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高速公路突发事件紧急救援关键技术研究
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摘要
随着我国高速公路通车里程的不断增加,国内高速公路已基本形成骨架网络,总规模己位于世界前列。高速公路行业的重点将从施工建设逐步转化为运营管理,如何保障高速公路安全、畅通、快捷、舒适成为关键。随着高速公路运营网络的日益完善,交通量快速增长,高速公路运营环境更加复杂,各种矛盾突出,给管理带来困难。高速公路突发事件的紧急救援系统是为了及时、有效地处理各种突发性交通事件,实现快速响应和紧急救助,以达到减少人员伤亡和经济损失的目的。紧急救援是高速公路管理的重要组成部分,对促进高速公路的可持续发展有重要意义。
     高速公路紧急救援系统的研究涉及应急管理理论、灾害学、交通安全学、协同学、系统工程等复杂科学理论。论文从高速公路紧急救援的基本概念和整体流程框架入手,通过分析高速公路突发事件的形成原因,将交通事件按事故状态和严重程度进行了分类和分级,并探讨了高速公路突发事件紧急救援的响应机构及责任,分析了紧急救援的实施过程,明确了高速公路突发事件紧急救援的过程。在此基础上,改进了紧急救援联动组织体系,提出了联动机制的完善措施。此后,论文在分析信息监测点需求的,优化了信息采集点的布设层次和布局方法,进而提出了基于多层检测数据的高速公路突发事件自动检测方法。紧急救援资源点的布设是紧急救援顺利实施的基础,论文随后提出应用基于NSGA-II算法对限制条件下的多紧急救援出救点的布局进行了优化。为保证紧急救援的实施过程中,各紧急救援资源的效用最大化,论文建立了模拟退火算法来求解基于机会成本的紧急救援资源调度模型。为对高速公路紧急救援系统进行评价,论文建立了紧急救援系统的可靠性分析模型,并建立模型评价不同紧急救援方案实施过程下的风险/损失。为适应交通信息化、智能化的过程,论文建立了紧急救援系统的软件框架,为科学的做出决策和实施紧急救援提供依据。
     论文首先将突发事件分为计划活动、轻微事故、重大事故、危险品倾覆、自然灾害、恐怖袭击及灾难等七类事故,明确了紧急救援相关职能部门的责任。在分析突发事件紧急救援流程的基础上,提出了高速公路联动组织指挥体系的构建和联动信息渠道的设计及完善方案。联动信息渠道设计以救援进程为线索,将一般事件的处理流程分为事件信息采集和通报、事件响应、到达现场实施交通管制、交通调查与实施救援、排障、养护等相关作业、结束管制与恢复交通和事故总结七个部分,明确救援各参与部门之间信息沟通的渠道和机制。
     为快速有效的检测高速公路事件,论文将高速公路突发事件紧急救援的交通信息采集需求分为了三个层次,并建立了分阶段分层次的交通信息采集点布局模式。考虑到信息采集点建设时序及功能的不同,对信息采集点实施三级阶段性布局,根据OD反推、交通波理论与模糊聚类研究其布局模型,在总体布局的基础上应用多目标优化模型实现信息采集点布局的动态调整。在此基础上,论文进一步基于交通检测数据的交通事件自动识别算法,既可以作为现有突发事件信息的补充,也可为将来突发事件自动检测奠定基础。
     根据高速公路突发事件紧急救援系统的目标,对救援系统中的救援资源配置和紧急救援资源调度这两个最关键的问题进行了深入研究。论文在分析高速公路突发事件紧急救援的救援点选址问题时,首先对单点和多个紧急救援服务设施选址问题进行建模,并建立了相应的选址优化求解算法。在此基础上,考虑实际突发事件紧急救援的特性,对限制条件下的紧急救援服务点选址问题进行了建模分析,并提出应用第二代多目标非支配排序遗传算法对模型进行求解。在分析紧急救援资源调度问题时,论文在回顾紧急救援资源调度算法的基础上,提出以广义救援成本作为紧急救援资源调度的考核指标,分别分析了以直接成本、潜在成本和机会成本为优化对象的紧急救援资源调度模型,指出了其建模思想主要在于是否考虑紧急救援过程中是否发生潜在事故。在此基础上,提出了应用模拟退火算法求解紧急资源调度模型的方法,并结合西安市高速公路网,在虚拟情景下给出了调度的算例。
     为评价高速公路紧急救援的绩效,论文建立了紧急救援可靠性分析模型,明确了高速公路突发事件的紧急救援系统可靠性有救援系统本身的可靠性和所依托的交通网络的可靠性共同决定,并着重对救援时间的可靠性进行了分析。在此基础上,论文根据紧急救援可靠性的概念,分析了不同救援方案及实施效果可能带来的事故的风险和最终损失,可为紧急救援系统的评价奠定基础。
     论文最后在分析高速公路突发事件紧急救援特性的基础上,建立了高速公路突发事件紧急救援系统的软件框架。论文在讨论紧急救援系统需求的基础上,讨论了紧急救援系统软件各部分之间的逻辑关系和层次,综合考虑高速公路网紧急救援联动机制、信息平台构建技术、救援资源配置与调度优化,危险品运输紧急救援等领域,建立了紧急救援系统的物理框架,并探讨了决策支持系统框架的建立途径。
The skeleton network of Chinese freeway is basically formed with the increasingof mileage, which makes the dimensions of freeway is larger than most countries allover the world. With the transform of key point from construction to operationmanagement, the freeway industry mainly focuses on how to protect highway safety,smooth, fast and comfortable. With the increasingly sophisticated freeway networkand rapid growth traffic volume, freeway operations is under a more complexenvironment, which makes it is difficult to manage. In order to deal with emergencyincident in a timely and effective manner, the highway emergency responding systemcan help the rescue staffs work efficiently to reduce casualties and economic losses.Emergency respond is an important part of the highway management, which isimportant to promote the sustainable development of highway system.
