基于多智能体的交通流微观仿真
|
摘要
在智能交通系统中，交通流仿真软件是人们评估交通管控策略、验证交通流理论中新的算法、和培训交通管理人员的有效工具。同时，多智能体系统，作为计算机科学与分布式人工智能领域的最新进展，提供了研究像城市交通系统这样的复杂系统一个新的途径。本文建立了一个基于多智能体的城市交通流微观仿真系统，主要展开了以下研究：
·确立了基于多智能体的交通流微观仿真模型的三层体系结构，分别为车辆智能体、路段智能体和路网智能体。车辆智能体仿真路网中车辆的运行，路段智能体收集各种状态信息，路网智能体控制交通系统的各个组成部分。通过三部分的协调与合作，仿真交通系统中从车辆运行的微观行为到各种控制策略的实施全过程；
·利用多智能体系统理论对车辆的微观换道行为重新建模。考虑到车辆在变换车道过程中的竞争与合作关系，并对这种竞争与合作产生的原因，合作的方式进行了讨论；
·使用面向对象程序设计语言开发了基于多智能体的交通流微观仿真软件。包括路网描述模块、车辆行驶模块、行驶控制模块、监控与记录模块等；
·在程序设计中广泛使用设计模式。各种控制模块不是“硬编码”在系统中，增强了系统的可重用性、灵活性和可扩展性。
Traffic problem is an important problem all over the world, it has seriously influenced the society, how to solve it is the key problem people pay attention to, now, "intelligent transportation system", which aims to solve the traffic problem using the advanced science and technology, is becoming the research emphasis in traffic fields. In ITS, traffic simulation system is the most efficient tool in the operation of transportation systems. Through simulate the real world's traffic flow, traffic simulation system can test traffic management strategies, validate traffic control algorithm, help to train new engineer, and so on.
Meanwhile, multi-agent system, a new paradigm of computer and distributed artificial intelligence, provides a new way for the research of such complicated systems as urban traffic system. This research develops an agent-based microscopic traffic simulation system, which focus on:
? Establish an agent-based three-level model architecture on traffic flow simulation system, which are vehicle agent, segment agent and road network agent. Vehicle agent simulates vehicle's microscopic behavior, while segment agent gather all information throughout the road networks, and road network agent control the transportation systems. Through three parts' coordination and cooperation, the traffic simulation system could model many traffic behaviors from vehicle moving to traffic control strategies.
? Re-model the vehicle's lane-changing behavior through the utilization of multi-agent system theory. Analyze compete and cooperate relationship between each vehicle when lane-changing behavior occurs. Also, some manners of cooperation are discussed.
? Develop an agent-based traffic simulation software, which implemented in C++ using object-oriented programming, includes road network depict module, vehicle moving module, moving control module, surveillance and record module, etc.
? Design patterns are widely used in programming, so various of control modules are not "hard-coded" in the system. By doing so, the
software system could be more flexible, extendable and ultimately reusable.
·确立了基于多智能体的交通流微观仿真模型的三层体系结构，分别为车辆智能体、路段智能体和路网智能体。车辆智能体仿真路网中车辆的运行，路段智能体收集各种状态信息，路网智能体控制交通系统的各个组成部分。通过三部分的协调与合作，仿真交通系统中从车辆运行的微观行为到各种控制策略的实施全过程；
·利用多智能体系统理论对车辆的微观换道行为重新建模。考虑到车辆在变换车道过程中的竞争与合作关系，并对这种竞争与合作产生的原因，合作的方式进行了讨论；
·使用面向对象程序设计语言开发了基于多智能体的交通流微观仿真软件。包括路网描述模块、车辆行驶模块、行驶控制模块、监控与记录模块等；
·在程序设计中广泛使用设计模式。各种控制模块不是“硬编码”在系统中，增强了系统的可重用性、灵活性和可扩展性。
Traffic problem is an important problem all over the world, it has seriously influenced the society, how to solve it is the key problem people pay attention to, now, "intelligent transportation system", which aims to solve the traffic problem using the advanced science and technology, is becoming the research emphasis in traffic fields. In ITS, traffic simulation system is the most efficient tool in the operation of transportation systems. Through simulate the real world's traffic flow, traffic simulation system can test traffic management strategies, validate traffic control algorithm, help to train new engineer, and so on.
