城市区域交通控制技术研究
|
摘要
近年来城市道路交通拥挤和交通阻塞已经成为世界大中城市普遍存在的问题,并且由此带来了一系列的社会问题,比如交通事故剧增、环境污染等。大力发展城市交通智能控制系统是解决现代社会交通需求与供给矛盾的重要途径之一。实现城市交通系统的智能控制不仅有利于提高交通运输效率,增加道路交通运营安全,而且还关系到土地资源与能源的合理利用、城市环境的改善,乃至国民经济的持续发展和社会效益的提高。
城市交通控制系统中,一般包括单点控制系统、干线控制系统、区域控制系统等几种划分和研究方式,尽管各种控制方式均具有不同的适用范围,但显然,城市交通拥堵在整个城市范围内普遍存在,交叉口之间的相关性非常明显,在一个区域中,单个交叉口信号的调整往往会影响到相邻若干节点和路段交通流的运行状况,单个交叉口的拥堵可能会逐步影响到周边数个交叉口。单点控制系统无论多么优化,也无法缓解某个区域或整个城市交通拥堵。因此,以某个区域甚至整个城市作为研究对象的区域信号控制理论方法研究也越来越受到重视。如何从整个系统的战略角度出发,将区域内的所有交叉口作为研究对象,同时对所有交叉口进行有效交通信号控制设计,以提高整个控制区域内的交通运输效率,已成为城市交通控制发展的新课题。本文研究重点也在于此。
论文针对区域交通控制的关键技术展开研究,主要包括了以下几个方面：
(1)本文将交通规划理念作为宏观控制的一个方面,从宏观层面考虑交通网络优化问题。基于均衡配流的思想,探讨了利用双层规划方法建立城市区域网络设计问题。在分析一般行程时间可靠度基础上,提出了绝对可靠度和相对可靠度的概念,从而更精细化描述路网在一天内的稳定性变化。并将行程时间可靠度与常规的交通阻抗相结合,作为广义的交通阻抗引入到路网设计的上层规划目标函数中,为路网设计开拓了新的优化思路。
(2)论文研究了交通状态辨识问题。本文在总结归纳状态分析方法的基础上,从量化角度提出了控制小区划分思想。论文设计了小区划分的原则,并提出了具体算法,可作为系统的交通状态辨识的基础工作,并通过以较大的路网实例验证了该算法的可行性。
(3)本文重点对区域交通信号控制问题做了研究,总结了区域交通信号控制系统常见的结构类型、控制策略,针对现有模型多数没有考虑各不同路口路段交通状态差异的特点,本文建立了基于均衡配流的双层规划模型,上层模型优化停车延误,下层模型解决均衡配流,并将状态划分的结果作为重要的因子引入到上层规划模型中。论文还探讨了双层规模模型的求解算法,提出了遗传算法和模拟退火结合的智能方法,通过一个标准测试网络验证了算法的有效性和局限性。
(4)论文将交通管理也作为宏观控制的一种手段,对大型活动区域的交通问题用管控一体化的思路做研究。首先对大型活动从交通需求特性、交通流特性和交通管控方面做了分析,重点从技术层面对管控措施做了研究。提出了活动区域交通控制的双层规划模型,统筹优化三个方面：大众离场的疏散效率、活动对周边交通影响程度、交通管控措施投入成本,利用遗传算法求解该问题,并通过济南市全运会的交通管控实例对模型做了验证。
在对上述问题进行探讨后,论文总结分析了创新点以及存在的不足,提出了未来的研究重点和方向。
In recent years, traffic congestion and jam has become a common problem to be faced by large and medium-sized cities in the world. And a series of social problems brought by traffic congestion also trouble them, such as traffic accidents, environment pollution, energy crisis and so on. Developing urban intelligent traffic control system is one of the important ways to solve contradictions between traffic demand and supply. Implementing intelligent control of urban traffic system is not only beneficial to improve transportation efficiency and enhance road traffic safety, but also relates to making full use of land source and energy, improving urban environment, developing national economy and social benefit.
Urban traffic control systems, generally includes single point control system, trunk control system and regional control system, from either classification or research. Various control system has a different scope of application, but it is clear that the urban traffic congestion is widespread throughout the city. The correlation between the intersections is very obvious in an area. The adjustment of a single intersection signal often affect traffic flow status of a number of adjacent nodes and links. Single intersection in congestion may gradually affect the surrounding intersection.