     Freeway emergency respond system involving emergency management theory,disaster science, traffic safety, synergetic theories, systems engineering and othercomplex scientific theories. Starting with the basic concepts and framework of theoverall process, the emergency incident is classified with incident status and severityby analyzing the causes of the emergencies incident. The duty of highwayemergency response agencies and their working process were then analyzed to obtainthe procedure of freeway emergency response. An improved linkage organization ofthe emergency responding system and the linkage mechanism are proposed. Basedon the requirements of the emergency responding system, an optimization method forthe layout of information collection point and highway incidents automatic detectionmethod based on multi-layer detection data are proposed. The NSGA-II algorithm isthen applied to optimize the layout of emergency resources point at the limitationconditions. To maximize the effectiveness of emergency resources, a simulatedannealing algorithm is established to solve emergency resources scheduling modelbased on the opportunity cost. To evaluate the freeway emergency respondingsystem, the system reliability model is utilized to evaluate the risk/loss under theemergency program implementation process. The software framework for freewayemergency responding system is also established to adapt to the traffic informationintelligent process.
     The emergency incident is divided into seven types to clear emergencydepartments’ responsibility, which is planning activities, minor accidents, majoraccidents, dangerous goods capsized, natural disasters, terrorist attacks and disasters.On the basis of the analysis of the process of the emergency emergencies, the highway linkage organization system and improved linkage information communicationchannels are designed. The process of emergency responding is utilized as the cluein the system. The process can be divided into information collection andnotification, incident response, arrived and traffic control, traffic surveys and rescueimplementation, troubleshooting, maintenance, traffic restoration and accidentsummarize.
     For the purpose of detecting freeway emergency incident effectively, ahierarchical traffic information collection point layout mode is established based onthe requirements of traffic information collection. Taking into account theinformation collection point construction sequence and functions, the informationcollection point should be constructed step by step. The optimized results should beadjusted based on the OD estimation, shockwave theory and fuzzy clustering. Themulti-objective optimization model is applied to adjust the layout of informationcollection point dynamically. Then, the McMaster algorithm improved to detect thefreeway emergency incident automatically.
