研究机构纷纷研究、出台和完善灾害性突发事件的预警、应急管理机制。其中，应急交通疏散作为规避或减轻灾害性事件危害，避免受到二次伤害的重要手段，作为以人为本的具体体现，成为应急管理的重要部分。本文以国内外现有的应急交通疏散研究为基础，从系统性、动态性和针对性着手，结合灾害性突发事件的特征，对应急交通疏散策略进行了深入研究。
本文通过总结近年来国内外具有代表性的一些突发灾害性事件造成的实际危害，阐明了突发灾害性事件的不确定性和危害性对我国应急管理提出的挑战，强调了本研究具有理论意义和现实意义。本文按照应急疏散流程，对国内外各疏散阶段的相关研究进行了综述，从宏观、中观和微观三个层次对现有应急疏散模型进行了分类，突出了应急交通疏散研究的重点和难点。总结了疏散应急疏散的时间、疏散对象规模、疏散方式和疏散区域四大要素对应急疏散的影响，给出了最短路径应急疏散模型、最短时间应急疏散模型、最小风险应急疏散模型，并对仿真方法进行了分析。在对三个基本模型的优缺点进行分析的基础上，考虑突发事件的分类、分级以及相关交通需求特征，将应急疏散划分为点对点、点对面和面对面三大类，提出了分类制定疏散策略的整体研究思路。
制定点对点应急疏散策略时，和通常仅考虑将人群最快疏散至目的地不同，本文还重点考虑了疏散者在疏散过程中可能受到灾害危害的风险问题，指出风险的存在会严重影响原应急疏散方案的可行性和有效性，最安全的将人群疏散至目的地才是根本目标，并针对该问题提出了既考虑应急疏散路径最短，又考虑疏散过程最安全的多目标点对点疏散模型。通过对两个目标赋予权重将模型转变为单目标后，模型求解基于K-最短路思想展开，采用多目标粒子群算法设计了算法，给出了既考虑疏散路径又考虑疏散安全性的疏散策略。通过对现有应急疏散算例的道路网络上增加各路段的风险值，设计并求解了算例，体现了更符合实际情况的应急疏散策略的有效性。
由于在飓风灾害中，各疏散点的人群只要离开飓风危害的区域即可，因此本文以飓风疏散为例研究了点对面应急疏散策略问题。考虑到飓风在危害范围、危害大小上具有明显的随时间变化的特征，构建了动态风险下的飓风应急疏散模型，反映了应急疏散在时间和安全性两方面的要求。在用时间参数方程形式刻画飓风移动路径和危害大小的基础上，给出了道路网络上个点的风险度量方法，以单位时间内风险降幅最大为原则制定了应急疏散策略，最后设计了具有一定规模的算例，对理想道路网络和存在交通瓶颈的道路网络分别进行了仿真，验证了策略的可行性。
面对面疏散在疏散群体、疏散区域以及疏散环境上都极为复杂，为确保人群能及时疏散，鉴于物流中的多式联运可以提高货物的运输效率，本文提出了基于多式联疏的模式进行面对面应急疏散的思路。同时，针对面对面疏散在基础数据上的庞大需求，本文强调并实际演示了地理信息系统在道路网络获取、安全区域识别、疏散对象分布等方面的强大功能。综合运用GIS中的道路信息和人口信息，采用锚定法对疏散困难区域进行了识别。以典型的面对面疏散——洪水灾害的疏散为例，设计了多种交通方式的系统协调应用和无缝衔接方法，并以城市洪灾的疏散为例，验证了多式联疏在面对面应急疏散中的可行性和优越性。
本文从突发事件的实际特征出发，按分类研究的思路，结合应急疏散过程中的多目标、动态风险、多式联疏等特点，分别以一般道路车辆疏散、飓风疏散和洪水疏散为例，构建了点对点、点对面和面对面应急疏散模型，并给出了仿真思路和求解算法，获得了一些考虑因素更全面、疏散过程更动态、疏散方法更系统的应急疏散策略，为相关机构应对突发事件，制定应急疏散方案提供了参考，同时也为相关研究的推进提供了新的思路。
In recent years, the disastrous incidents to be reported at home and abroad,ranging from natural disasters, such as earthquakes, typhoons, landslides, floods, etc,and also man-made disasters, such as terrorist attacks, chemical spills, etc, whichposes a great threat to people's lives。Relevant research institutions and governmentresearch, introduce, and improve mechanisms for early warning and emergencymanagement of disaster emergency. Among them, as an important means to avoidharm or mitigate catastrophic events and secondary victimization and represented anembodiment of the people-oriented, the emergency traffic evacuation became animportant part of emergency management.
