基于行人仿真的轨道交通车站设施规模及布局研究
|
摘要
摘要：交通拥堵已经成为中国大城市可持续发展的首要障碍,并逐渐向二线城市蔓延。城市轨道交通在解决路面交通拥堵问题上具有高效、低耗、安全、环保等优势,因而在我国取得了快速发展。由于我国大城市流动人口比例高,居民出行量大,轨道交通承担的客流负荷高,车站拥挤问题突出,严重影响了轨道交通运营效率和安全。目前轨道交通车站行人设施规模和布局的确定采用简单的静态容量计算方法,无法反映客流动态特性。随着以计算机为工具的仿真技术的发展,行人微观仿真模型逐渐成为车站行人与设施关系分析的有效手段。然而目前的行人仿真模型存在难以达到车站拥挤状态下行人密度、无法反映拥挤状态下行人挤压力等不足,同时车站行人设施设计也存在规模测算和布局方法上的问题。对此,本文归纳分析研究现状,采用理论分析、模型构建、乘客调查、程序开发等多种手段和方法,展开了以下几方面的研究工作,取得了相应成果：
1)全面地对轨道交通各类设施上行人的行为特征进行了调研和分析,得到了各类设施上行人密度-速度关系曲线、期望速度分布等,为仿真参数标定和结果校核提供了数据；
2)构建了基于Agent的连续空间粒子理论模型。总结了目前可用于车站行人仿真的各种模型方法,详细分析了社会力模型的原理及其各种改进,针对该模型算法复杂度高、仅在力作用下的粒子与高度自控的行人存在运动特征等差异问题,本文引入分子动力学的Gear预测校正法及链接列表元胞加速算法,以及Agent感知-决策-行动建模方法,建立了基于Agent的连续空间粒子行人仿真模型理论及框架；
3)基于Agent的连续空间模型实现及仿真实验。对行人形体描述方法进行了修正,借鉴元胞自动机等离散模型空间离散化方法,设计了链接列表元胞算法实现,基于Agent建模方法将行人密度扫描-空挡选择、随密度改变斥力作用强度、恐慌系数调节等机制加入模型并设计了相应算法,基于调研结果对一系列参数进行了标定。采用面向对象语言建立了简单的仿真环境,根据车站通道单、双向行人流及疏散仿真分析,模型能再现瓶颈成拱及通道渠化现象,改进的人体参数及可变强度的作用机制能同时适用于低密度和高密度的行人仿真,能达到拥挤状态下车站的最大行人密度,并与通道调研确定的行人密度-流量较为吻合,而优化算法可以大大节约仿真时间,所建立的模型能得到疏散时间的同时反映行人受挤压力的情况；
4)收集对比了国内外轨道交通车站行人设施规模与布局的设计手册,分析得到了站台、楼扶梯、站厅等设施设计方法的差异。针对这些差异,选取典型车站,采用行人仿真工具对站台宽度设计、大编组车站楼扶梯布置、检票机布局方案等进行了仿真评价,基于定量定性分析优化了设施规模设计和布局方法,提出了改进的站台宽度算法及紧急疏散检算方法等建议。
ABSTRACT:Traffic congestion has become the leading impediment for the sustainable development for metropolitans in China, and has begun to sprawl to second-tier cities. The characteristics of urban rail transit including high efficiency, low consumption, safety, environment-friendly, make it has great advantage in treating road traffic congestion, which has been demonstrated in Beijing, Shanghai. Due to the large sharing of floating population out of the overall residents in metropolitans in China, urban rail transit assumes high passenger load, and the pedestrian congestion in stations is serious, which is of great disservice to efficiency and safety. However, different from structure designing, the design of dimension and layout of the pedestrian facilities in rail station is based on rules of thumb, while simple calculation method in terms of static capacity is not able to reflect the complexity. Along with the development of computer aided modeling technology, pedestrian micro-simulation model became an effective tool in rail station facility designing eventually. However, the present models cannot reach the pedestrian density in congestion situation, and also fail to reflect the squeeze force under dense situation. Meanwhile, there are flaws in the present design approach for the dimension calculation and layout scheme for pedestrian facilities in rail station. To this end, this paper collected and analyzed the present work done on this topic. With the methodology of theory analyzing, model formulating, field study and computer programming, the following work was done and the corresponding conclusion was achieved.
1) The pedestrian behavioral characteristics on various facilities in rail station was fully recorded and analyzed. The flow-density diagrams of different facilities, and the desired speed distribution were obtained, which supply data for simulation parameters calibration and validation. The attainable maximum capacities of facilities were got, which was compared with design capacities.
2) The simulation model and analysis method applicable for station pedestrian simulation was concluded. Specifically, the basic theory of social force model and its various modified version is detailed. For the problems of this model, such as the high algorithm complexity, the differences in moving characteristics between particles acted by forces and pedestrian with high degree of self-control. The Gear's predictor-corrector method and linked-list cell algorithm, and the perception-decision making-acting modeling approach of Agent, was introduced, the implementing framework of a space continuous particle model with object oriented programming technology was established.