Meanwhile, multi-agent system, a new paradigm of computer and distributed artificial intelligence, provides a new way for the research of such complicated systems as urban traffic system. This research develops an agent-based microscopic traffic simulation system, which focus on:
? Establish an agent-based three-level model architecture on traffic flow simulation system, which are vehicle agent, segment agent and road network agent. Vehicle agent simulates vehicle's microscopic behavior, while segment agent gather all information throughout the road networks, and road network agent control the transportation systems. Through three parts' coordination and cooperation, the traffic simulation system could model many traffic behaviors from vehicle moving to traffic control strategies.
? Re-model the vehicle's lane-changing behavior through the utilization of multi-agent system theory. Analyze compete and cooperate relationship between each vehicle when lane-changing behavior occurs. Also, some manners of cooperation are discussed.
? Develop an agent-based traffic simulation software, which implemented in C++ using object-oriented programming, includes road network depict module, vehicle moving module, moving control module, surveillance and record module, etc.
? Design patterns are widely used in programming, so various of control modules are not "hard-coded" in the system. By doing so, the
software system could be more flexible, extendable and ultimately reusable.
引文
[1] Sharon Adams Boxill, Lei Yu, An Evaluation of Traffic simulation Models for Supporting ITS Development, Report No. SWUTC/00/167602-1. 2000,8, p114.
[2] 张安胜，董敏，林建臻。城市道路交通流仿真算法研究，计算机工程，2002，8：102—104
[3] N.H. Gartner, C. Stamatiadis, and P.J. Tarnoff. Development of advanced traffic signal control strategies for IVNS: A multi-level design . Transportation Research Record, (1494), 1995
[4] Matti Pursula, Simulation of Traffic Systems - An overview, Journal of Geographic Information and Decision Analysis. vol 3, no.1: 1-8
[5] Masroor Hasan, Mithilesh Jha, Moshe Ben-Akiva. Evaluation of Ramp Control Algorithms Using Microscopic Traffic Simulation. Transportation Research Part C: Emerging Technologies, 2002, 10(3): 229-256
[6] J．A．斯普里特，计算机辅助建模和仿真，北京：科学出版社，1991．4：85-90
[7] 毛保华，杨肇夏，陈海波．道路交通仿真技术与系统研究．北方交通大学学报，2002，10：37-46
[8] Kallberg, H Traffic Simulation (in Finish). Licentiate thesis, Helsinki University of Technology, 1971.
[9] Jennings, N.R. and Wooldridge, M.J. Agent technology: foundations, applications, and markets. Springer-Verlag, Berlin, Germany, 1998
[10] AIMSUN Microscopic Traffic Simulator: A Tool For the Analysis and Assessment of ITS Systems, http:// www. aimsun, com/
[11] Moshe Ben-Akiva, Michel Bierlaire, Naris Koutsopoulos, DynaMIT: a simulation-based system for traffic prediction, paper presented at the DACCORD Short Term Forecasting Workshop, Delft, the Netherlands, 1998.
[12] 段进宇，高速道路入口匝道范围交通仿真研究与入口最短控制研究，[博士学位论文]，上海，同济大学，1997．
[13] 邹智军，计算机仿真法研究主／次有限控制T型交叉口通行能力和延误，[硕士论文]，上海，同济大学，1994．
[14] 邹智军，杨东援，微观交通仿真中的车道变换模型，中国公路学报，2002，4，p105-108
[15] 邹智军，杨东援，城市交通仿真试验系统的面向对象开发，系统仿真学报，
2002．7，p844-848
[16] 邹智军，城市道路交通仿真研究，[博士学位论文]，上海，同济大学，2000
[17] Kai Nagel. Distributed intelligence in large scale traffic simulations on parallel computers. Collective Cognition: Mathematical Foundations of Distributed Intelligence, Santa Fe Institute, 2002.
