基于MAS的客运专线交通枢纽行人交通微观仿真研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
中国高速铁路建设举世瞩目。随着客运专线的建设,在一些大中城市已经形成了综合性的交通枢纽,如北京南站、上海南站、广州南站等。这些交通枢纽存在空间结构复杂,枢纽内客流量大、客流成份复杂、疏散空间受限等特点。客流在枢纽内会如何使用各种设施?哪些设施是制约客流集散的主要瓶颈?这些瓶颈如何改善?对于枢纽的服务水平、安全等级以及枢纽内设施的利用率如何评估?传统的静态客流预测及枢纽评估分析方法已经不能很好地回答这些问题。如能解决这些问题,将为既有和在建大型综合交通枢纽的评估提供技术保障和理论指导。本文基于以上这些问题,结合作者正在从事的国家863课题(2009AA11Z207),对综合交通枢纽行人交通仿真系统进行研究设计。
     首先,本文对国内外的多Agent系统及交通仿真现状进行了详细的综述。在详细介绍Agent的特征、体系结构、Agent司的通信模型和通信语言、消息结构等的基础上,为了全局通信的方便性和准确性,创建了适合本系统的基于本体的交通枢纽知识共享模型。
     其次,根据交通枢纽行人交通仿真的需要,对交通枢纽设施的服务特性进行了研究,根据实地调研的数据,给出了设施服务时间分布规律。由于枢纽内行人的产生规律是否符合现实,对仿真数据的可靠性和实用性起着关键作用,作者基于大量的调研数据,构建出了符合复合负指数分布的客流产生模型。
     接着,对交通枢纽行人交通微观仿真的行人运动模型及行人路径选择模型进行了研究。对于行人在交通枢纽内的运动模型—社会力模型,作者进行了完善和改进。对于在单纯的社会力作用下行人的重叠问题,设计出了切实可行的重叠消除算法;对于在多出口情况下存在的客流分布严重不均衡的问题,作者扩充了出口吸引力的概念,设计出了针对不同吸引力的概率选择模型,实验证明,这种改进效果显著。对于行人在运动过程中的路径选择行为,作者首先对这种路径选择进行了层次化分,然后依据效用最优理论,针对行人在执行层的走行行为创建了路径选择模型。
     随后,基于以上的Agent理论、枢纽设施服务规律、客流产生规律以及行人运动模型和路径选择规律,构建枢纽仿真所需各Agent,并以各Agent为构件,建立了基于Agent的交通枢纽仿真系统。本系统的普适性和可移植性都比较好,尤其是Agent理论的引入,更是使系统以及行走在其中的行人Agent的个性化设置可以方便快捷得实现。
     最后,以北京南站为例,构建了仿真系统,并对正常情况和客流加压情况下分别进行了仿真实验。这些仿真数据对南站的日常管理及危机预防有着重要的参考意义。
In China, the construction of the high-speed railway is remarkable. With the construction of Passenger Dedicated Line (PDL), some comprehensive transportation hubs have already formed in some major cities such as the Beijing South Railway Station, the Shanghan South Railway Station and the Guangzhou South Railway Station. With regard to these stations, there are some characteristics such as the space structure is complex, the passenger flow is large, the passenger constitute is complex, and the evacuating space is limited. In the hubs, passengers how to use the facilities? Which facilities are bottleneck of evacuation? How to improve the bottlenecks? How to evaluate the service level, the security level, and the utilization rate of the hubs? The traditional methods of forecasting passenger flow and evaluating and analyzing the hubs are unapplicable yet. How to resolve the problems, will provide technology safeguard and theoretical support for evaluating the hubs. Based on the problems above, combined with the project of the National High-Tech R&D Program of China (Grant No.2009AA11Z207) the author is engaging in, the paper primarily research and design the traffic hub pedestrians'simulation system.
     Firstly, in this paper, a detailed overview of multi-Agent systems and traffic hub simulation at home and abroad is given, based on that, characteristics and structures of Agent together with the structure of multi-Agent system are introduced, and then, communication model, communication language between Agents and message structures are presented. For the convenience and accuracy of the global communication, a transportation hub knowledge sharing model which is based on the ontology and suitable for system is established.
     Secondly, According to the need of traffic hub pedestrians' simulation, the author researched the service characteristics of the traffic hub facilities, and then, based on the field survey data, obtained the service time distribution of the facilities. It is significant to the reliability and the practicability of the simulation data that the produce rule of the traffic hub pedestrians is in line with the reality. Based on plenty of investigation data, the author establishes the model of the passenger flow produce rule—composite negative exponent distribution.