3) Based on the simulation framework of the space continuous particle model, the description of pedestrian figure was optimized. The implementing algorithm for linked-list cell method was designed taking the spatial discrete method in cellular agent model as reference. Using the agent modeling method, the behavior mechanism including pedestrian density scanning and space choice, variable interaction intensity between pedestrians pertained to density and panic index adjusting, were formulated, and the corresponding algorithm was designed. A cluster of parameters for the model was calibrated. With VC++programming platform, the aforementioned model and algorithm was integrated, and a simple version of simulation tool was developed. In terms of simulation result analysis of one-direction and bi-direction walkway, and evacuation simulation with the tool, the model is able to well perform self-organization phenomenon such as arc blocking at bottleneck and lane formation in walkway. The modified pedestrian figure description approach and the variable social force interaction intensity together allow applicability in simulation under both low density and congestion density condition, and the maximum pedestrian density drawn from field study can be reached. The pedestrian flow-density diagram from simulation in walkway fits well with that got by field study, while the optimized algorithm saves simulation time obviously. And also, the model established can reflect both the evacuation time and the squeeze force exerted by other pedestrians or obstacles.
4) Although effected by operation quality to some extent, the level of service perceived by passengers in rail station, the density in particular, is fundamentally determined by design scheme. Therefore, domestic or abroad design manual on urban rail station were collected and compared. The differences of the design approach on platform, stairway and escalator, and concourse level were summarized. Aiming at these differences, typical stations were chosen as case study. The platform width calculation method, the stairway and escalator layout of long-train station, the layout scheme of fee collecting gates and evacuation testing method were evaluated with simulation tool. Based on the quantitative and qualitative analysis of the simulation results, the dimension calculation methods and layout schemes of various facilities were optimized, and modified platform width calculation method and evacuation test method under emergent situation were proposed.
1)全面地对轨道交通各类设施上行人的行为特征进行了调研和分析,得到了各类设施上行人密度-速度关系曲线、期望速度分布等,为仿真参数标定和结果校核提供了数据；
2)构建了基于Agent的连续空间粒子理论模型。总结了目前可用于车站行人仿真的各种模型方法,详细分析了社会力模型的原理及其各种改进,针对该模型算法复杂度高、仅在力作用下的粒子与高度自控的行人存在运动特征等差异问题,本文引入分子动力学的Gear预测校正法及链接列表元胞加速算法,以及Agent感知-决策-行动建模方法,建立了基于Agent的连续空间粒子行人仿真模型理论及框架；
3)基于Agent的连续空间模型实现及仿真实验。对行人形体描述方法进行了修正,借鉴元胞自动机等离散模型空间离散化方法,设计了链接列表元胞算法实现,基于Agent建模方法将行人密度扫描-空挡选择、随密度改变斥力作用强度、恐慌系数调节等机制加入模型并设计了相应算法,基于调研结果对一系列参数进行了标定。采用面向对象语言建立了简单的仿真环境,根据车站通道单、双向行人流及疏散仿真分析,模型能再现瓶颈成拱及通道渠化现象,改进的人体参数及可变强度的作用机制能同时适用于低密度和高密度的行人仿真,能达到拥挤状态下车站的最大行人密度,并与通道调研确定的行人密度-流量较为吻合,而优化算法可以大大节约仿真时间,所建立的模型能得到疏散时间的同时反映行人受挤压力的情况；
4)收集对比了国内外轨道交通车站行人设施规模与布局的设计手册,分析得到了站台、楼扶梯、站厅等设施设计方法的差异。针对这些差异,选取典型车站,采用行人仿真工具对站台宽度设计、大编组车站楼扶梯布置、检票机布局方案等进行了仿真评价,基于定量定性分析优化了设施规模设计和布局方法,提出了改进的站台宽度算法及紧急疏散检算方法等建议。
ABSTRACT:Traffic congestion has become the leading impediment for the sustainable development for metropolitans in China, and has begun to sprawl to second-tier cities. The characteristics of urban rail transit including high efficiency, low consumption, safety, environment-friendly, make it has great advantage in treating road traffic congestion, which has been demonstrated in Beijing, Shanghai. Due to the large sharing of floating population out of the overall residents in metropolitans in China, urban rail transit assumes high passenger load, and the pedestrian congestion in stations is serious, which is of great disservice to efficiency and safety. However, different from structure designing, the design of dimension and layout of the pedestrian facilities in rail station is based on rules of thumb, while simple calculation method in terms of static capacity is not able to reflect the complexity. Along with the development of computer aided modeling technology, pedestrian micro-simulation model became an effective tool in rail station facility designing eventually. However, the present models cannot reach the pedestrian density in congestion situation, and also fail to reflect the squeeze force under dense situation. Meanwhile, there are flaws in the present design approach for the dimension calculation and layout scheme for pedestrian facilities in rail station. To this end, this paper collected and analyzed the present work done on this topic. With the methodology of theory analyzing, model formulating, field study and computer programming, the following work was done and the corresponding conclusion was achieved.
1) The pedestrian behavioral characteristics on various facilities in rail station was fully recorded and analyzed. The flow-density diagrams of different facilities, and the desired speed distribution were obtained, which supply data for simulation parameters calibration and validation. The attainable maximum capacities of facilities were got, which was compared with design capacities.