[18] M. McDonald, J. Wu, M. Brackstone, Development of a Fuzzy Logic Based Microscopic Motorway Simulation Model, In the Proceedings of the IEEE Conf. on Intelligent Transportation Systems (ITSC97).
[19] 马寿峰，贺国光，刘豹，一种通用的城市道路交通流微观仿真系统的研究，系统工程学报，1998，12，p8-15．
[20] 冯蔚东，贺国光，刘豹，交通流理论评述，系统工程学报，1998，9：p71-82
[21] Ross P. Traffic dynamics. Transportation Research. 1988, 22B:p421-435
[22] Papa Georgiou M. Macroscopic modeling of traffic flow on the BOULEVARD PERIPHERIQUE. in Paris, Transportation Research, 1989,23B(1)
[23] Payne H J. Models of freeway traffic and control. Mathematical Methods of Public Systems. 1971,1(1):p51-61
[24] 欧海涛，张文渊，张卫东，许晓呜，城市交通控制研究的新发展，信息与控制，2000．10，p441-451．
[25] Erich Gamma, Richard helm, Ralph Jonson, John Vlissides, Design Patterns: Elements of Reusable Object-oriented Software. Addison Wesley Longman, 1995
[26] Shoham, Y. An overview of agent-oriented programming. In Software agents. Bradshaw, J.M editor, AAAI Press, Cambridge, Massachusetts, 1997
[27] Jacques Ferber. Multi-Agent Systems: An Introduction to distributed artificial intelligence. New York: Addison-Wesley. 1999.9
[28] Bradshaw, Software agents, AAAI Press, Cambridge, Massachusetts, 1997
[29] 刘金琨，尔联洁，多智能体技术应用综述，控制与决策，2001．3，p133—140
[30] B. Burmeister, A. Haddadi, G. Matylis. Applications of multi-agent systems in traffic and transportation. IEEE Trans on Software Engineering, 1997, 144(1): p51-60
[31] C. V. Goldman, J.S. Rosenschein. Mutual supervised learning in multi-agent systems. Proc of IJCAI'95 Workshop. Berlin, 1996:p85-96
[32] N. V. Findler. Distributed control of collaborating and learning
expert systems for street traffic signals. IFAC Distributed Intelligence Systems. Pergamon Press, 1991: p125-130.
[33] G. Adorni, A. Poggl. Route guidance as a just-in-time multi-agent task. Applied Artificial intelligence. 1996,10(2): p95-120.
[34] K. H. Funk, J. H. Lind. Agent-based pilot-vehicle inter-face: concept and prototype. IEEE Trans on System, Man and Cybernetics, 1992,22(6):p1309-1322.
[35] G. Vernazza, R. Zunino. A distributed intelligence methodology for railway traffic control. IEEE Trans on Vehicular Technology, 1990,39(3):p263-270.
[36] Y. Jin, T. Koyama, Z. J. Zhang. The marine traffic control systems as a distributed problem solving network. Proc IEEE int Cnf on Systems, man and cybernetics. 1990: p876-881.
[37] Nicholas R. Jennings, On agent-based software engineering, Artificial Intelligence, 117(2000), 277-296.
[38] Krishna M. Kavi, Mohamed Aborizka, David Kung, A Framework For Designing, Modelling and Analyzing Agent Based Software Systems, In Proceedings of 5th International Conference on Algorithms & Architectures for Parallel Processing, October 23-25, Beijing, China, 2002.
[39] Maria Bruno Marietto, Nuno David, Jaime Simao Sichman and Helder Coelho, Requirements Analysis of Agent-based Simulation Platforms: State of the Art and New Prospects, In: Proceedings 3rd. International Workshop on Multi-Agent Based Simulation (MABS'02), Bologna, Italy.