Based on existing emergency traffic evacuation studies at home and abroad, thisarticle combining characteristics of disastrous incidents, research on emergencytraffic evacuation strategy deeply from the systemic, dynamic and targeted view. Bysummarizing recent representative of actual harm caused by some unexpected disasterevents, this article clarified the uncertainties and hazards of sudden-onset disasterschallenge to emergency management, emphasized the theoretical significance andpractical significance of this study. In accordance with emergency evacuationprocedures, this article overview of the study on evacuation phase both at home andabroad, and given the classification of existing emergency evacuation model s from themacro-levels, meso-levels and micro-levels, highlighted the emphases and difficultiesof emergency traffic evacuation studies. This paper also summarizes the time ofevacuation emergency evacuation, evacuation, evacuation and evacuation of regionalscale four elements effect on emergency evacuation, emergency evacuation modelgives the shortest path, minimum time model for emergency evacuation emergencyevacuation model, minimal risk, and conducted an analysis of simulation method.Analysis of the advantages and disadvantages of the three basic models based onconsidering emergency sorting, grading and related traffic demand characteristics,emergency evacuation are classified as point to point, point to three main types of faceto face and on the other side, proposed a classification research ideas developevacuation strategy as a whole.
Different from the usual way that people evacuated to destinations only considerthe fastest way, this paper also focus on the evacuation in the evacuation process maybe the risk of disaster damage, pointed out that the risks will seriously affect the feasibility and effectiveness of the emergency evacuation plan, most p eople evacuatedto the destination is the fundamental goal of safety, and emergency evacuation for theissues raised both considered the shortest path, also taking into account the safeevacuation process of multi-objective model of evacuation from point to point whendevelop the point to point emergency evacuation point strategy. By given weight totwo goals after the model into a single destination, model based on the k-shortestpaths, using multi-objective particle swarm optimization algorithm to design thealgorithm gives both consider evacuation route and consider evacuation safety ofevacuation strategies. Emergency evacuation is available through the various sectionsof the road network increases the value-at-risk, design and solution of the examplereflects the more realistic emergency evacuation policy effectiveness.
Due to the hurricane disaster, evacuate crowds only need leaving the area ofhurricane damage, so this article has a case study of hurricane evacuation study pointopposite the emergency evacuation policy problems. Taking into account the scope ofhurricane damage, has an obvious hazard size characteristics change over time,constructed under the dynamic risk Hurricane emergency evacuation models, reflectsthe emergency evacuation and security requirements. In with time parameter equationform portrays Hurricane mobile path and against size of based Shang, to our has roadnetwork last points of risk measure method, to units time within risk fall maximum forprinciples developed has emergency evacuation strategy, last design has must scale ofis cases, to ideal road network and exists traffic bottlenecks of road networkrespectively for has simulation, validation has strategy of feasibility.
Area-to-area evacuation groups, areas and environment are extremely complex,and given multimodal logistics can improve the efficiency of cargo transport, toensure that the population can be evacuated references of intermodal logistics concept,put forward the idea of multi-modal emergency evacuation sparse. The same time, thehuge demand for area-to-area evacuation on the basis of data, the paper emphasizesthe practical demonstration of the powerful features of GIS in road network access,the security zone identification, evacuation object distribution, and the combination ofanchor method evacuation difficult areas identification. Typical area-to-areaevacuation-evacuation of flood disasters, for example, the design of the system andcoordination of multiple transportation modes applications and seaml ess connection tothe city's flood evacuation, for example, verify that the multi-modal sparse inarea-to-area emergency evacuation the feasibility and superiority.
This article departure from the actual characteristics of the emergency classification research ideas, as much as possible the use of quantitative modeling andsimulation visualization method of emergency evacuation strategy, get someconsideration in a more comprehensive and more dynamic evacuation, moresystematic method of emergency evacuation strategies to respond to emergencies tothe relevant agencies to develop emergency evacuation plan to provide a reference,but also for the advancement of research provides a new way of thinking.
本文通过总结近年来国内外具有代表性的一些突发灾害性事件造成的实际危害，阐明了突发灾害性事件的不确定性和危害性对我国应急管理提出的挑战，强调了本研究具有理论意义和现实意义。本文按照应急疏散流程，对国内外各疏散阶段的相关研究进行了综述，从宏观、中观和微观三个层次对现有应急疏散模型进行了分类，突出了应急交通疏散研究的重点和难点。总结了疏散应急疏散的时间、疏散对象规模、疏散方式和疏散区域四大要素对应急疏散的影响，给出了最短路径应急疏散模型、最短时间应急疏散模型、最小风险应急疏散模型，并对仿真方法进行了分析。在对三个基本模型的优缺点进行分析的基础上，考虑突发事件的分类、分级以及相关交通需求特征，将应急疏散划分为点对点、点对面和面对面三大类，提出了分类制定疏散策略的整体研究思路。