     According to the target of freeway emergency respond, the optimization modelsfor allocation and scheduling of the emergency rescue resources are studied. Theoptimization method for the layout of single emergency rescue point andmulti-emergency rescue points are discussed theoretically. The models are improvedbased the limitations in real world. The NSGA-II algorithm is selected to solve themodel. After reviewing the modeling idea, all the emergency resource schedulingalgorithms are generalized by rescue costs. Then, the algorithms based on directcosts, potential costs and opportunity costs are analyzed respectively. In this way,the simulated annealing algorithm is utilized to solve emergency resource schedulingmodel. A virtual emergency resource scheduling example using Xi’an freewaynetwork is tested with the proposed method.
     To evaluate the performance of the highway emergency, a reliability analysismodel for emergency relief is established. The freeway emergency respondingsystem reliability is related with the system itself and the freeway network. As a keyparameter in the system, the reliability of the rescue time is analyzed separately.Then, the risk of incident and final loss by the implementation of the selected respondscenario are discussed based on the analysis of system reliability.
     The software framework of the freeway emergency respond system is putforward based on the analysis of the characteristics of highway emergency respond.The logical relationships between the various parts in the software are discussed firstly. Then, by considering network linkage mechanism, information platformtechnology, rescue resource allocation and scheduling, emergency respond fordangerous goods, the physical framework of the system is established. The decisionsupport system framework is also discussed.
引文
[1]刘伟铭.高速公路系统控制方法[M].北京:人民交通出版社,1998.
    [2]公安部交通管理局.全国道路交通事故统计资料汇编[M].北京:群众出版社,2007.
    [3]向红艳.高速公路交通事件紧急救援系统研究[D]:[博士].成都:西南交通大学,交通运输学院,2011
    [4]马社强,韩凤春郑英力.道路交通事故紧急救援体系研究[J].中国人民公安大学学报(自然科学版),2004,41(3):87-91.
    [5]顾建华,邹其嘉,卢寿德等.紧急救援有关问题的探讨与思考[J].国际地震动态,2003,(3):17-23.
    [6] Booz·Allen H..Incident Management: Detection,Verification,and Traffic ManagementField Operational Test Cross-Cutting Study[R].1998, U.S.Department of Transportationand Federal Highway Administration:
    [7]韩建保,陈厉兵.德国车辆故障现场救护与故障类型分析[J].汽车与安全,2002,(7):34-35.
    [8] FHWA. Freeway incident management handbook[M]. Washington D.C.: U.S.Departmentof Transportation,1991.
    [9] Mannering F, Hallenbeck M Koehne J. A framework for developing incident managementsystems:a summary.[R].1992, Washington State Transportation Center: Seattle, WA
    [10] Omar B S, Dung L D Athanasios K Z. A Predictive Time Based Feedback ControlApproach For Managing Freeway Incidents[C]. in79th Annual meeting of theTransportation Research Board.1999. Washington DC: TRB.
    [11] Bertini R, Rose M El-Geneidy A. Using Archived ITS Data Sources to Measure theEffectiveness of a Freeway Incident Response Program[C]. in84th Annual meeting of theTransportation Research Board.2005. Washington DC: TRB.
    [12]杨晓光,彭国雄王一如.高速公路交通事故预防与紧急救援系统[J].公路交通科技,1998,15(4):46-51.
    [13]黄同愿,黄席诞,李刚等.高速公路紧急事件与安全系统探索[J].重庆大学学报,2003,26(9):1-4.
    [14]李万新.高速公路交通事故快速救援联动机制探索[J].交通管理研究,2001,(6):22-23.
    [15]陈睿,韩春梅,朱健等.高速公路应急救援指挥软件系统的设计[J].交通与计算机,2001,(5):26-29.
    [16] Nahi N E. Freeway-traffic data processing[J]. Proceedings of the IEEE,1973,61(5):537-541.
    [17] TRB. Highway Capacity Manual2010[M]. Washington DC: National Academy ofSciences,2010.