[40] Michael Wooldridge, Nicholas R. Jennings, David Kinny: The Gaia Methodology for Agent-Oriented Analysis and Design. Autonomous Agents and Multi-Agent Systems, 3, pp285-312, 2000
[41] Nikos Manouselis, Pythagoras Karampiperis, Elias Kosmatopoulos: A Multi-Agent, Microscopic Traffic Simulation Architecture Incorporating Entities With Adaptive Behaviors. Proceedings of the 1st Human Centered Transportation Simulation Conference, Iowa, November 2001.
[42] J. L. Bowman, M.E. Ben-Akiva: Activity-based disaggregate travel demand model system with activity schedules. Transportation Research, Part A 35(2000): p1-28.
[43] Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, Rabi
Mishalani, Demand Simulation For Dynamic Traffic Assignment, In the Proceedings of the 8th IFAC/IFIP/IFORS symposium on transportation systems, Chania, 1997.
[44] 王正武，0D估计双层规划模型扩展及求解，[硕士学位论文]．长沙，长沙交通学院，2003．
[45] Haris N. Koutsopoulos, Amalia Polydoropoulou, Moshe Ben-Akiva: Travel simulators for data collection on driver behavior in the presence of information. Transportation Research, Part C. Vol 3, No. 3 p143-159, 1995.
[46] Alexandros Moukas, Konstantinos Chandrinos and Pattie Maes: Trafficopter: A Distributed Collection System for Traffic Information.
[47] 张廷楷等，道路路线设计，同济大学出版社，1990，9
[48] Chandler R. E, Herman R, Montroll E. W: Traffic dynamics: studies in car following. Operations Research, 1958, 6, p165-184
[49] Edie L. C. Car following and steady state theory for non-congested traffic. Operations Research, 1961, 9, p66-76
[50] Peter Hidas. Modeling lane changing and merging in microscopic traffic simulation. Transportation Research, Part C, 2002,10:p351-371
[51] Peter Hidas, Kamran Behbahanizadeh, SITRAS: A Simulation Model for ITS Applications, Proceedings of the 5th World Congress on Intelligent Transport Systems, Seoul,Korea, 1998.8
[52] Stefano Pallottino, Maria Grazia Scutella, Shortest Path Algorithms In Transportation Models: Classical and Innovative Aspects, In Equilibrium and Advanced Transportation Modelling, Kluwer, p245-281, 1998.
[53] Boris V. Cherkassky, Andrew V. Golderg, Tomasz Radzik, Shortest Paths Algorithms: Theory and Experimental Evaluation, In Proceedings of the Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, p516-525, Arlington, Virginia, 23-25 January 1994.
[54] Jan Husdal, Fastest Path Problems in Dynamic Transportation Networks,http://www. husdal. com/mscgis/research. htm
[55] Ismail Chabini, Discrete Dynamic Shortest Path Problems In Transportation Applications: Complexity and Algorithms With Optimal Run Time, Transportation Research Record 1645, 1998.
[56] F. Benjamin Zhan, Charles E. Noon, shortest Path Algorithms: An
Evaluation using Real Road Networks, Transportation Science, Vol. 32, 1998,2, p65-72.
[57] F. Benjamin Zhan, Three Fastest Shortest Path Algorithms on Real Road Networks: Data Structures and Procedures, Journal of Geographic Information and Decision Analysis, vol. 1, no.l, p. 69-82.
[58] Karen Zita Haigh, Manuela Velso, Route Planning by Analogy, In the proceedings of the International conference on Case-based Reasoning, Portugal, 1995.
[59] Seth Rogers, Claude-Nicolas Fiechter, Pat Langley, An Adaptive Interactive Agent for Route Advice, In the proceedings of the Third International Conference on Autonomous Agents, Seattle, 1999,5. p 198-205.