制定点对点应急疏散策略时，和通常仅考虑将人群最快疏散至目的地不同，本文还重点考虑了疏散者在疏散过程中可能受到灾害危害的风险问题，指出风险的存在会严重影响原应急疏散方案的可行性和有效性，最安全的将人群疏散至目的地才是根本目标，并针对该问题提出了既考虑应急疏散路径最短，又考虑疏散过程最安全的多目标点对点疏散模型。通过对两个目标赋予权重将模型转变为单目标后，模型求解基于K-最短路思想展开，采用多目标粒子群算法设计了算法，给出了既考虑疏散路径又考虑疏散安全性的疏散策略。通过对现有应急疏散算例的道路网络上增加各路段的风险值，设计并求解了算例，体现了更符合实际情况的应急疏散策略的有效性。
由于在飓风灾害中，各疏散点的人群只要离开飓风危害的区域即可，因此本文以飓风疏散为例研究了点对面应急疏散策略问题。考虑到飓风在危害范围、危害大小上具有明显的随时间变化的特征，构建了动态风险下的飓风应急疏散模型，反映了应急疏散在时间和安全性两方面的要求。在用时间参数方程形式刻画飓风移动路径和危害大小的基础上，给出了道路网络上个点的风险度量方法，以单位时间内风险降幅最大为原则制定了应急疏散策略，最后设计了具有一定规模的算例，对理想道路网络和存在交通瓶颈的道路网络分别进行了仿真，验证了策略的可行性。
面对面疏散在疏散群体、疏散区域以及疏散环境上都极为复杂，为确保人群能及时疏散，鉴于物流中的多式联运可以提高货物的运输效率，本文提出了基于多式联疏的模式进行面对面应急疏散的思路。同时，针对面对面疏散在基础数据上的庞大需求，本文强调并实际演示了地理信息系统在道路网络获取、安全区域识别、疏散对象分布等方面的强大功能。综合运用GIS中的道路信息和人口信息，采用锚定法对疏散困难区域进行了识别。以典型的面对面疏散——洪水灾害的疏散为例，设计了多种交通方式的系统协调应用和无缝衔接方法，并以城市洪灾的疏散为例，验证了多式联疏在面对面应急疏散中的可行性和优越性。
本文从突发事件的实际特征出发，按分类研究的思路，结合应急疏散过程中的多目标、动态风险、多式联疏等特点，分别以一般道路车辆疏散、飓风疏散和洪水疏散为例，构建了点对点、点对面和面对面应急疏散模型，并给出了仿真思路和求解算法，获得了一些考虑因素更全面、疏散过程更动态、疏散方法更系统的应急疏散策略，为相关机构应对突发事件，制定应急疏散方案提供了参考，同时也为相关研究的推进提供了新的思路。
In recent years, the disastrous incidents to be reported at home and abroad,ranging from natural disasters, such as earthquakes, typhoons, landslides, floods, etc,and also man-made disasters, such as terrorist attacks, chemical spills, etc, whichposes a great threat to people's lives。Relevant research institutions and governmentresearch, introduce, and improve mechanisms for early warning and emergencymanagement of disaster emergency. Among them, as an important means to avoidharm or mitigate catastrophic events and secondary victimization and represented anembodiment of the people-oriented, the emergency traffic evacuation became animportant part of emergency management.
Based on existing emergency traffic evacuation studies at home and abroad, thisarticle combining characteristics of disastrous incidents, research on emergencytraffic evacuation strategy deeply from the systemic, dynamic and targeted view. Bysummarizing recent representative of actual harm caused by some unexpected disasterevents, this article clarified the uncertainties and hazards of sudden-onset disasterschallenge to emergency management, emphasized the theoretical significance andpractical significance of this study. In accordance with emergency evacuationprocedures, this article overview of the study on evacuation phase both at home andabroad, and given the classification of existing emergency evacuation model s from themacro-levels, meso-levels and micro-levels, highlighted the emphases and difficultiesof emergency traffic evacuation studies. This paper also summarizes the time ofevacuation emergency evacuation, evacuation, evacuation and evacuation of regionalscale four elements effect on emergency evacuation, emergency evacuation modelgives the shortest path, minimum time model for emergency evacuation emergencyevacuation model, minimal risk, and conducted an analysis of simulation method.Analysis of the advantages and disadvantages of the three basic models based onconsidering emergency sorting, grading and related traffic demand characteristics,emergency evacuation are classified as point to point, point to three main types of faceto face and on the other side, proposed a classification research ideas developevacuation strategy as a whole.
Different from the usual way that people evacuated to destinations only considerthe fastest way, this paper also focus on the evacuation in the evacuation process maybe the risk of disaster damage, pointed out that the risks will seriously affect the feasibility and effectiveness of the emergency evacuation plan, most p eople evacuatedto the destination is the fundamental goal of safety, and emergency evacuation for theissues raised both considered the shortest path, also taking into account the safeevacuation process of multi-objective model of evacuation from point to point whendevelop the point to point emergency evacuation point strategy. By given weight totwo goals after the model into a single destination, model based on the k-shortestpaths, using multi-objective particle swarm optimization algorithm to design thealgorithm gives both consider evacuation route and consider evacuation safety ofevacuation strategies. Emergency evacuation is available through the various sectionsof the road network increases the value-at-risk, design and solution of the examplereflects the more realistic emergency evacuation policy effectiveness.
Due to the hurricane disaster, evacuate crowds only need leaving the area ofhurricane damage, so this article has a case study of hurricane evacuation study pointopposite the emergency evacuation policy problems. Taking into account the scope ofhurricane damage, has an obvious hazard size characteristics change over time,constructed under the dynamic risk Hurricane emergency evacuation models, reflectsthe emergency evacuation and security requirements. In with time parameter equationform portrays Hurricane mobile path and against size of based Shang, to our has roadnetwork last points of risk measure method, to units time within risk fall maximum forprinciples developed has emergency evacuation strategy, last design has must scale ofis cases, to ideal road network and exists traffic bottlenecks of road networkrespectively for has simulation, validation has strategy of feasibility.