     Thirdly, the author researched on the movement model and the route choice model of the pedestrians in the traffic hub which can be applied to the micro-simulation system. The author firstly perfected and improved the movement model of pedestrians in the traffic hub. With regard to the problem of pedestrians overlapping, a practical and feasible overlapping elimination algorithm is given About the problem of serious imbalance of passenger flow when several exits available, the autor expanded the concept of exit attractive force, and then a probability model is introduced aimed at different attractive force. An experiment proved that the improvement effect is remarkable. With a view to the route choice of pedestrians in the traffic hub, firstly, a hierarchical method is used, and then, a route choice model is established in according to the utility optimal theory.
     And then, based on the agent theory, service time distribution of the traffic facilities, the passenger flow produce rule, the pedestrians'movement model, pedestrians' route choice rule, Agents suitable for the simulation are constructed, and a Agents based simulation system is established. The universality and the portability are all excellent, especially after the import of the Agent theory, the customization of the traffic hub which will be simulated and the pedestrians moving in the hub can be achieved conveniently and quickly.
     Finally, take the Beijing South Station as an example, based on the previous functional agents, a simulation system is established and experiments are carried out for verification. The simulation data is meaningful to the Beijing South Station to manage the passengers and to prevent the crisis.
引文
[1]许炜强,基于全面造价管理原理的高速铁路造价控制研究[D].硕士学位论文,成都,西南交通大学,2010.
    [2]http://www.santafe.edu
    [3]http://www.swarm.org
    [4]http://www.c3.lanl.gov/-rocha/complex/index.htm
    [5]http://www.complex.org/
    [6]Namatame A. Agent-Based simulation. Dept. of Computer Science, National Defense Academy, Yolosuka, JAPAN.
    [7]Green D G. Hierarchy, complexity and Agent based models. In Our Fragile World:Challenges and Opportunities for Sustainable Development. UNESCO, Paris.
    [8]Marcenac P. Emergence of Behaviors in Natural Phenomena Agent Simulation, in Proceedings of the Third International Conference on Complex Systems:From Local Interactions to Global Phenomena, Eds R Stocker, H Jelinek, Bohdan Durnota and T Bossomaier, pp.284-289, Albury, Australia,1996.
    [9]Marcenac P, Giroux S, Grasso J R, Lahaie F. Simulating Emergent Behaviors:An Application to Volcanoes. In Proceedings of Summer Computer Simulation Conference, Portland, OR, July 1996.
    [10]Calderoni S, Marcenac P. Emergence of Earthquakes by Multi-Agent Simulation. In Proceedings of European Simulation Multi-Conference, ESM'97, Istambul, Turquey, SCS int. Publishers, pp.665-669,1997.
    [11]Multi Agent Simulation. http://www.maths.ox.ac.uk/-sumpter/beesim/index.html
    [12]Franklin S, Graesser A. Is it an Agent, or just a program? A Taxonomy for autonomous Agent. In:Proceedings of the Third international Workshops on Agent Theories, Architectures, and Language, Springer-Verlag,1996:62-71.
    [13]Wooldridge M J. Agent-based Software Engineering. IEE Proc. Software Engineering.1997, 144(1):26-37.
    [14]Shoham Y. Agent-oriented programming. Artificial Intelligence,1993,60:51-92.
    [15]Lane D M, Mcfadzean A G. Distributed problem solving and real-time Mechanisms in robot architectures. Engineering Application intelligence,1994,7(2):105-117.
    [16]范玉顺、曹军威编著,多代理系统理论、方法与应用,第1版,北京:清华大学出版社、施普林格出版社,2002.1-4.
    [17]Bond,A.H., Gasser,L. Readings of Distributed Artificial Intelligence. Morgan Kaufmann,1988.
    [18]Ljungberg, M., Lucas, A. The OASIS air traffic management system, PRICAI'92, Seoul, Korea,1992,1003-1009.
    [19]Lux, Steiner, D. D. Understanding cooperation:an Agent's perspective. In:Proc. Of the First International Conference on Multi-Agent Systems, San Francisco,1995.
    [20]Bonasso, Kortenkamp, Miller and Slack. Experiences with an architecture for intelligent, reactive Agents. In:Intelligent Agents-Pro. Of the 1995 Workshop on Agent Theories, Architectures, and Language(ATAL-95),1995.