2) The simulation model and analysis method applicable for station pedestrian simulation was concluded. Specifically, the basic theory of social force model and its various modified version is detailed. For the problems of this model, such as the high algorithm complexity, the differences in moving characteristics between particles acted by forces and pedestrian with high degree of self-control. The Gear's predictor-corrector method and linked-list cell algorithm, and the perception-decision making-acting modeling approach of Agent, was introduced, the implementing framework of a space continuous particle model with object oriented programming technology was established.
3) Based on the simulation framework of the space continuous particle model, the description of pedestrian figure was optimized. The implementing algorithm for linked-list cell method was designed taking the spatial discrete method in cellular agent model as reference. Using the agent modeling method, the behavior mechanism including pedestrian density scanning and space choice, variable interaction intensity between pedestrians pertained to density and panic index adjusting, were formulated, and the corresponding algorithm was designed. A cluster of parameters for the model was calibrated. With VC++programming platform, the aforementioned model and algorithm was integrated, and a simple version of simulation tool was developed. In terms of simulation result analysis of one-direction and bi-direction walkway, and evacuation simulation with the tool, the model is able to well perform self-organization phenomenon such as arc blocking at bottleneck and lane formation in walkway. The modified pedestrian figure description approach and the variable social force interaction intensity together allow applicability in simulation under both low density and congestion density condition, and the maximum pedestrian density drawn from field study can be reached. The pedestrian flow-density diagram from simulation in walkway fits well with that got by field study, while the optimized algorithm saves simulation time obviously. And also, the model established can reflect both the evacuation time and the squeeze force exerted by other pedestrians or obstacles.
4) Although effected by operation quality to some extent, the level of service perceived by passengers in rail station, the density in particular, is fundamentally determined by design scheme. Therefore, domestic or abroad design manual on urban rail station were collected and compared. The differences of the design approach on platform, stairway and escalator, and concourse level were summarized. Aiming at these differences, typical stations were chosen as case study. The platform width calculation method, the stairway and escalator layout of long-train station, the layout scheme of fee collecting gates and evacuation testing method were evaluated with simulation tool. Based on the quantitative and qualitative analysis of the simulation results, the dimension calculation methods and layout schemes of various facilities were optimized, and modified platform width calculation method and evacuation test method under emergent situation were proposed.
引文
[1]中国土木工程学会.中国城市轨道交通新技术[M].北京：中国科学技术出版社,2007.
[2]施仲衡等.中国城市轨道交通年度报告[G].北京：北京交通大学出版社,2012.
[3]王理达.地铁车站人群疏散行为仿真研究[D].北京交通大学安全技术及工程,2006.
[4]马杰.城市轨道交通车站通行设施通过能力研究[D].北京交通大学道路与铁道工程,2010.
[5]F H L. The Statistics of Crowd Fluids[J]. Nature,1971,229:381-383.
[6]Helbing D M P F I. Self-organizing pedestrian movement[J]. Environment and Planning B: Planning and Design,2001,28(3):361-383.
[7]Hughes R. The Flow of Human Crowds[J]. Annual Review of Fluid Mechanics,2003, 35:162-182.
[8]Blue V J, Adler J L. Cellular automata microsimulation for modeling bi-directional pedestrian walkways[J]. Transportation Research Part B:Methodological,2001,35(3):293-312.
[9]J. Dijkstra J J H T. A multi-agent cellular automata model of pedestrian movement[J]. Pedestrian and Evacuation Dynamics,2001:173-181.
[10]S. Okazaki S M. A study of simulation model for pedestrian movement with evacuation and queuing[J]. Proceedings of the International Conference on Engineering for Crowd Safety, 1993,271-280.
[11]吉岩,李力,胡坚明,等.一种基于分片磁场和动态博弈的行人仿真模型[J].自然科学进展,2009,19(3)：337-343.
[12]Helbing D M P. Social force model for pedestrian dynamics [J]. Physical Review E, 1995,51:4282-4286.
[13]廖明军,李克平,王凯英,等.行人交通微观仿真研究综述[J].武汉理工大学学报(交通科学与工程版),2010,34(1)：180-183.
[14]中华人民共和国行业标准.GB50157-2003地铁设计规范[S].北京：中国计划出版社,2003.
[15]中华人民共和国行业标准.GB 50490-2009,城市轨道交通技术规范[s].北京：中国建筑工业出版社,2009.
[16]中国台北捷运局.台北都会区大众捷运系统规划手册[S].台北：中兴顾问出版社,2004.
[17]Associates K, Administration U S F T, Program T C R, et al. Transit capacity and quality of service manual[M]. Transportation Research Board National Research,2003.
[18]Association N F P, Others. Standard for Fixed Guideway Transit and Passenger Rail Systems[S]. NFPA,2007.
[19]Authority A R T. Marta System Design Criteria[S].1997.
[20]蒙晓莲.广州轨道交通3号线车站合理规模的探讨[J].城市轨道交通研究,2005,7(6)：63-66.
[21]汪晓蓉,于波.控制地铁车站规模的体会[J].现代隧道技术,2009(3)：22-28.
[22]饶雪平,顾保南.关于缩小地铁车站规模的思考[J].城市轨道交通研究,2001,4(003)：14-17.
[23]梁广深.缩短地铁列车编组长度对降低车站造价作用不大[J].城市轨道交通研究,2003,6(6).
[24]沈景炎.乘客动态分布与站台宽度的研究[J].城市轨道交通研究,2001,4(1)：21-25.