Area-to-area evacuation groups, areas and environment are extremely complex,and given multimodal logistics can improve the efficiency of cargo transport, toensure that the population can be evacuated references of intermodal logistics concept,put forward the idea of multi-modal emergency evacuation sparse. The same time, thehuge demand for area-to-area evacuation on the basis of data, the paper emphasizesthe practical demonstration of the powerful features of GIS in road network access,the security zone identification, evacuation object distribution, and the combination ofanchor method evacuation difficult areas identification. Typical area-to-areaevacuation-evacuation of flood disasters, for example, the design of the system andcoordination of multiple transportation modes applications and seaml ess connection tothe city's flood evacuation, for example, verify that the multi-modal sparse inarea-to-area emergency evacuation the feasibility and superiority.
This article departure from the actual characteristics of the emergency classification research ideas, as much as possible the use of quantitative modeling andsimulation visualization method of emergency evacuation strategy, get someconsideration in a more comprehensive and more dynamic evacuation, moresystematic method of emergency evacuation strategies to respond to emergencies tothe relevant agencies to develop emergency evacuation plan to provide a reference,but also for the advancement of research provides a new way of thinking.
引文
[1] Pidd M, De Silva F N, Eglese R W. A simulation model for emergency evacuation.European Journal of Operational Research,1996,90(3):413-419.
[2] Perry R W, Lindell M K. Preparedness for emergency response: guidelines for theemergency planning process. Disasters,2003,27(4):336-350.
[3]安实,崔建勋,王健.国外道路交通应急区域疏散研究综述.交通运输系统工程与信息,2008,8(6):38-45.
[4]刘小明,胡红.应急交通疏散研究现状与展望.交通运输工程学报,2008,8(3):108-115.
[5] Southworth F. Regional evacuation modeling: a state-of-the-art review.ORNL/TM-11740, Oak Ridge National Laboratory, Oak Ridge, Tennessee,1990,2008,8(3):108-115.
[6] Zelinsky W, Kosiński L A. The emergency evacuation of cities: A cross-nationalhistorical and geographical study. Rowman和Littlefield Pub Inc,1991.
[7] McLoughlin D. A framework for integrated emergency management. PublicAdministration Review,1985,45:165-172.
[8] Stepanov A, Smith JMG. Multi-objective evacuation routing in transportationnetworks. European Journal of Operational Research,2009,198(2):435-446.
[9] Lindell M K. Assessing emergency preparedness in support of hazardous facilityrisk analyses: Application to siting a US hazardous waste incinerator. Journal ofHazardous Materials,1995,40(3):297-319.
[10] Cova T J, Johnson J P. Microsimulation of neighborhood evacuations in theurban-wildland interface. Environment and Planning A,2002,34(12):2211-2230.
[11] Church R L, Sexton R. Modeling small area evacuation: Can existingtransportation infrastructure impede public safety. Final Rep,2002,.
[12] Lindell M K. EMBLEM2: An empirically based large scale evacuation timeestimate model. Transportation Research Part A: Policy and Practice,2008,42(1):140-154.
[13] Longley Paul, Goodchild Michael, Maguire David, Rhind David. GIS inemergency management. New York: John Wiley和Sons,1999.
[14] Gunes A E, Kovel J P. Using GIS in emergency management operations. Journal ofUrban Planning and Development,2000,126(3):136-149.
[15] Chen T, Yuan H, Yang R, Chen J. Integration of GIS and Computational Models forEmergency Management. Proceedings of the2008International Conference onIntelligent Computation Technology and Automation,2008.
[16] Sauvagnargues-Lesage S, Ayral P A. Using GIS for emergency management: a casestudy during the2002and2003flooding in south-east France. InternationalJournal of Emergency Management,2007,4(4):682-703.
[17]刘敏,卢兆明,袁国杰.基于GIS系统的灾时大范围应急疏散研究.第十届中国科协年会,2008.
[18] Stern E, Sinuany-Stern Z. A behavioural-based simulation model for urbanevacuation. Papers in Regional Science,1989,66(1):87-103.
[19] Sorensen J H, Shumpert B L, Vogt B M. Planning for protective action decisionmaking: evacuate or shelter-in-place. Journal of hazardous materials,2004,109(1-3):1-11.
[20] Lindell M K, Lu J C, Prater C S. Household decision making and evacuation inresponse to Hurricane Lili. Natural Hazards Review,2005,6:171.
[21] Cohn P J, Carroll M S, Kumagai Y. Evacuation behavior during wildfires: Resultsof three case studies. Western Journal of Applied Forestry,2006,21(1):39-48.
[22] Lindell M K, Prater C S. Critical Behavioral Assumptions in Evacuation TimeEstimate Analysis for Private Vehicles: Examples from Hurricane Research andPlanning. Journal of Urban Planning and Development,2007,133(1):18-29.