    [21]Jennings, N. R. Controlling cooperative problem solving in industrial multi-Agent systems using. Artificial Intelligence,1995,Vol.74(2).
    [22]Etzioi, O., Weld, D. A softbot-based Interface to the Internet. Communications of ACM,1994, 37,7
    [23]Shi, Zhongzhi, Wei Li, Xiaoli Li, Ho Cao. Distributed Information Retrieval Agent JMAT. Hong Kong, IAT'99,1999.
    [24]潘谦红.分布式信息检索的研究与应用.博士学位论文,中国科学院计算机研究所,1999
    [25]Hankin B D, Wright R A. Passenger flow in subways. Operational Research Quarterly 1958,9:81-88
    [26]Fruin J J. Designing for pedestrians:a level-of-service concept. Highway Research Board, Washington, DC. In Highway Research Record Number 355:Pedestrians, Prentice Hall Inc.[S]. New Jersey.1969.
    [27]Mori M, Tsukaguchi H.A new method for evaluation of level of service in pedestrian facilities. Transportation Research A.1987,21:223-234.
    [28]Polus A, Schofer J L, Ushpiz A. Pedestrian flow and level of service. Journal of Transportation Engineering.1983,109:46-56.
    [29]Brilon W, Gropmann M,Blanke H. Methods for the calculation of the capacity and quality of traffic flow in streets. Ministry of Traffic, Bonn, chapter 13,1993.
    [30]Davis D G, Braaksma J P. Adjusting for luggage-laden pedestrians in airport terminals. Transportation Research A.1988,22:375-388.
    [31]Predtetschenski W M, Milinski A I. Pedestrian flow in buildings:calculation methods for design. 1971 (in Gennan).
    [32]TRB. "Pedestrians", in Highway Capacity Manual special report 209. Transportation Research Board, Washington, DC. Chapter 13,1985.
    [33]何民,混合交通流微观仿真关键技术研究[博士学位论文],北京,北京工业大学,2003.
    [34]Batty M, Jiang B, Thurstain-Goodwin M Local Movement:Agent-Based Models of Pedestrian Flows. Working Paper 4, Centre for Advanced Spatial Analysis, University College, London; available at http://www.case.ucl.ac.uk/publications/workingpager.
    [35]Thorsten Schelhorn, David O'Sullivan, Muki Haklay, Mark Thurstain-Goodwin. STREETS:An Agent-Based Pedestrian Model. Working Paper 9, Centre for Advanced Spatial Analysis, University College, London; available at http://www.case.ucl.ac.uk/publications/workingpager.
    [36]D. Helbing, A. Hennecke, V. Shvetsov, and M. Treiber (2002) Micro-and-macro-simulation of freeway traffic. Mathematical and Computer Modelling 35(5/6),517-547.
    [37]Helbing D, Molnar P. Social Force Model for Pedestrians Dynamics [J]. Physical Review E (S1063-651X),1995,51(5):4282-4285.
    [38]Dirk Helbing, Ⅲes Farkas & Tamas Vicsek, Simulating dynamical features of escape panic[J], NATURE, VOL 407,28 SEPTEMBER 2000,487-490
    [39]D. Helbing and B.A. Huberman (1998) Coherent moving states in highway traffic. Nature 396, 738-740.
    [40]Dirk Helbing, Joachim Keltsch, Pater Modelling the Evolution of Human Trail Systems. Nature, 1997,388:47-50.
    [41]A Dussutour, V. Fourcassie, D. Helbing, and J.-L Deneubourg (2004) Optimal traffic organization in ants under crowded conditions. Nature 428,70-73.
    [42]Kukla, R., Kerridge, J., Willis, A. and Hine, J. (2001). PEDFLOW:Development of an Autonomous Agent Model of Pedestrian Flow. Transportation Research Record, USA,1774, 11-17.
    [43]孙晋文.基于Agent的智能交通控制策略与可视化动态仿真研究[博士学位论文].北京:中国农业大学,2001.12-13.
    [44]严飞.基于Agent和元胞自动机的智能交通仿真研究[硕士学位论文].大连:大连海事大学,2004.7-9.
    [45]刘隽.基于分散自律体系的多Agent客运专线运营调试系统[博士学位论文].北京:铁道科学研究院,2006.5-6.
    [46]Sargent, P. Back to School for a Brand New ABC. In:The Guardian,1992, P28.