[25]赵天智.广州地铁车站站厅建筑布置及规模的探讨[J].铁道标准设计,2005(10)：120-123.
[26]贾洪飞,杨丽丽,唐明.综合交通枢纽内部行人流特性分析及仿真模型参数标定[J].交通运输系统工程与信息,2009,9(5)：117-123.
[27]杨丽丽.综合交通客运枢纽内部行人交通特性研究[D].吉林大学,2009.
[28]刘福华,赵怀民,邓瑞.大型铁路客运枢纽设施应急能力匹配度研究[J].铁道运输与经济,2011,33(9)：74-77.
[29]彭进,陈三明.城市轨道交通大型换乘站客流组织优化方案设计[J].桂林理工大学学报,2011,31(2)：296-302.
[30]吴先宇.城市轨道交通枢纽设施配置适应性分析及仿真优化方法[D].北京交通大学交通运输规划与管理,2010.
[31]刘文婷.城市轨道交通车站乘客紧急疏散能力研究[D].同济大学交通运输工程学院同济大学交通运输规划与管理,2008.
[32]李明华.轨道交通枢纽行人步行设施适应性分析[D].北京交通大学交通运输规划与管理，2008.
[33]陈峰,吴奇兵,张慧慧,等.北京地铁1号线车站设施与客流关系分析[J].交通运输系统工程与信息,2009,9(2)：93-98.
[34]李得伟.城市轨道交通枢纽乘客集散模型及微观仿真理论[D].北京交通大学交通运输规划与管理,2007.
[35]孙立光.步行设施内的行人行为微观仿真模型研究[D].北京：清华大学,2009.
[36]蒋启文.城市轨道交通车站进出站设施优化配置问题研究[D].北京交通大学交通运输规划与管理,2009.
[37]吕鹏.地铁车站乘客集散仿真研究及其在设施协调设计中的应用[D].北京交通大学城市轨道交通工程,2007.
[38]魏召.基于空当搜索的客运交通枢纽行人交通仿真建模研究[D].北京交通大学城市交通工程,2008.
[39]饶雪平.轨道交通车站楼梯和自动扶梯处客流延时分析[J].交通与运输,2005(z1)：13-15.
[40]王磊,杨晓光,陈春.地铁站乘客步行通道的优化设计[J].城市轨道交通研究,2003,6(2)：41-45.
[41]张建勋,韩宝明,李得伟.VISSIM在地铁枢纽客流微观仿真中的应用[J].计算机仿真,2007,24(6)：239-242,283.
[42]徐尉南,吴正.地铁候车厅客流运动的数学模型[J].铁道科学与工程学报,2005,2(2)：70-75.
[43]汪晓蓉.关于地铁车站紧急疏散计算的体会[J].科学技术通讯,2001(3)：26-27.
[44]喻言,刘栋栋,孔维伟.地铁出口和内部条件对人员疏散的影响分析及应用[J].北京建筑工程学院学报,2008,24(4)：30-35.
[45]吴娇蓉,冯建栋,陈小鸿.中美地铁车站火灾疏散设计规范对比与分析[J].同济大学学报(自然科学版),2009,37(8)：1034-1039,1138.
[46]姚斌,徐晓玲,左剑,等.自动扶梯运行方式对地铁站台人员安全疏散的影响[J].火灾科学,2008,17(1)：19-24.
[47]黄希发.大型场馆人员疏散仿真研究[D].哈尔滨工程大学,2010.
[48]张盛.城市轨道交通地下车站行人设施规模和布局评价方法研究[D].北京交通大学道路与铁道工程,2011.
[49]田娟荣,周孝清,李健.地铁自动检票闸机对人员疏散的影响分析[J].火灾科学,2006(1)：38-43.
[50]王子甲,陈峰,罗诚.轨道交通车站检票闸机布局的仿真优化[J].北京交通大学学报,2011(6)：28-32.
[51]C. Y. Cheung W H K L. Pedestrian Route Choices between Escalator and Stairway in MTR Stations[J]. Journal of transportation engineering,1998(5):277-285.
[52]张慧慧,陈峰,吴奇兵.北京地铁进出站设施通行瓶颈问题定量分析[J].都市快轨交通,2009(3)：20-23.
[53]Fruin J J. Pedestrian planning and design[M]. New York:Metropolitan Association of Urban Designers and Environmental Planners,1971.
[54]张驰清.城市轨道交通枢纽乘客交通设施服务水平研究[D].北京交通大学交通运输规划与管理,2007.
[55]K L. Field Theory in social Science[G]. NewYork:Harper and Row,1951.
[56]单庆超.城市轨道交通行人流运动建模及仿真[J].北京交通大学.
[57]Helbing D, Molnar P. Social Force Model for Pedestrian Dynamics[J]. PHYSICAL Review E, 1995,51(5):4282-4286.
[58]单庆超.城市轨道交通行人流运动建模及仿真[D].北京交通大学,2010.
[59]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.
[60]PTV. VISSIM 5.30 User Manual[M]. Planung Transport Verkehr AG, Germany:2010.
[61]D. Helbing F T V. Simulating Dynamical Features Of Escape Panic[J]. Nature, 2000,407(6803):487-490.
[62]Parisi D R, Dorso C O. Microscopic dynamics of pedestrian evacuation[J]. Physica A: Statistical Mechanics and its Applications,2005,354(1-4):606-618.