[23] Meit M, Briggs T, Kennedy A. Urban to rural evacuation: planning for ruralpopulation surge. Research Report, Bethesda, MD: The Walsh Center for RuralHealth Analysis,2008.
[24] Santos G, Aguirre B E. A critical review of emergency evacuation simulationmodels. Proceeding of Conference "Building Occupant Movement During FireEmergencies",2004.
[25]张江华,刘治平,朱道立.多源点突发灾害事故应急疏散模型与算法.管理科学学报,2009,(3):111-118.
[26] Yuan F, Han L D, Chin S M, Hwang H. Proposed Framework for SimultaneousOptimization of Evacuation Traffic Destination and Route Assignment.Transportation Research Record: Journal of the Transportation Research Board,2006,1964(1):50-58.
[27] Kerbache L, Smith JMG. Multi-objective routing within large scale facilities usingopen finite queueing networks. European Journal of Operational Research,2000,121(1):105-123.
[28] Smith JMG, Cruz FRB. The buffer allocation problem for general finite bufferqueueing networks. IIE Transactions,2005,37(4):343-365.
[29] Cruz FRB, MacGregor Smith J, Medeiros R O. An M/G/C/C state-dependentnetwork simulation model. Computers和Operations Research,2005,32(4):919-941.
[30] Talebi K, Smith JMG. Stochastic network evacuation models. Computers和Operations Research,1985,12(6):559-577.
[31] Floudas Christodoulos A, Pardalos Panos M. Encyclopedia of Optimization.Springer,2008.
[32] Tanaka K, Nagatani T, Hanaura H. Traffic mixing in deterministic two-lane modelof Hurricane evacuation. Physica A: Statistical Mechanics and its Applications,2007,380:490-502.
[33]胡红,刘小明,魏恒,等.基于路口和路段人口综合控制的应急疏散交通控制算法.交通运输工程学报,2009,9(3):108-111.
[34] Kim S, George B, Shekhar S. Evacuation route planning: scalable heuristics.Proceedings of the15th annual ACM international s ymposium on Advances ingeographic information systems,2007.
[35] Yusoff M, Ariffin J, Mohamed A. Optimization approaches for macroscopicemergency evacuation planning: A survey. Information Technology,2008. ITSim2008. International Symposium on,2008.
[36] Yamada T. A network flow approach to a city emergency evacuation planning.International Journal of Systems Science,1996,27(10):931-936.
[37] Campos VBG, Da Silva PAL, Netto P O B. Evacuation transportation planning: amethod of identifying optimal independent routes. Surcharov L J. Proceedings ofUrban Transport V: Urban Transport and the Environment for the21st Century,2000,:555-564.
[38] Wolshon B, Lambert L. Reversible lane systems: Synthesis of practice. Journal ofTransportation Engineering,2006,132(12):933-944.
[39] Mahmassani H S, Jayakrishnan R, Herman R. Network traffic flow theory:Microscopic simulation experiments on supercomputers. Transportation ResearchPart A: General,1990,24(2):149-162.
[40] Rathi A K, Santiago A J. The new NETSIM simulation model. Traffic Engineeringand Control,1990,31(5):317.
[41] Lammel Gregor, Dominik Grether, Kai Nagel. The representation andimplementation of time-dependent inundation in large-scale microscopicevacuation simulations. Transportation Research Part C: Emerging Technologies,2010,18(1):84-98.
[42] Sheffi Y, Mahmassani H, Powell W B. A transportation network evacuation model.Transportation Research Part A: General,1982,16(3):209-218.
[43] McLean M A, Moeller M P, Desrosiers A E. CLEAR: a model for the calculation ofevacuation-time estimates in Emergency Planning Zones. Conference on modelingand simulation on microcomputers,1983.
[44] Cova T J, Johnson J P. A network flow model for lane-based evacuation routing.Transportation research part A: Policy and Practice,2003,37(7):579-604.
[45] Barcello J, Grau R. PACKSIM: An experience in using traffic simulation in ademand responsive traffic control system. XIII World Conference on OperationsResearch,1993.
[46] Moeller M P, Urbanik T, Desrosiers A E. CLEAR (calculated logical evacuationand response): a generic transportation network model for the calculation ofevacuation time estimates. Prepared for the Nuclear Regulatory Commission byPacific Northwest Laboratory. NUREG/CR,1981.
[47] B Mei. Development of Trip Generation Models of Hurricane Evacuation.Louisiana State University,2002.
[48] Southworth F, Janson B N, Venigalla M M. DYMOD: Towards real time, dynamictraffic routing during mass evacuations. Annual International Nuclear Power PlantSimulators Conference,1992.
[49] Hobeika A G, Kim C. Comparison of traffic assignments in evacuation modeling.IEEE Transactions on Engineering Management,1998,45(2):192-198.
[50] Rickert M, Nagel K. Dynamic traffic assignment on parallel computers inTRANSIMS. Future generation computer systems,2001,17(5):637-648.
[51] Jain R., Smith JMG. Modeling vehicular traffic flow using M/G/C/C statedependent queueing models. Transportation Science,1997,31(4):324.
[52] Rathi A K, Solanki R S. Simulation of traffic flow during emergency evacuations:a microcomputer based modeling system.1993,:1258.