    [47]Uhrmacher A M, Gugler K. Distributed, Parallel Simulation of Multiple, Deliberative Agents. Proceedings of the 14# Workshop on Parallel and Distributed Simulation,2000.
    [48]Uhrmacher A M, Tyschler P, et al. Modeling and Simulation of Mobile Agents. Future Generation Computer Systems,2000.
    [49]Agent Working Group. Agent Technology Green Paper. Object Management Group Document ec/99-08-06 version 0.8,1999
    [50]Anderson J, Evans M. A Generic Simulation Systems for Intelligent Agent Designs. Applied Artificial Intelligence, Volume 9, Number 5, October,1995, pp.527-562.
    [51]Dooley K, Corman S. Agent-based Generic and Emergent Computational models of Complex Systems, under review at Encyclopedia of Life Support Systems.
    [52]Wooldridge M J, Jennings N R. Agent Theories, Architectures, and Language:A Survey, in Wooldridge and Jennings Eds. Intelligent Agents, ppl-22, Berlin:Springer-Verlage,1995.99 Appendix A Sample Cable Amplifier Network Topology Table A.1:Portion of topology from the cable amplifier network in,1995.
    [53]Ting-Peng Liang, Jin-Shang Huang. A Framework for Applying intelligent Agents to electronic trading. Decision Support Systems,2000,28:305-317
    [54]Lee K J, Chang Y S, Lee J K. Time-bound negotiation framework for electronic commerce Agents. Decision Support Systems,2000:319-331.
    [55]Jennings N R, Corera J M, et al. Developing Industrial Multi-Agent System. In:Proceedings of the First International Conference on Multi-Agent Systems, (ICMA-95),423-430.
    [56]王红卫.建模与仿真,北京:科学出版社,2002.193-207.
    [57]洪流,基于MAS的协调知识与协调策略研究,[博士学位论文],华中科技大学,2007.6
    [58]王岚,基于Multi-Agent的分布式应用系统研究,[硕士学位论文],北京,首都经济贸易大学,2004.3
    [59]唐超,面向应用需求的软件智能体系统研究与开发[D].硕十学位论文,湖北,华中科技大学,2002.
    [60]李海滨,莫藏,唐超,基于多智能体系统的面向对象本体研究[J],计算机工程与应用,2003,39(22),81-83.
    [61]Gilmore J F, Roth S P, Tynor SD.A blackboard system for distributed problem solving [M]. Blackboard Architectures and Applications. Academic Press, San Diego,CA,1989
    [62]Yilmaz C. Daytona B FL. Orlando FL. A dynamic knowledge exchange tool for intelligent Agents [C]. The Third CLIPS Conference at NASA Johnson September 1994
    [63]黄波,倪重匡,一种基于黑板模型的智能决策系统生成器的结构设计,[J],计算机研究与发展,Vol.34,No.5,1997,P382-386
    [64]夏胜国.公交枢纽客流特征分析及行人路径交通分配研究[D].硕士学位论文,上海:同济大学,2008.
    [65]陆化普.交通规划理论与方法[M].北京:清华大学出版社,1998.
    [66]何宇强,毛保华,陈绍宽等.铁路客运站旅客最高聚集人数计算方法研究[J].铁道学报,2006,28(1):6-11.
    [67]林震,杨浩.出行者心理与交通信息系统存在问题分析[J].公路,2002,50(12):90-93.
    [68]Osaragi T. Modeling of pedestrian behavior and its applications to spatial evaluation [C]. In Proceedings of the third international joint conference on autonomous agents and multi-agent systems,2004.
    [69]Joseph S. Milazzo Ⅱ, Nagui M. Rouphail, et al. Quality of Service for Uninterrupted Pedestrian Facilities in the 2000 Highway Capacity Manual. The 78th Annual Meeting of the Transportation Research Board,1999.
    [70]Joseph S. Milazzo Ⅱ, Nagui M. Rouphail, et al. Quality of Service for Interrupted Pedestrian Facilities in the 2000 Highway Capacity Manual. The 78th Annual Meeting of the Transportation Research Board,1999.
    [71]Jake L. Paul. A personal perspective on research, consulting and codes standards development in fire-related human behavior,1969-1999, with an emphasis on space and time factors. Fire and Materials, Vol.23,1999, pp.265-272.
    [72]Jake L. Paul. Suggestions on evacuation models and research questions. Proceedings of 3rd international symposium on human behavior in fires,2004, Interscience communications, London, pp.23-33.