[63]Lakoba T I, Kaup D J, Finkelstein N M. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution[J]. Simulation,2005,81(5):339-352.
[64]A. Johansson D H P K. Specification of a Microscopic Pedestrian Model by Evolutionary Adjustment to Video Tracking Data [J]. Advances in Complex Systems,2008,10(4):271-288.
[65]Parisi D R, Gilman M, Moldovan H. A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions[J]. Physica A:Statistical Mechanics and its Applications,2009,388(17):3600-3608.
[66]陈涛,应振根,申世飞,等.相对速度影响下社会力模型的疏散模拟与分析[J].自然科学进展,2006,16(12)：1606-1612.
[67]胡清梅,方卫宁,邓野.一种基于社会力的行人运动模型研究[J].系统仿真学报,2009,21(4)：977-980.
[68]高春霞,董宝田.交通枢纽微观行人仿真社会力模型的改进及实现[J].物流技术,2010,29(10)：57-59.
[69]陈敏伯.计算化学：从理论化学到分子模拟[M].科学出版社,2009.
[70]Richard L. Burden J D F. Numerical Analysis[G]. Boston:Prindle, Weber and Schmidt., 1993.
[71]Courant R, Friedrichs K, Lewy H. On the partial difference equations of mathematical physics[J].1956,11(2):215-234.
[72]Dan Dumitrescu F J. Link-Cell Method for Dyncmic Evolutionary Clustering[J]. Symbolic and Numeric Algorithms for Scientific Computing,2004,20:480-489.
[73]刘春艳.基于Agent的管理信息系统的设计与人机交互系统的研究[D].重庆大学控制理论与控制工程,2003.
[74]张克,孙基男.Agent技术在矿井管理决策中的应用[J].计算机与现代化,2002,10：29-31.
[75]刘继山,王延章.RN理论支持的多Agent协同业务流程建模[J].计算机应用与软件,2011,28(4)：12-16.
[76]赵龙文,侯义斌.多Agent系统及其组织结构[J].计算机应用研究,2000,17(7)：12-14,25.
[77]张克,邵长胜,强文义.基于面向Agent技术的任务规划系统研究[J].高技术通讯,2002,12(5)：82-86.
[78]伍雄斌.城市交通集成系统的多智能体博弈模型研究[D].福建农林大学,2007.
[79]朱茵,唐祯敏,钱大琳.基于多Agent技术的交通事故救援系统的研究[J].中国安全科学学报,2002,12(1)：51-55.
[80]闻育.复杂多阶段动态决策的蚁群优化方法及其在交通系统控制中的应用[D].浙江大学控制科学与工程,2004.
[81]张云丰.基于多代理的第四方物流作业外包合同设计[D].重庆大学管理科学与工程,2009.
[82]曾令赫.协同设计中信息管理技术的研究[D].北京工业大学,2003.
[83]于长立,鲁迪,鲁铭,等.基于多智能体系统的分布式数字农业管理平台构建[J].华中师范大学学报(自然科学版),2007,41(4)：617-621.
[84]张囡囡.基于主体的电子政务业务系统元模型建模研究[D].东北财经大学,2011.
[85]朱茵,唐祯敏,钱大琳.基于多智能体技术的交通管理系统的研究[J].中国公路学报,2002,15(3)：80-83.
[86]承向军,杨肇夏.基于多智能体技术的城市交通控制系统的探讨[J].北方交通大学学报, 2002,26(5)：47-50.
[87]刘继山.基于角色和多主体理论电子政务业务系统建模[D].大连理工大学,2011.
[88]彭滨.一种基于MAS的入侵检测方法[J].计算机安全,2011(7)：54-57.
[89]左大杰,徐学才.基于多Agent的高速公路AIMS架构[J].交通运输工程与信息学报,2007,5(003)：6-11.
[90]徐海祥.基于支持向量机方法的图像分割与目标分类[D].华中科技大学,2005.
[91]中国标准化与信息分类编码所.GB/T 10000-1988中国成年人人体尺寸[S].国家质检总局,1988.
[92]李绍珠.心理统计方法简介(续)[J].教育科研情况交流,1982(4)：36-41.
[93]Apel M, WALDEER K T. Simulation of pedestrian flows based on the social force model using the verlet link cell algorithm[J]. Karl-Scharfenberg-Fakult at Salzgitter, Institut fur Simulation und Modellierung,2004.
[94]Osaragi T. Modeling of pedestrian behavior and its applications to spatial evaluation, 2004[C].
[95]Shao W, Terzopoulos D. Autonomous pedestrians,2005[C].
[96]Daamen W. Modelling passenger flows in public transport facilities[D]. Delft, the Netherlands:Netherlands TRAIL Research School,2004.
[97]富涛.基于社会力模型的轨道交通车站内部行人仿真研究[D].北京交通大学,2011.
[98]郭录.软件高频雷达系统控制平台的设计与实现[D].哈尔滨工业大学,2007.
[99]文臣.雷达显示与控制系统的软件设计[D].电子科技大学,2005.
[100]曹宇.激光微细熔覆柔性加工平台CAD/CAM系统软件与工艺研究[D].华中科技大学,2006.