[53] Bhaduri B, Liu C, Franzese O. Oak Ridge evacuation modeling system (OREMS):A PC-based computer tool for emergency evacuation planning. Symposium o n GISfor Transportation,2006.
[54] Franzese O, Sorensen J. Fast deployable system for consequence management: Theemergency evacuation component. ITS Safety and Security Conference,2004.
[55] Mahmassani H S, Hu T, Jayakrishnan R. Dynamic traffic assignment andsimulation for advanced network informatics (DYNASMART). In Proceedings ofthe2nd International CAPRI Seminar on Urban Traffic Networks,1992.
[56] Chiu Y C, Korada P, Mirchandani P B. Dynamic traffic management forevacuation.. The84th Annual Meeting of Transportation Research Board,2005.
[57] Qiao F, Ge R, Yu L. Computer Simulation-Based Framework for TransportationEvacuation in Major Trip Generator.Southwest Region University TransportationCenter,2009.
[58] Nagel K. Multi agent based large-scale evacuation simulation2008-Jul-31GregorL mmel Transport Systems Planning and Transport Telematics, Berlin Institute ofTechnology, D-10587Berlin.2008,.
[59]湛永松,卢兆明.计算机辅助大规模人群疏散平台.计算机工程,2008,34(20):77-79.
[60]陈岳明,萧德云.基于动态交通分配的路网应急疏散模型.清华大学学报:自然科学版,2009,(8):1102-1105.
[61]李强,陈翔,陈晋,唐巧.考虑危险源的城市应急交通疏散风险评价模型.科学通报,2009,54(16):2431-2436.
[62]吕永波,贾楠,任锦鸾,付蓬勃.救灾物资发放问题的动态遗传算法求解.管理科学学报,2008,11(003):29-34.
[63] Barrett B, Ran B, Pillai R. Developing a dynamic traffic management modelingframework for hurricane evacuation. Transportation Research Record: Journal ofthe Transportation Research Board,2000,1733(1):115-121.
[64] Radwan E, Mollaghasemi M, Mitchell S, Yildirim G. Framework for modelingemergency evacuation. Final project report submitted to Florida Department ofTransportation,2005.
[65] Tweedie S W, Rowland J R, Walsh S J, Rhoten Paul I, Ronald P. A methodology forestimating emergency evacuation times. The Social Science Journal,1986,23(2):189-204.
[66] Radwan A E, Hobeika A G, Sivasailam D. A computer simulation model for ru ralnetwork evacuation under natural disasters. ITE journal,1985,55(9):25-30.
[67] Meit M, Briggs T, Kennedy A. Urban to rural evacuation: planning for ruralpopulation surge. Research Report, Bethesda, MD: The Walsh Center for RuralHealth Analysis,2008.
[68] Lu Q, Huang Y, Shekhar S. Evacuation planning: A capacity constrained routingapproach. Intelligence and Security Informatics, Springer Berlin/Heidelberg2003.
[69] Shekhar S, Kim S. Contraflow Transportation Network Reconfiguration forEvacuation Route Planning. Knowledge and Data Engineering, IEEE Transactionson,2008,20(8)1115-1129.
[70] Litman T. Lessons from Katrina and Rita: What major disasters can teachtransportation planners. Journal of Transportation Engineering,2006,132(1):11-18.
[2] Perry R W, Lindell M K. Preparedness for emergency response: guidelines for theemergency planning process. Disasters,2003,27(4):336-350.
[3]安实,崔建勋,王健.国外道路交通应急区域疏散研究综述.交通运输系统工程与信息,2008,8(6):38-45.
[4]刘小明,胡红.应急交通疏散研究现状与展望.交通运输工程学报,2008,8(3):108-115.
[5] Southworth F. Regional evacuation modeling: a state-of-the-art review.ORNL/TM-11740, Oak Ridge National Laboratory, Oak Ridge, Tennessee,1990,2008,8(3):108-115.
[6] Zelinsky W, Kosiński L A. The emergency evacuation of cities: A cross-nationalhistorical and geographical study. Rowman和Littlefield Pub Inc,1991.
[7] McLoughlin D. A framework for integrated emergency management. PublicAdministration Review,1985,45:165-172.
[8] Stepanov A, Smith JMG. Multi-objective evacuation routing in transportationnetworks. European Journal of Operational Research,2009,198(2):435-446.
[9] Lindell M K. Assessing emergency preparedness in support of hazardous facilityrisk analyses: Application to siting a US hazardous waste incinerator. Journal ofHazardous Materials,1995,40(3):297-319.
[10] Cova T J, Johnson J P. Microsimulation of neighborhood evacuations in theurban-wildland interface. Environment and Planning A,2002,34(12):2211-2230.
[11] Church R L, Sexton R. Modeling small area evacuation: Can existingtransportation infrastructure impede public safety. Final Rep,2002,.
[12] Lindell M K. EMBLEM2: An empirically based large scale evacuation timeestimate model. Transportation Research Part A: Policy and Practice,2008,42(1):140-154.