[60] Kai Nagel: Multi-Agent Transportation Simulation, 2003.6, http://www, sim. inf. ethz. ch/papers/book/html/
[61] J. Wahle, O. Annen, Ch. Schuster, L. Neubert, M. Schreckenberg: A Dynamic Route Guidance System Based on Real Traffic Data. European Journal Operational Research 131 (2001), 302-308
[62] J. Wahle,L. Neubert, J. Esser, M. Schreckenberg: A Cellular Automaton Traffic Flow Model for Online Simulation of Traffic. Parallel Computing 27 (2001), 719-735
[63] Qi Yang, Haris N. Koutsopoulos: A Microscopic Traffic Simulator For Evaluation of Dynamic Traffic Management Systems. Transportation Research. Vol 4, No. 3, pp113-129, 1996
[64] Qi Yang, A Simulation Laboratory for Evaluation of Dynamic Traffic Management Systems. Ph.D. thesis report, Massachusetts Institute of Technology, June 1997.
[65] Serge P. Hoogendoorn, State-of-the-art of Vehicular Traffic Flow Modelling, Journal of Systems and Control Engineering, Special Issue on Road Traffic Modelling and Control, vol. 215, 2001, pp283-304.
[2] 张安胜，董敏，林建臻。城市道路交通流仿真算法研究，计算机工程，2002，8：102—104
[3] N.H. Gartner, C. Stamatiadis, and P.J. Tarnoff. Development of advanced traffic signal control strategies for IVNS: A multi-level design . Transportation Research Record, (1494), 1995
[4] Matti Pursula, Simulation of Traffic Systems - An overview, Journal of Geographic Information and Decision Analysis. vol 3, no.1: 1-8
[5] Masroor Hasan, Mithilesh Jha, Moshe Ben-Akiva. Evaluation of Ramp Control Algorithms Using Microscopic Traffic Simulation. Transportation Research Part C: Emerging Technologies, 2002, 10(3): 229-256
[6] J．A．斯普里特，计算机辅助建模和仿真，北京：科学出版社，1991．4：85-90
[7] 毛保华，杨肇夏，陈海波．道路交通仿真技术与系统研究．北方交通大学学报，2002，10：37-46
[8] Kallberg, H Traffic Simulation (in Finish). Licentiate thesis, Helsinki University of Technology, 1971.
[9] Jennings, N.R. and Wooldridge, M.J. Agent technology: foundations, applications, and markets. Springer-Verlag, Berlin, Germany, 1998
[10] AIMSUN Microscopic Traffic Simulator: A Tool For the Analysis and Assessment of ITS Systems, http:// www. aimsun, com/
[11] Moshe Ben-Akiva, Michel Bierlaire, Naris Koutsopoulos, DynaMIT: a simulation-based system for traffic prediction, paper presented at the DACCORD Short Term Forecasting Workshop, Delft, the Netherlands, 1998.
[12] 段进宇，高速道路入口匝道范围交通仿真研究与入口最短控制研究，[博士学位论文]，上海，同济大学，1997．
[13] 邹智军，计算机仿真法研究主／次有限控制T型交叉口通行能力和延误，[硕士论文]，上海，同济大学，1994．
[14] 邹智军，杨东援，微观交通仿真中的车道变换模型，中国公路学报，2002，4，p105-108
[15] 邹智军，杨东援，城市交通仿真试验系统的面向对象开发，系统仿真学报，
2002．7，p844-848
[16] 邹智军，城市道路交通仿真研究，[博士学位论文]，上海，同济大学，2000
[17] Kai Nagel. Distributed intelligence in large scale traffic simulations on parallel computers. Collective Cognition: Mathematical Foundations of Distributed Intelligence, Santa Fe Institute, 2002.
[18] M. McDonald, J. Wu, M. Brackstone, Development of a Fuzzy Logic Based Microscopic Motorway Simulation Model, In the Proceedings of the IEEE Conf. on Intelligent Transportation Systems (ITSC97).