[101]王子甲,陈峰,施仲衡.基于Agent的社会力模型实现及地铁通道行人仿真[J].南理工大学学报,2013,41(4)：90-95.
[102]魏召.基于空当搜索的客运交通枢纽行人交通仿真建模研究[D].北京交通大学,2008.
[103]王子甲,陈峰,李小红.地铁车站同站台换乘实现方式的仿真研究[J].综合运输,2012(6)：71-74.
[104]刘晓娟.大型超市火灾时人员安全疏散模型研究[D].安徽理工大学安全技术及工程,2009.
[105]万鑫铭.基于虚拟试验的汽车前碰撞安全气囊防护效率的研究[D].湖南大学车辆工程,2006.
[106]Wang Z, Chen F, Li X. Comparative Analysis and Pedestrian Simulation Evaluation on Emergency Evacuation Test Methods for Urban Rail Transit Stations[J]. PROMET-Traffic\&Transportation,2012,24(6):535-542.
[107]Zijia W, Feng C, Wu D. Modification of the Platform Width Calculation Method of Urban Rail Transit:1st International Conference on Railway Engineering, Beijing, China,2010[C].
[2]施仲衡等.中国城市轨道交通年度报告[G].北京：北京交通大学出版社,2012.
[3]王理达.地铁车站人群疏散行为仿真研究[D].北京交通大学安全技术及工程,2006.
[4]马杰.城市轨道交通车站通行设施通过能力研究[D].北京交通大学道路与铁道工程,2010.
[5]F H L. The Statistics of Crowd Fluids[J]. Nature,1971,229:381-383.
[6]Helbing D M P F I. Self-organizing pedestrian movement[J]. Environment and Planning B: Planning and Design,2001,28(3):361-383.
[7]Hughes R. The Flow of Human Crowds[J]. Annual Review of Fluid Mechanics,2003, 35:162-182.
[8]Blue V J, Adler J L. Cellular automata microsimulation for modeling bi-directional pedestrian walkways[J]. Transportation Research Part B:Methodological,2001,35(3):293-312.
[9]J. Dijkstra J J H T. A multi-agent cellular automata model of pedestrian movement[J]. Pedestrian and Evacuation Dynamics,2001:173-181.
[10]S. Okazaki S M. A study of simulation model for pedestrian movement with evacuation and queuing[J]. Proceedings of the International Conference on Engineering for Crowd Safety, 1993,271-280.
[11]吉岩,李力,胡坚明,等.一种基于分片磁场和动态博弈的行人仿真模型[J].自然科学进展,2009,19(3)：337-343.
[12]Helbing D M P. Social force model for pedestrian dynamics [J]. Physical Review E, 1995,51:4282-4286.
[13]廖明军,李克平,王凯英,等.行人交通微观仿真研究综述[J].武汉理工大学学报(交通科学与工程版),2010,34(1)：180-183.
[14]中华人民共和国行业标准.GB50157-2003地铁设计规范[S].北京：中国计划出版社,2003.
[15]中华人民共和国行业标准.GB 50490-2009,城市轨道交通技术规范[s].北京：中国建筑工业出版社,2009.
[16]中国台北捷运局.台北都会区大众捷运系统规划手册[S].台北：中兴顾问出版社,2004.
[17]Associates K, Administration U S F T, Program T C R, et al. Transit capacity and quality of service manual[M]. Transportation Research Board National Research,2003.
[18]Association N F P, Others. Standard for Fixed Guideway Transit and Passenger Rail Systems[S]. NFPA,2007.
[19]Authority A R T. Marta System Design Criteria[S].1997.
[20]蒙晓莲.广州轨道交通3号线车站合理规模的探讨[J].城市轨道交通研究,2005,7(6)：63-66.
[21]汪晓蓉,于波.控制地铁车站规模的体会[J].现代隧道技术,2009(3)：22-28.
[22]饶雪平,顾保南.关于缩小地铁车站规模的思考[J].城市轨道交通研究,2001,4(003)：14-17.
[23]梁广深.缩短地铁列车编组长度对降低车站造价作用不大[J].城市轨道交通研究,2003,6(6).
[24]沈景炎.乘客动态分布与站台宽度的研究[J].城市轨道交通研究,2001,4(1)：21-25.
[25]赵天智.广州地铁车站站厅建筑布置及规模的探讨[J].铁道标准设计,2005(10)：120-123.
[26]贾洪飞,杨丽丽,唐明.综合交通枢纽内部行人流特性分析及仿真模型参数标定[J].交通运输系统工程与信息,2009,9(5)：117-123.
[27]杨丽丽.综合交通客运枢纽内部行人交通特性研究[D].吉林大学,2009.
[28]刘福华,赵怀民,邓瑞.大型铁路客运枢纽设施应急能力匹配度研究[J].铁道运输与经济,2011,33(9)：74-77.
[29]彭进,陈三明.城市轨道交通大型换乘站客流组织优化方案设计[J].桂林理工大学学报,2011,31(2)：296-302.
[30]吴先宇.城市轨道交通枢纽设施配置适应性分析及仿真优化方法[D].北京交通大学交通运输规划与管理,2010.
[31]刘文婷.城市轨道交通车站乘客紧急疏散能力研究[D].同济大学交通运输工程学院同济大学交通运输规划与管理,2008.