[13] Longley Paul, Goodchild Michael, Maguire David, Rhind David. GIS inemergency management. New York: John Wiley和Sons,1999.
[14] Gunes A E, Kovel J P. Using GIS in emergency management operations. Journal ofUrban Planning and Development,2000,126(3):136-149.
[15] Chen T, Yuan H, Yang R, Chen J. Integration of GIS and Computational Models forEmergency Management. Proceedings of the2008International Conference onIntelligent Computation Technology and Automation,2008.
[16] Sauvagnargues-Lesage S, Ayral P A. Using GIS for emergency management: a casestudy during the2002and2003flooding in south-east France. InternationalJournal of Emergency Management,2007,4(4):682-703.
[17]刘敏,卢兆明,袁国杰.基于GIS系统的灾时大范围应急疏散研究.第十届中国科协年会,2008.
[18] Stern E, Sinuany-Stern Z. A behavioural-based simulation model for urbanevacuation. Papers in Regional Science,1989,66(1):87-103.
[19] Sorensen J H, Shumpert B L, Vogt B M. Planning for protective action decisionmaking: evacuate or shelter-in-place. Journal of hazardous materials,2004,109(1-3):1-11.
[20] Lindell M K, Lu J C, Prater C S. Household decision making and evacuation inresponse to Hurricane Lili. Natural Hazards Review,2005,6:171.
[21] Cohn P J, Carroll M S, Kumagai Y. Evacuation behavior during wildfires: Resultsof three case studies. Western Journal of Applied Forestry,2006,21(1):39-48.
[22] Lindell M K, Prater C S. Critical Behavioral Assumptions in Evacuation TimeEstimate Analysis for Private Vehicles: Examples from Hurricane Research andPlanning. Journal of Urban Planning and Development,2007,133(1):18-29.
[23] Meit M, Briggs T, Kennedy A. Urban to rural evacuation: planning for ruralpopulation surge. Research Report, Bethesda, MD: The Walsh Center for RuralHealth Analysis,2008.
[24] Santos G, Aguirre B E. A critical review of emergency evacuation simulationmodels. Proceeding of Conference "Building Occupant Movement During FireEmergencies",2004.
[25]张江华,刘治平,朱道立.多源点突发灾害事故应急疏散模型与算法.管理科学学报,2009,(3):111-118.
[26] Yuan F, Han L D, Chin S M, Hwang H. Proposed Framework for SimultaneousOptimization of Evacuation Traffic Destination and Route Assignment.Transportation Research Record: Journal of the Transportation Research Board,2006,1964(1):50-58.
[27] Kerbache L, Smith JMG. Multi-objective routing within large scale facilities usingopen finite queueing networks. European Journal of Operational Research,2000,121(1):105-123.
[28] Smith JMG, Cruz FRB. The buffer allocation problem for general finite bufferqueueing networks. IIE Transactions,2005,37(4):343-365.
[29] Cruz FRB, MacGregor Smith J, Medeiros R O. An M/G/C/C state-dependentnetwork simulation model. Computers和Operations Research,2005,32(4):919-941.
[30] Talebi K, Smith JMG. Stochastic network evacuation models. Computers和Operations Research,1985,12(6):559-577.
[31] Floudas Christodoulos A, Pardalos Panos M. Encyclopedia of Optimization.Springer,2008.
[32] Tanaka K, Nagatani T, Hanaura H. Traffic mixing in deterministic two-lane modelof Hurricane evacuation. Physica A: Statistical Mechanics and its Applications,2007,380:490-502.
[33]胡红,刘小明,魏恒,等.基于路口和路段人口综合控制的应急疏散交通控制算法.交通运输工程学报,2009,9(3):108-111.
[34] Kim S, George B, Shekhar S. Evacuation route planning: scalable heuristics.Proceedings of the15th annual ACM international s ymposium on Advances ingeographic information systems,2007.
[35] Yusoff M, Ariffin J, Mohamed A. Optimization approaches for macroscopicemergency evacuation planning: A survey. Information Technology,2008. ITSim2008. International Symposium on,2008.
[36] Yamada T. A network flow approach to a city emergency evacuation planning.International Journal of Systems Science,1996,27(10):931-936.
[37] Campos VBG, Da Silva PAL, Netto P O B. Evacuation transportation planning: amethod of identifying optimal independent routes. Surcharov L J. Proceedings ofUrban Transport V: Urban Transport and the Environment for the21st Century,2000,:555-564.
[38] Wolshon B, Lambert L. Reversible lane systems: Synthesis of practice. Journal ofTransportation Engineering,2006,132(12):933-944.
[39] Mahmassani H S, Jayakrishnan R, Herman R. Network traffic flow theory:Microscopic simulation experiments on supercomputers. Transportation ResearchPart A: General,1990,24(2):149-162.
[40] Rathi A K, Santiago A J. The new NETSIM simulation model. Traffic Engineeringand Control,1990,31(5):317.
[41] Lammel Gregor, Dominik Grether, Kai Nagel. The representation andimplementation of time-dependent inundation in large-scale microscopicevacuation simulations. Transportation Research Part C: Emerging Technologies,2010,18(1):84-98.