    [18] Gentile G, Meschini L Papola N. Spillback congestion in dynamic traffic assignment: Amacroscopic flow model with time-varying bottlenecks[J]. Transportation Research PartB: Methodological,2007,41(10):1114-1138.
    [19] Sisiopiku V P, Rouphail N M Santiago A. Analysis of correlation between arterial traveltime and detector data from simulation and field studies[J]. Transportation ResearchRecord,1994,(1457):166-173.
    [20] Thomas G B. Optimal Detector Location on Arterial Streets for Advanced TravelerInformation System[D]:[Ph. D.]. Tempe, AR, USA: Arizona State University,1999
    [21] Oh S, Ran B. Optimal Detector Location for Estimating Link Travel Speed in UrbanArterial Roads[C]. in Transportation Research Broad Annual Meeting.2003. WashingtonDC: TRB.
    [22] Liu H X, Danczyk A. Optimal Detector Placement for Freeway BottleneckIdentification[C]. in Transportation Research Broad Annual Meeting.2008. WashingtonDC: TRB.
    [23]姜桂艳.道路交通状态判别技术与应用[M].北京:人民交通出版社,2004.
    [24]伍建国,王峰.城市道路交通数据采集系统检测器优化布点研究[J].公路交通科技,2004,(2):88-92.
    [25] Johnston R A, Rodier C J. Regional simulations of highway and transit ITS: Travel,emissions, and economic welfare effects[J]. Mathematical and Computer Modelling,1998,(27):143-161.
    [26]王兆华,刘志强.视频检测技术在交通安全中的应用[J].交通运输工程与信息学报,2005,3(3):
    [27] Tufekci S, Wallace W A. The emerging area of emergency management andengineering[J]. IEEE Transactions on Engineering Management,1998,45(02):103-105.
    [28] Hobeika A G, Kim C. comparison of traffic assignments in evacuation modeling[J]. IEEETransactions on Engineering Management,1998,45(2):103-105.
    [29] Ogryczak W o. On the distribution approach to location problems[J]. Computers&Industrial Engineering,1999,37(3):595-612.
    [30] Marianov V, Revelle C. The queuing probabilistic location set covering problem andsome extensions[J]. Socio-Economic Planning Sciences,1994,28(3):167-178.
    [31] Badri M A, Mortagy A K Alsayed C A. A multi-objective model for locating firestations[J]. European Journal of Operational Research,1998,110(2):243-260.
    [32] Chu S C K, Chu L. A modeling framework for hospital location and service allocation[J].International Transactions in Operational Research2000,7(6):539-568.
    [33] Adenso-Díaz B, Rodríguez F. A simple search heuristic for the MCLP: Application to thelocation of ambulance bases in a rural region[J]. Omega,1997,25(2):181-187.
    [34] Espejo L G A, Galv o R D Boffey B. Dual-based heuristics for a hierarchical coveringlocation problem[J]. Computers& Operations Research,2003,30(2):165-180.
    [35] Wybo J-L. FMIS:A decision support system for forest fire prevention and fighting[J].IEEE Transcation on Engineering Management,1998,45(2):127-131.
    [36] Hay W W. Reduction of earthquake risk in the United States: bridging the gap betweenresearch and practice[J]. IEEE Transactions on Engineering Management1998,45(2):176-180.
    [37] Cole H R. Decision making during a mine fire escape[J]. IEEE Transactions onEngineering Management1998,45(2):(2):153-162.
    [38] List G E. Routing and Emergency·Respond-Team siting for high-level radioactivewaste shipments[J]. IEEE Transactions on Engineering Management1998,45(2):141-152.
    [39] Zografos K G. Analytical framework for minimizing fi'eeway·incident response time[J].Journal of Transportation Engineering,1993,119(4):535-549.
    [40] Zografos K G, N.Androutsopoulos K M.Vasilakis G. A real-time decision support systemfor roadway network incident response logistics[J]. Transportation Research Part C:Emerging Technologies,2002,10(1):1-18.