[32]李明华.轨道交通枢纽行人步行设施适应性分析[D].北京交通大学交通运输规划与管理，2008.
[33]陈峰,吴奇兵,张慧慧,等.北京地铁1号线车站设施与客流关系分析[J].交通运输系统工程与信息,2009,9(2)：93-98.
[34]李得伟.城市轨道交通枢纽乘客集散模型及微观仿真理论[D].北京交通大学交通运输规划与管理,2007.
[35]孙立光.步行设施内的行人行为微观仿真模型研究[D].北京：清华大学,2009.
[36]蒋启文.城市轨道交通车站进出站设施优化配置问题研究[D].北京交通大学交通运输规划与管理,2009.
[37]吕鹏.地铁车站乘客集散仿真研究及其在设施协调设计中的应用[D].北京交通大学城市轨道交通工程,2007.
[38]魏召.基于空当搜索的客运交通枢纽行人交通仿真建模研究[D].北京交通大学城市交通工程,2008.
[39]饶雪平.轨道交通车站楼梯和自动扶梯处客流延时分析[J].交通与运输,2005(z1)：13-15.
[40]王磊,杨晓光,陈春.地铁站乘客步行通道的优化设计[J].城市轨道交通研究,2003,6(2)：41-45.
[41]张建勋,韩宝明,李得伟.VISSIM在地铁枢纽客流微观仿真中的应用[J].计算机仿真,2007,24(6)：239-242,283.
[42]徐尉南,吴正.地铁候车厅客流运动的数学模型[J].铁道科学与工程学报,2005,2(2)：70-75.
[43]汪晓蓉.关于地铁车站紧急疏散计算的体会[J].科学技术通讯,2001(3)：26-27.
[44]喻言,刘栋栋,孔维伟.地铁出口和内部条件对人员疏散的影响分析及应用[J].北京建筑工程学院学报,2008,24(4)：30-35.
[45]吴娇蓉,冯建栋,陈小鸿.中美地铁车站火灾疏散设计规范对比与分析[J].同济大学学报(自然科学版),2009,37(8)：1034-1039,1138.
[46]姚斌,徐晓玲,左剑,等.自动扶梯运行方式对地铁站台人员安全疏散的影响[J].火灾科学,2008,17(1)：19-24.
[47]黄希发.大型场馆人员疏散仿真研究[D].哈尔滨工程大学,2010.
[48]张盛.城市轨道交通地下车站行人设施规模和布局评价方法研究[D].北京交通大学道路与铁道工程,2011.
[49]田娟荣,周孝清,李健.地铁自动检票闸机对人员疏散的影响分析[J].火灾科学,2006(1)：38-43.
[50]王子甲,陈峰,罗诚.轨道交通车站检票闸机布局的仿真优化[J].北京交通大学学报,2011(6)：28-32.
[51]C. Y. Cheung W H K L. Pedestrian Route Choices between Escalator and Stairway in MTR Stations[J]. Journal of transportation engineering,1998(5):277-285.
[52]张慧慧,陈峰,吴奇兵.北京地铁进出站设施通行瓶颈问题定量分析[J].都市快轨交通,2009(3)：20-23.
[53]Fruin J J. Pedestrian planning and design[M]. New York:Metropolitan Association of Urban Designers and Environmental Planners,1971.
[54]张驰清.城市轨道交通枢纽乘客交通设施服务水平研究[D].北京交通大学交通运输规划与管理,2007.
[55]K L. Field Theory in social Science[G]. NewYork:Harper and Row,1951.
[56]单庆超.城市轨道交通行人流运动建模及仿真[J].北京交通大学.
[57]Helbing D, Molnar P. Social Force Model for Pedestrian Dynamics[J]. PHYSICAL Review E, 1995,51(5):4282-4286.
[58]单庆超.城市轨道交通行人流运动建模及仿真[D].北京交通大学,2010.
[59]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.
[60]PTV. VISSIM 5.30 User Manual[M]. Planung Transport Verkehr AG, Germany:2010.
[61]D. Helbing F T V. Simulating Dynamical Features Of Escape Panic[J]. Nature, 2000,407(6803):487-490.
[62]Parisi D R, Dorso C O. Microscopic dynamics of pedestrian evacuation[J]. Physica A: Statistical Mechanics and its Applications,2005,354(1-4):606-618.
[63]Lakoba T I, Kaup D J, Finkelstein N M. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution[J]. Simulation,2005,81(5):339-352.
[64]A. Johansson D H P K. Specification of a Microscopic Pedestrian Model by Evolutionary Adjustment to Video Tracking Data [J]. Advances in Complex Systems,2008,10(4):271-288.
[65]Parisi D R, Gilman M, Moldovan H. A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions[J]. Physica A:Statistical Mechanics and its Applications,2009,388(17):3600-3608.
[66]陈涛,应振根,申世飞,等.相对速度影响下社会力模型的疏散模拟与分析[J].自然科学进展,2006,16(12)：1606-1612.
[67]胡清梅,方卫宁,邓野.一种基于社会力的行人运动模型研究[J].系统仿真学报,2009,21(4)：977-980.
[68]高春霞,董宝田.交通枢纽微观行人仿真社会力模型的改进及实现[J].物流技术,2010,29(10)：57-59.
[69]陈敏伯.计算化学：从理论化学到分子模拟[M].科学出版社,2009.