Single point control systems, no matter how optimization cannot be mitigated to traffic congestion of a certain area or the entire urban. Therefore, research on signal control theory of a region or even the entire city more and more attention. Departure from the strategic point of view of the entire system, all intersections in the area as the object of study, all intersection traffic signal control is designed to improve transport efficiency within the entire control area, has become the development of urban traffic control new topics. The focus of this thesis is also here.
This thesis aims key technologies research on area traffic control, including the following aspects:
(1) In this thesis, the transportation planning concept as one aspect of a macro-control, transport network problems are optimized from the macro level. Based on the balanced flow of ideas, the design of metropolitan area network is set up by the bi-level programming method. Based on the analysis of the general travel time reliability, absolute reliability and relative reliability are posed, which will more refined description of the stability of the road network in the day change. Travel time reliability combined with conventional traffic impedance, as generalized traffic impedance, is introduced to objective function of the upper level of network design. And then a new road is constructed to optimize network design.
(2) The traffic state identification problem is studied in this thesis. After summarizes the status of analytical methods, we build the ideas of the control cell division from a quantitative point of view. We designed the principle of division of the cell, and pose a detailed algorithm, which can be used as basic work of traffic system state identification. And examples of large road network demonstrate the feasibility of the algorithm.
(3) We focus on the regional traffic signal control problem, and summed up the all type of common structure and control strategy for regional traffic signal control system. Taking into account the differences of traffic state between the various junctions and links are ignored in the majority of the existing model, establishes a bi-level programming model is built based on the equilibrium assignment traffic flow in the thesis. Optimization vehicle delay is worked in upper model, while a balanced flow is solved in the lower model. And the results of state partition, which as an important factor, are introduced to the upper programming model. We also explore the solving algorithm to the bi-level model in the thesis, and intelligent method combining genetic algorithm with simulated annealing and solving ideas based on the gradient projection are put forward. The validity and limitations of the algorithms are verified by a network of standard.
(4) Traffic management is treated as a means of macro-control in the thesis, and ideas of integration traffic management and control are introduced into research on traffic problems of the massive activities area. First we analysis the characteristics of traffic demand, traffic flow and traffic control of massive activities. Second, research is focused on control measures from the technical aspects. The bi-level programming model of the active area traffic control is posed to optimize simultaneously three problems:impact on the surrounding traffic of activities, input costs of control measures, evacuation efficiency of the mass departures. The solving idea of combination of rough set and genetic algorithm is set up in the thesis, and the instance of Jinan National Games verifies the traffic control algorithm.
Finally, we summarize innovations and shortcomings after explore the issues above in the thesis, and proposes future research priorities and orientations.
城市交通控制系统中,一般包括单点控制系统、干线控制系统、区域控制系统等几种划分和研究方式,尽管各种控制方式均具有不同的适用范围,但显然,城市交通拥堵在整个城市范围内普遍存在,交叉口之间的相关性非常明显,在一个区域中,单个交叉口信号的调整往往会影响到相邻若干节点和路段交通流的运行状况,单个交叉口的拥堵可能会逐步影响到周边数个交叉口。单点控制系统无论多么优化,也无法缓解某个区域或整个城市交通拥堵。因此,以某个区域甚至整个城市作为研究对象的区域信号控制理论方法研究也越来越受到重视。如何从整个系统的战略角度出发,将区域内的所有交叉口作为研究对象,同时对所有交叉口进行有效交通信号控制设计,以提高整个控制区域内的交通运输效率,已成为城市交通控制发展的新课题。本文研究重点也在于此。
论文针对区域交通控制的关键技术展开研究,主要包括了以下几个方面：
(1)本文将交通规划理念作为宏观控制的一个方面,从宏观层面考虑交通网络优化问题。基于均衡配流的思想,探讨了利用双层规划方法建立城市区域网络设计问题。在分析一般行程时间可靠度基础上,提出了绝对可靠度和相对可靠度的概念,从而更精细化描述路网在一天内的稳定性变化。并将行程时间可靠度与常规的交通阻抗相结合,作为广义的交通阻抗引入到路网设计的上层规划目标函数中,为路网设计开拓了新的优化思路。
(2)论文研究了交通状态辨识问题。本文在总结归纳状态分析方法的基础上,从量化角度提出了控制小区划分思想。论文设计了小区划分的原则,并提出了具体算法,可作为系统的交通状态辨识的基础工作,并通过以较大的路网实例验证了该算法的可行性。
(3)本文重点对区域交通信号控制问题做了研究,总结了区域交通信号控制系统常见的结构类型、控制策略,针对现有模型多数没有考虑各不同路口路段交通状态差异的特点,本文建立了基于均衡配流的双层规划模型,上层模型优化停车延误,下层模型解决均衡配流,并将状态划分的结果作为重要的因子引入到上层规划模型中。论文还探讨了双层规模模型的求解算法,提出了遗传算法和模拟退火结合的智能方法,通过一个标准测试网络验证了算法的有效性和局限性。
(4)论文将交通管理也作为宏观控制的一种手段,对大型活动区域的交通问题用管控一体化的思路做研究。首先对大型活动从交通需求特性、交通流特性和交通管控方面做了分析,重点从技术层面对管控措施做了研究。提出了活动区域交通控制的双层规划模型,统筹优化三个方面：大众离场的疏散效率、活动对周边交通影响程度、交通管控措施投入成本,利用遗传算法求解该问题,并通过济南市全运会的交通管控实例对模型做了验证。
在对上述问题进行探讨后,论文总结分析了创新点以及存在的不足,提出了未来的研究重点和方向。