    [41] Yarnad T. A network flow approach to a city emergency evacuation planning[J].Intemational Journal of Systems Science,1996,27(10):931-936.
    [42] Carter G M, Chaiken J M Ignall E. Response area for two emergency units[J]. OperationResearch,1972,20(3):571-594.
    [43] Mirchandani P B, Odoni A R. Locations of medians on stochastic networks[J].Transportation Science,1979,13(2):85-97.
    [44] Sheral H D, Subramanian S. Opportunity cost-based models for traffic incident responseproblem[J]. Journal of Transportation Engineering,1999,125(3):176-185.
    [45] Oh S-C. A multi-commodity, multi-modal network flow model for logisticsmanagement[D]:[Ph. D.]. College Park, MA: University of Maryland at College Park,Operations Research,1993
    [46] Haghani A, Oh S-C. Formulation and solution of a multi-commodity, multi-modalnetwork flow model for disaster relief operations[J]. Transportation Research Part A:Policy and Practice,1996,30I(3):231-250.
    [47]刘春林,何建敏盛昭瀚.应急系统多出救点选择问题的模糊规划方法[J].管理工程学报,1999,13(4):23-26.
    [48]何建敏,刘春林尤海燕.应急系统多出救点的选择问题[J].系统工程理论与实践,2011,(11):89-93.
    [49]刘春林,何建敏盛昭瀚.给定限制期条件下最小风险路径的选取算法[J].系统工程学报,1999,14(3):221-226.
    [50] Collins J M, Williams A N, Paxton C H, et al. Geographical, meteorological, andclimatological conditions surrounding the2008interstate-4disaster in Florida [C]. in theApplied Geography Conferences2009.153-162.
    [51]薛克勋.政府紧急事件响应机理研究[J].中国行政管理,2004,(2):77-82.
    [52] Wallace C E, Boyd A, Sergent J, et al. A Guide to Emergency Response Planning at StateTransportation Agencies[R].2010, TRB: Washington DC
    [53]刘君,王长君马兆有.区域高速公路网紧急事件救援协作体系构建[J].中国安全科学学报,2010,20(07):158-164.
    [54] Gao X. Fuzzy Cluster Analysis and its Applications[M]. Xi'an, China: Xi'an Electronicand Science University Press,2004.
    [55] Kwon J, Varaiya P. Effectiveness of California's High Occupancy Vehicle (HOV)system[J]. Transportation Research Part C: Emerging Technologies,2007,
    [56]张敬磊,王晓原.交通事件检测算法研究进展[J].武汉理工大学学报(交通科学与工程版)2005,29(2):215-218.
    [57]柴干,方程炜,刘庆全等.道路交通紧急救援服务点的优化选址[J].中国安全科学学报,2009,19(10):159-165.
    [58]云美萍,杨晓光.交通事故管理系统中路网分区优化模型的改进[J].公路交通科技,2004,21(4):73-76.
    [59]吕保和,王明贤,肖建兰等.我国高速公路交通事故应急救援体系的构建[J].中国安全科学学报,2006,16(7):76-80.
    [60]柴干,周家铭,濮居一等高速公路紧急救援决策支持系统的设计[J].中国安全科学学报,2007,17(05):58-63.
    [61]何建敏,刘春林,曹杰等.应急管理与应急系统——选址、调度与算法[M].北京:科学出版社,2005.
    [62] Durier R. The general one center location problem[J]. Mathematics of Operation Research,1995,20(2):400-418.
    [63] Peteers P H. Some new algorithms for location problems on networks[J]. EuropeanJournal of Operation Research,1998,(104):299-309.
    [64] Hakimi S L. Optimum location of switching centers and the absolute centers and mediansof a graph[J]. Operations Research,1965,(13):450-459.
    [65]方磊,何建敏.应急系统优化选址的模型及其算法[J].系统工程学报,2003,(1):
    [66] Douglas M I, Lee P. Facility location on a tree with maximun distance constraints[J].Computers and Operation Research,1995,22(9):905-914.