[19] 马寿峰，贺国光，刘豹，一种通用的城市道路交通流微观仿真系统的研究，系统工程学报，1998，12，p8-15．
[20] 冯蔚东，贺国光，刘豹，交通流理论评述，系统工程学报，1998，9：p71-82
[21] Ross P. Traffic dynamics. Transportation Research. 1988, 22B:p421-435
[22] Papa Georgiou M. Macroscopic modeling of traffic flow on the BOULEVARD PERIPHERIQUE. in Paris, Transportation Research, 1989,23B(1)
[23] Payne H J. Models of freeway traffic and control. Mathematical Methods of Public Systems. 1971,1(1):p51-61
[24] 欧海涛，张文渊，张卫东，许晓呜，城市交通控制研究的新发展，信息与控制，2000．10，p441-451．
[25] Erich Gamma, Richard helm, Ralph Jonson, John Vlissides, Design Patterns: Elements of Reusable Object-oriented Software. Addison Wesley Longman, 1995
[26] Shoham, Y. An overview of agent-oriented programming. In Software agents. Bradshaw, J.M editor, AAAI Press, Cambridge, Massachusetts, 1997
[27] Jacques Ferber. Multi-Agent Systems: An Introduction to distributed artificial intelligence. New York: Addison-Wesley. 1999.9
[28] Bradshaw, Software agents, AAAI Press, Cambridge, Massachusetts, 1997
[29] 刘金琨，尔联洁，多智能体技术应用综述，控制与决策，2001．3，p133—140
[30] B. Burmeister, A. Haddadi, G. Matylis. Applications of multi-agent systems in traffic and transportation. IEEE Trans on Software Engineering, 1997, 144(1): p51-60
[31] C. V. Goldman, J.S. Rosenschein. Mutual supervised learning in multi-agent systems. Proc of IJCAI'95 Workshop. Berlin, 1996:p85-96
[32] N. V. Findler. Distributed control of collaborating and learning
expert systems for street traffic signals. IFAC Distributed Intelligence Systems. Pergamon Press, 1991: p125-130.
[33] G. Adorni, A. Poggl. Route guidance as a just-in-time multi-agent task. Applied Artificial intelligence. 1996,10(2): p95-120.
[34] K. H. Funk, J. H. Lind. Agent-based pilot-vehicle inter-face: concept and prototype. IEEE Trans on System, Man and Cybernetics, 1992,22(6):p1309-1322.
[35] G. Vernazza, R. Zunino. A distributed intelligence methodology for railway traffic control. IEEE Trans on Vehicular Technology, 1990,39(3):p263-270.
[36] Y. Jin, T. Koyama, Z. J. Zhang. The marine traffic control systems as a distributed problem solving network. Proc IEEE int Cnf on Systems, man and cybernetics. 1990: p876-881.
[37] Nicholas R. Jennings, On agent-based software engineering, Artificial Intelligence, 117(2000), 277-296.
[38] Krishna M. Kavi, Mohamed Aborizka, David Kung, A Framework For Designing, Modelling and Analyzing Agent Based Software Systems, In Proceedings of 5th International Conference on Algorithms & Architectures for Parallel Processing, October 23-25, Beijing, China, 2002.
[39] Maria Bruno Marietto, Nuno David, Jaime Simao Sichman and Helder Coelho, Requirements Analysis of Agent-based Simulation Platforms: State of the Art and New Prospects, In: Proceedings 3rd. International Workshop on Multi-Agent Based Simulation (MABS'02), Bologna, Italy.
[40] Michael Wooldridge, Nicholas R. Jennings, David Kinny: The Gaia Methodology for Agent-Oriented Analysis and Design. Autonomous Agents and Multi-Agent Systems, 3, pp285-312, 2000
[41] Nikos Manouselis, Pythagoras Karampiperis, Elias Kosmatopoulos: A Multi-Agent, Microscopic Traffic Simulation Architecture Incorporating Entities With Adaptive Behaviors. Proceedings of the 1st Human Centered Transportation Simulation Conference, Iowa, November 2001.
[42] J. L. Bowman, M.E. Ben-Akiva: Activity-based disaggregate travel demand model system with activity schedules. Transportation Research, Part A 35(2000): p1-28.
[43] Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, Rabi
Mishalani, Demand Simulation For Dynamic Traffic Assignment, In the Proceedings of the 8th IFAC/IFIP/IFORS symposium on transportation systems, Chania, 1997.