[42] Sheffi Y, Mahmassani H, Powell W B. A transportation network evacuation model.Transportation Research Part A: General,1982,16(3):209-218.
[43] McLean M A, Moeller M P, Desrosiers A E. CLEAR: a model for the calculation ofevacuation-time estimates in Emergency Planning Zones. Conference on modelingand simulation on microcomputers,1983.
[44] Cova T J, Johnson J P. A network flow model for lane-based evacuation routing.Transportation research part A: Policy and Practice,2003,37(7):579-604.
[45] Barcello J, Grau R. PACKSIM: An experience in using traffic simulation in ademand responsive traffic control system. XIII World Conference on OperationsResearch,1993.
[46] Moeller M P, Urbanik T, Desrosiers A E. CLEAR (calculated logical evacuationand response): a generic transportation network model for the calculation ofevacuation time estimates. Prepared for the Nuclear Regulatory Commission byPacific Northwest Laboratory. NUREG/CR,1981.
[47] B Mei. Development of Trip Generation Models of Hurricane Evacuation.Louisiana State University,2002.
[48] Southworth F, Janson B N, Venigalla M M. DYMOD: Towards real time, dynamictraffic routing during mass evacuations. Annual International Nuclear Power PlantSimulators Conference,1992.
[49] Hobeika A G, Kim C. Comparison of traffic assignments in evacuation modeling.IEEE Transactions on Engineering Management,1998,45(2):192-198.
[50] Rickert M, Nagel K. Dynamic traffic assignment on parallel computers inTRANSIMS. Future generation computer systems,2001,17(5):637-648.
[51] Jain R., Smith JMG. Modeling vehicular traffic flow using M/G/C/C statedependent queueing models. Transportation Science,1997,31(4):324.
[52] Rathi A K, Solanki R S. Simulation of traffic flow during emergency evacuations:a microcomputer based modeling system.1993,:1258.
[53] Bhaduri B, Liu C, Franzese O. Oak Ridge evacuation modeling system (OREMS):A PC-based computer tool for emergency evacuation planning. Symposium o n GISfor Transportation,2006.
[54] Franzese O, Sorensen J. Fast deployable system for consequence management: Theemergency evacuation component. ITS Safety and Security Conference,2004.
[55] Mahmassani H S, Hu T, Jayakrishnan R. Dynamic traffic assignment andsimulation for advanced network informatics (DYNASMART). In Proceedings ofthe2nd International CAPRI Seminar on Urban Traffic Networks,1992.
[56] Chiu Y C, Korada P, Mirchandani P B. Dynamic traffic management forevacuation.. The84th Annual Meeting of Transportation Research Board,2005.
[57] Qiao F, Ge R, Yu L. Computer Simulation-Based Framework for TransportationEvacuation in Major Trip Generator.Southwest Region University TransportationCenter,2009.
[58] Nagel K. Multi agent based large-scale evacuation simulation2008-Jul-31GregorL mmel Transport Systems Planning and Transport Telematics, Berlin Institute ofTechnology, D-10587Berlin.2008,.
[59]湛永松,卢兆明.计算机辅助大规模人群疏散平台.计算机工程,2008,34(20):77-79.
[60]陈岳明,萧德云.基于动态交通分配的路网应急疏散模型.清华大学学报:自然科学版,2009,(8):1102-1105.
[61]李强,陈翔,陈晋,唐巧.考虑危险源的城市应急交通疏散风险评价模型.科学通报,2009,54(16):2431-2436.
[62]吕永波,贾楠,任锦鸾,付蓬勃.救灾物资发放问题的动态遗传算法求解.管理科学学报,2008,11(003):29-34.
[63] Barrett B, Ran B, Pillai R. Developing a dynamic traffic management modelingframework for hurricane evacuation. Transportation Research Record: Journal ofthe Transportation Research Board,2000,1733(1):115-121.
[64] Radwan E, Mollaghasemi M, Mitchell S, Yildirim G. Framework for modelingemergency evacuation. Final project report submitted to Florida Department ofTransportation,2005.
[65] Tweedie S W, Rowland J R, Walsh S J, Rhoten Paul I, Ronald P. A methodology forestimating emergency evacuation times. The Social Science Journal,1986,23(2):189-204.
[66] Radwan A E, Hobeika A G, Sivasailam D. A computer simulation model for ru ralnetwork evacuation under natural disasters. ITE journal,1985,55(9):25-30.
[67] Meit M, Briggs T, Kennedy A. Urban to rural evacuation: planning for ruralpopulation surge. Research Report, Bethesda, MD: The Walsh Center for RuralHealth Analysis,2008.
[68] Lu Q, Huang Y, Shekhar S. Evacuation planning: A capacity constrained routingapproach. Intelligence and Security Informatics, Springer Berlin/Heidelberg2003.
[69] Shekhar S, Kim S. Contraflow Transportation Network Reconfiguration forEvacuation Route Planning. Knowledge and Data Engineering, IEEE Transactionson,2008,20(8)1115-1129.
[70] Litman T. Lessons from Katrina and Rita: What major disasters can teachtransportation planners. Journal of Transportation Engineering,2006,132(1):11-18.
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