    [67] Halpern J. Duality in the cent-dian of a graph[J]. Operations Research,1980,(28):722-736.
    [68] Mirchandani P B, Francis R L. Discrete location theory[M]. New York City: Wiley,1990.
    [69] Kariv O, Hakimi S L. An algorithmic approach to network location problems[J]. SIAM JAppl Math,1997,(37a):513-538.
    [70] Averbakh I, Berman O. Minimax regret p-center location on a network with demanduncertainy[J]. Location Science,1997,5(4):247-254.
    [71] Jaramillo J H, Bhadury J Batta R. On the use of genetic algorithms to solve locationsproblems[J]. Computers and Operation Research,2002,(29):761-779.
    [72] Garfinkel R S, Neebe A W Rao M R. The m-center problem: minmax facility location[J].Operations Research,1977,(23):1133-1142.
    [73]方磊,何建敏.给定限期条件下的应急服务系统优化选址模型[J].管理工程学报,2004,(1):
    [74] Aly A A, White J A. Probabilistic Formation of the Emergency Service LocationProblem[J]. Journal of Operation Research Soiety,1978,29(12):1167-1179.
    [75]黄斌,陈德礼.多目标优化问题的有效Pareto最优集[J].计算机与数字工程,2009,37(2):28-30.
    [76]雷德明,严新平.多目标智能优化算法及其应用[M].北京:科学出版社,2009.
    [77] Schaffer J D, Multiple Objective Optimization with Vector Evaluated Genetic Algorithms,in Proceedings of the1st International Conference on Genetic Algorithms.1985, L.Erlbaum Associates Inc. p.93-100.
    [78] Hajela P, Lin C Y. Genetic search strategies in multicriterion optimal design[J]. Structuraland Multidisciplinary Optimization,1992,4(2):99-107.
    [79] Fonseca C M, Fleming P J. Genetic algorithms for multiobjective optimization:formulation, discussion and generalization[C]. in Proceedings of ICGA-93: FifthInternational Conference on Genetic Algorithms,17-22July1993.1993. San Mateo, CA,USA: Morgan Kaufmann.416-423.
    [80] Srinivas N, Deb K. Muiltiobjective optimization using nondominated sorting in geneticalgorithms[J]. Evol. Comput.,1994,2(3):221-248.
    [81] Horn J, Nafpliotis N Goldberg D E. A niched Pareto genetic algorithm for multiobjectiveoptimization[C]. in Evolutionary Computation,1994. IEEE World Congress onComputational Intelligence., Proceedings of the First IEEE Conference on.1994.82-87vol.81.
    [82] Zitzler E, Thiele L. Multiobjective Evolutionary Algorithms: A Comparative Case Studyand the Strength Pareto Approach [J]. IEEE TRANSACTIONS ON EVOLUTIONARYCOMPUTATION,1999,3(4):257-271.
    [83] Deb K, Agrawal S, Pratap A, et al., A Fast Elitist Non-dominated Sorting GeneticAlgorithm for Multi-objective Optimization: NSGA-II, in Parallel Problem Solving fromNature PPSN VI, M Schoenauer, et al., Editors.2000, Springer Berlin/Heidelberg. p.849-858.
    [84]杨晓光.基于ITS的高速公路紧急救援管理系统研究[J].上海公路,2002,(1):4-8.
    [85]高爱霞.城市快速路运行时间可靠度研究[D]:[硕士].北京:北京工业大学,建筑工程学院,2003
    [86]过秀成,孔哲叶茂.大城市绿色交通技术政策体系研究[J].现代城市研究,2010,(1):11-15.
    [87]郭瑞鹏.应急物资动员决策的方法与模型研究[D]:[博士].北京:北京理工大学,管理与经济学院,2006
    [88]秦小虎.城市交通紧急事件处理与安全系统模型及应用研究[D]:[博士].重庆:重庆大学,自动化学院,2005
    [89] Dijkstra E W. A note on two problems in connexion with graphs[J]. NumerischeMathematik,1959,1269-271.