[44] 王正武，0D估计双层规划模型扩展及求解，[硕士学位论文]．长沙，长沙交通学院，2003．
[45] Haris N. Koutsopoulos, Amalia Polydoropoulou, Moshe Ben-Akiva: Travel simulators for data collection on driver behavior in the presence of information. Transportation Research, Part C. Vol 3, No. 3 p143-159, 1995.
[46] Alexandros Moukas, Konstantinos Chandrinos and Pattie Maes: Trafficopter: A Distributed Collection System for Traffic Information.
[47] 张廷楷等，道路路线设计，同济大学出版社，1990，9
[48] Chandler R. E, Herman R, Montroll E. W: Traffic dynamics: studies in car following. Operations Research, 1958, 6, p165-184
[49] Edie L. C. Car following and steady state theory for non-congested traffic. Operations Research, 1961, 9, p66-76
[50] Peter Hidas. Modeling lane changing and merging in microscopic traffic simulation. Transportation Research, Part C, 2002,10:p351-371
[51] Peter Hidas, Kamran Behbahanizadeh, SITRAS: A Simulation Model for ITS Applications, Proceedings of the 5th World Congress on Intelligent Transport Systems, Seoul,Korea, 1998.8
[52] Stefano Pallottino, Maria Grazia Scutella, Shortest Path Algorithms In Transportation Models: Classical and Innovative Aspects, In Equilibrium and Advanced Transportation Modelling, Kluwer, p245-281, 1998.
[53] Boris V. Cherkassky, Andrew V. Golderg, Tomasz Radzik, Shortest Paths Algorithms: Theory and Experimental Evaluation, In Proceedings of the Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, p516-525, Arlington, Virginia, 23-25 January 1994.
[54] Jan Husdal, Fastest Path Problems in Dynamic Transportation Networks,http://www. husdal. com/mscgis/research. htm
[55] Ismail Chabini, Discrete Dynamic Shortest Path Problems In Transportation Applications: Complexity and Algorithms With Optimal Run Time, Transportation Research Record 1645, 1998.
[56] F. Benjamin Zhan, Charles E. Noon, shortest Path Algorithms: An
Evaluation using Real Road Networks, Transportation Science, Vol. 32, 1998,2, p65-72.
[57] F. Benjamin Zhan, Three Fastest Shortest Path Algorithms on Real Road Networks: Data Structures and Procedures, Journal of Geographic Information and Decision Analysis, vol. 1, no.l, p. 69-82.
[58] Karen Zita Haigh, Manuela Velso, Route Planning by Analogy, In the proceedings of the International conference on Case-based Reasoning, Portugal, 1995.
[59] Seth Rogers, Claude-Nicolas Fiechter, Pat Langley, An Adaptive Interactive Agent for Route Advice, In the proceedings of the Third International Conference on Autonomous Agents, Seattle, 1999,5. p 198-205.
[60] Kai Nagel: Multi-Agent Transportation Simulation, 2003.6, http://www, sim. inf. ethz. ch/papers/book/html/
[61] J. Wahle, O. Annen, Ch. Schuster, L. Neubert, M. Schreckenberg: A Dynamic Route Guidance System Based on Real Traffic Data. European Journal Operational Research 131 (2001), 302-308
[62] J. Wahle,L. Neubert, J. Esser, M. Schreckenberg: A Cellular Automaton Traffic Flow Model for Online Simulation of Traffic. Parallel Computing 27 (2001), 719-735
[63] Qi Yang, Haris N. Koutsopoulos: A Microscopic Traffic Simulator For Evaluation of Dynamic Traffic Management Systems. Transportation Research. Vol 4, No. 3, pp113-129, 1996
[64] Qi Yang, A Simulation Laboratory for Evaluation of Dynamic Traffic Management Systems. Ph.D. thesis report, Massachusetts Institute of Technology, June 1997.
[65] Serge P. Hoogendoorn, State-of-the-art of Vehicular Traffic Flow Modelling, Journal of Systems and Control Engineering, Special Issue on Road Traffic Modelling and Control, vol. 215, 2001, pp283-304.