[70]Richard L. Burden J D F. Numerical Analysis[G]. Boston:Prindle, Weber and Schmidt., 1993.
[71]Courant R, Friedrichs K, Lewy H. On the partial difference equations of mathematical physics[J].1956,11(2):215-234.
[72]Dan Dumitrescu F J. Link-Cell Method for Dyncmic Evolutionary Clustering[J]. Symbolic and Numeric Algorithms for Scientific Computing,2004,20:480-489.
[73]刘春艳.基于Agent的管理信息系统的设计与人机交互系统的研究[D].重庆大学控制理论与控制工程,2003.
[74]张克,孙基男.Agent技术在矿井管理决策中的应用[J].计算机与现代化,2002,10：29-31.
[75]刘继山,王延章.RN理论支持的多Agent协同业务流程建模[J].计算机应用与软件,2011,28(4)：12-16.
[76]赵龙文,侯义斌.多Agent系统及其组织结构[J].计算机应用研究,2000,17(7)：12-14,25.
[77]张克,邵长胜,强文义.基于面向Agent技术的任务规划系统研究[J].高技术通讯,2002,12(5)：82-86.
[78]伍雄斌.城市交通集成系统的多智能体博弈模型研究[D].福建农林大学,2007.
[79]朱茵,唐祯敏,钱大琳.基于多Agent技术的交通事故救援系统的研究[J].中国安全科学学报,2002,12(1)：51-55.
[80]闻育.复杂多阶段动态决策的蚁群优化方法及其在交通系统控制中的应用[D].浙江大学控制科学与工程,2004.
[81]张云丰.基于多代理的第四方物流作业外包合同设计[D].重庆大学管理科学与工程,2009.
[82]曾令赫.协同设计中信息管理技术的研究[D].北京工业大学,2003.
[83]于长立,鲁迪,鲁铭,等.基于多智能体系统的分布式数字农业管理平台构建[J].华中师范大学学报(自然科学版),2007,41(4)：617-621.
[84]张囡囡.基于主体的电子政务业务系统元模型建模研究[D].东北财经大学,2011.
[85]朱茵,唐祯敏,钱大琳.基于多智能体技术的交通管理系统的研究[J].中国公路学报,2002,15(3)：80-83.
[86]承向军,杨肇夏.基于多智能体技术的城市交通控制系统的探讨[J].北方交通大学学报, 2002,26(5)：47-50.
[87]刘继山.基于角色和多主体理论电子政务业务系统建模[D].大连理工大学,2011.
[88]彭滨.一种基于MAS的入侵检测方法[J].计算机安全,2011(7)：54-57.
[89]左大杰,徐学才.基于多Agent的高速公路AIMS架构[J].交通运输工程与信息学报,2007,5(003)：6-11.
[90]徐海祥.基于支持向量机方法的图像分割与目标分类[D].华中科技大学,2005.
[91]中国标准化与信息分类编码所.GB/T 10000-1988中国成年人人体尺寸[S].国家质检总局,1988.
[92]李绍珠.心理统计方法简介(续)[J].教育科研情况交流,1982(4)：36-41.
[93]Apel M, WALDEER K T. Simulation of pedestrian flows based on the social force model using the verlet link cell algorithm[J]. Karl-Scharfenberg-Fakult at Salzgitter, Institut fur Simulation und Modellierung,2004.
[94]Osaragi T. Modeling of pedestrian behavior and its applications to spatial evaluation, 2004[C].
[95]Shao W, Terzopoulos D. Autonomous pedestrians,2005[C].
[96]Daamen W. Modelling passenger flows in public transport facilities[D]. Delft, the Netherlands:Netherlands TRAIL Research School,2004.
[97]富涛.基于社会力模型的轨道交通车站内部行人仿真研究[D].北京交通大学,2011.
[98]郭录.软件高频雷达系统控制平台的设计与实现[D].哈尔滨工业大学,2007.
[99]文臣.雷达显示与控制系统的软件设计[D].电子科技大学,2005.
[100]曹宇.激光微细熔覆柔性加工平台CAD/CAM系统软件与工艺研究[D].华中科技大学,2006.
[101]王子甲,陈峰,施仲衡.基于Agent的社会力模型实现及地铁通道行人仿真[J].南理工大学学报,2013,41(4)：90-95.
[102]魏召.基于空当搜索的客运交通枢纽行人交通仿真建模研究[D].北京交通大学,2008.
[103]王子甲,陈峰,李小红.地铁车站同站台换乘实现方式的仿真研究[J].综合运输,2012(6)：71-74.
[104]刘晓娟.大型超市火灾时人员安全疏散模型研究[D].安徽理工大学安全技术及工程,2009.
[105]万鑫铭.基于虚拟试验的汽车前碰撞安全气囊防护效率的研究[D].湖南大学车辆工程,2006.
[106]Wang Z, Chen F, Li X. Comparative Analysis and Pedestrian Simulation Evaluation on Emergency Evacuation Test Methods for Urban Rail Transit Stations[J]. PROMET-Traffic\&Transportation,2012,24(6):535-542.
[107]Zijia W, Feng C, Wu D. Modification of the Platform Width Calculation Method of Urban Rail Transit:1st International Conference on Railway Engineering, Beijing, China,2010[C].