    [90] Bellman R. On a routing problem[J]. Quarterly of Applied Mathematics,1958,16(1):87-90.
    [91] Ford L R, Fulkerson D R. Flows in Networks [M]. Princeton Princeton University Press,1962.
    [92] Cooke K L, Halsey E. The shortest route through a network with time-dependentinternodal transit times[J]. Journal of Mathematical Analysis and Applications,1966,14(3):493-498.
    [93]任刚,王炜邓卫.带转向延误和限制的最短路径问题及其求解方法[J].东南大学学报(自然科学版),2004,34(1):104-108.
    [94] Sung K, Bell M G H, Seong M, et al. Shortest path in a network with time-dependent flowspeeds[J]. European Journal ofOperational Research,2000,121(1):32-39.
    [95] Grier N, Gchabini. I. A new approach to compute minimumtime path trees in FIFO timedependent networks[C]. in Proceedings of the IEEE5th International Conference onIntelligent Transportation Systems.2002: IEEE.485-490.
    [96]赵韩涛.基于GIS-T的高速公路紧急救援系统构建及相关模型研究[D]:[博士].长春:吉林大学,交通学院,2006
    [97] Buchanan J M. Cost and Choice [M]. Chicago: The University of Chicago Press,1999.
    [98]黄珍文.机会成本:决策分析中一个重要的成本概念[J].当代经济,2002,(5):47.
    [99] Posnett J, Jan S. Indirect cost in economic evaluation: The opportunity cost of unpaidinputs[J]. Health Economics,1996,5(1):13-23.
    [100] Kerins F, Smith J K Smith R. Opportunity Cost of Capital for Venture Capital Investorsand Entrepreneurs[J]. Journal of Financial and Quantitative Analysis,2004,39(02):385-405.
    [101]肖殿良.高速公路紧急救援系统可靠性研究[D]:[硕士].西安:长安大学,公路学院,2008
    [102] Ogryczak W. On the distribution approach to location problems[J]. Computers andIndustrial Engineering,1999,37(3):595-612.
    [103]曾声奎,赵廷弟,张建国等系统可靠性设计分析教程[M].北京:北京航空航天大学出版社,2001.
    [104]肖殿良,陈红柳孟松.高速公路紧急救援系统可靠性分析[J].西华大学学报(自然科学版),2008,27(01):12-14.
    [105]张义.高速公路紧急救援模型及仿真研究[D]:[硕士].长春:吉林大学,交通学院,2006
    [106]程振华.高速公路交通事故紧急救援管理研究[D]:[硕士].成都:西南交通大学,交通运输学院,2006
    [107]王菲.高速公路交通事故紧急救援时间模型及救援站点布局研究[D]:[硕士].重庆:重庆交通大学,交通运输学院,2008
    [108]贲莉莉.城市交通事故紧急救援系统研究及辅助决策系统设计[D]:[硕士].南京:河海大学,土木工程学院,2007
    [109]马社强,韩凤春郑英力.道路交通事故紧急救援体系研究[J].中国人民公安大学学报(自然科学版)2004,10(3):87-91.
    [110]方楷.城市道路交通事故的紧急救援处理研究[D]:[硕士].南京:东南大学,交通学院,2006
    [111] Zografos K G, Androutsopoulos K N. A decision support system for integratedhazardous materials routing and emergency response decisions[J]. TransportationResearch Part C: Emerging Technologies,2008,16(6):684-703.
    [112] Zografos K G, Konstantinos N.Androutsopoulos.[R].84th Annual Meeting of theTransportation Research Board. A Decision Supports System For Hazardous MaterialsTransportation and Emergency Response Management[J].
    [113]中华人民共和国国家统计局.中国统计年鉴2011[M].北京:中国统计出版社,2012.
    [114] Hsieh W W. Machine Learning Methods in the Environmental Sciences[M]. CambridgeCambridge University Press,2009.
    [115]柴干,杨晓光.高速公路紧急救援系统的体系框架与实施方案研究[J].交通与计算机,2007,25(04):78-81.

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