    [73]Seth B. Yound, Evaluation of pedestrian walking speeds in airport terminals. The 78th Transportation Research Board, Washington DC,1999.
    [74]Thomas F. Fugger, et al. Analysis of pedestrian gait and percepetion/reaction at signal-controlled crosswalk intersections. The 79th Transportation Research Board, Washington DC,2000.
    [75]Transportation Research Board. Highway Capacity Manual. TRB, National Research Council, Washington DC,2000.
    [76]Robert E. Dewar and Paul L. Olson. Human Factors in Traffic Safety. Tucson, USA:Lawyers & Judges Publishing Company, Inc.2005.
    [77]北京工业大学,同济大学,南京工学院(东南大学),交通工程讲义,1983.
    [78]Institute of Transportation Engineers. Transportation and Traffic Eengineering Handbook
    [79]S W Cellular and Automata and Complexity [M].Baltimore:Addison-Wesley Publishing Company,1994:74-75.
    [80]W S. Theory and Application of Cellular Automata [M].Singapore:1986.
    [81]B. Chopard and M.Droz. Cellular Automata Modeling of Physical Systems//祝玉学,赵学龙(泽),物理系统的元胞自动机模拟,北京:清华大学出版社(2003)
    [82]B C L. Transportation Analysis Simulation System(TRANSIMS). [R]. Los Alamos, NM,USA: 1999
    [83]Nagel,kai H J H. Deterministic Models for Traffic Jams [J]. Physica A.1993:254-269
    [84]Helbing D.A Fluid-dynamic Model for the Movement of Pedestrians [J].Complex Systems (S0891-2513),1992,6(5):391-415.
    [85]Taras I.Lakoba, D.J.Kaup, Neal M.Finkelstein, Modifications of the Helbing-Molnar-Farkas-Vicsek Social Force Model for Pedestrian Evolution[J],SIMULATION, VOL.81, Issue 5, May 2005 339-352
    [86]Yuan Weifang, Tan Kang Hai, A novel algorithm of simulation multi-velocity evacuation based on cellular automata modeling and tenability condition[J], Physica A 379(2007)250-262
    [87]S.P. Hoogendoorn, P.H.L.Bovy, Pedestrian rout-choice and activity scheduling theory and models, Transportation Research Part B 38 (2004) 169-190.
    [88]Hoogendoorn S.P., Bovy P.H.L. Pedestrian Travel Behavior Modeling [J]. Transportation and Planning Section, Delft University of Technology, Delft, The Netherlands,2005(5):193-216.
    [89]Mitchell D.H., Smith M.G.J. Topological network design of pedestrian networks [J]. Transportation Research Part B,2001,35:107-135.
    [90]郑大钟,赵千川.离散时间动态系统[M].北京:清华大学出版社,2001
    [91]Cruz F.R.B., MacGregor Smith J., Medeiros R.O. An M/G/C/C state-dependent network simulation model [J]. Computers & Operations Research,2005,32:919-941.
    [92]Jain R, MacGregor Smith J. Modeling vehicular traffic flow using M/G/C/C state dependent queueing models [J]. Transportation Science,1997,31(4):24-36.
    [93]Thumsi V, Macgregor Smith J. M/G/C/C state-dependent queueing models [J]. Transportation Science,1997,31(3):24-36.
    [94]唐应辉,唐小我,排队论---基础与分析技术,北京,科学出版社,2006.9,1-2.
    [95]何宇强,毛保华,丁勇等,铁路客运站最高聚集人数模拟计算机研究,系统仿真学报,2006年1月,P213-224
    [96]李得伟,韩宝明,铁路客运专线车站乘客集散微观仿真模型,交通运输工程学报,2009年2月,P83-86
    [97]高春霞,董宝田,李乾,北京南站客流分析,物流技术,2010年12月,P18-20
    [98]John.H Mathews,Kurtis D Fink,数值方法(MATLAB版),[M],北京,电子工业出版社,2005:195-215
    [99]苏金明,张莲花等,MATLAB工具箱应用,[M],北京,高等教育出版社,2002:62-85
    [100]姜启源,谢金星,叶俊,数学模型,[M],北京,高等教育出版社,2003:308-316
    [101]乔立山,王玉兰,曾锦光,实验数据处理中曲线拟合方法探讨,[J],成都理工大学学报(自然科学版),2004,31(1):91-95.
    [102]唐家德,基于MATLAB的非线性曲线拟合,[J],计算机与现代化,2008.6:15-19.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700