In recent years, traffic congestion and jam has become a common problem to be faced by large and medium-sized cities in the world. And a series of social problems brought by traffic congestion also trouble them, such as traffic accidents, environment pollution, energy crisis and so on. Developing urban intelligent traffic control system is one of the important ways to solve contradictions between traffic demand and supply. Implementing intelligent control of urban traffic system is not only beneficial to improve transportation efficiency and enhance road traffic safety, but also relates to making full use of land source and energy, improving urban environment, developing national economy and social benefit.
Urban traffic control systems, generally includes single point control system, trunk control system and regional control system, from either classification or research. Various control system has a different scope of application, but it is clear that the urban traffic congestion is widespread throughout the city. The correlation between the intersections is very obvious in an area. The adjustment of a single intersection signal often affect traffic flow status of a number of adjacent nodes and links. Single intersection in congestion may gradually affect the surrounding intersection.
Single point control systems, no matter how optimization cannot be mitigated to traffic congestion of a certain area or the entire urban. Therefore, research on signal control theory of a region or even the entire city more and more attention. Departure from the strategic point of view of the entire system, all intersections in the area as the object of study, all intersection traffic signal control is designed to improve transport efficiency within the entire control area, has become the development of urban traffic control new topics. The focus of this thesis is also here.
This thesis aims key technologies research on area traffic control, including the following aspects:
(1) In this thesis, the transportation planning concept as one aspect of a macro-control, transport network problems are optimized from the macro level. Based on the balanced flow of ideas, the design of metropolitan area network is set up by the bi-level programming method. Based on the analysis of the general travel time reliability, absolute reliability and relative reliability are posed, which will more refined description of the stability of the road network in the day change. Travel time reliability combined with conventional traffic impedance, as generalized traffic impedance, is introduced to objective function of the upper level of network design. And then a new road is constructed to optimize network design.
(2) The traffic state identification problem is studied in this thesis. After summarizes the status of analytical methods, we build the ideas of the control cell division from a quantitative point of view. We designed the principle of division of the cell, and pose a detailed algorithm, which can be used as basic work of traffic system state identification. And examples of large road network demonstrate the feasibility of the algorithm.
(3) We focus on the regional traffic signal control problem, and summed up the all type of common structure and control strategy for regional traffic signal control system. Taking into account the differences of traffic state between the various junctions and links are ignored in the majority of the existing model, establishes a bi-level programming model is built based on the equilibrium assignment traffic flow in the thesis. Optimization vehicle delay is worked in upper model, while a balanced flow is solved in the lower model. And the results of state partition, which as an important factor, are introduced to the upper programming model. We also explore the solving algorithm to the bi-level model in the thesis, and intelligent method combining genetic algorithm with simulated annealing and solving ideas based on the gradient projection are put forward. The validity and limitations of the algorithms are verified by a network of standard.
(4) Traffic management is treated as a means of macro-control in the thesis, and ideas of integration traffic management and control are introduced into research on traffic problems of the massive activities area. First we analysis the characteristics of traffic demand, traffic flow and traffic control of massive activities. Second, research is focused on control measures from the technical aspects. The bi-level programming model of the active area traffic control is posed to optimize simultaneously three problems:impact on the surrounding traffic of activities, input costs of control measures, evacuation efficiency of the mass departures. The solving idea of combination of rough set and genetic algorithm is set up in the thesis, and the instance of Jinan National Games verifies the traffic control algorithm.
Finally, we summarize innovations and shortcomings after explore the issues above in the thesis, and proposes future research priorities and orientations.
引文
[1]杨佩昆,吴兵.交通管理与控制[M].人民交通出版社,2005：89-152.
[2]全永燊.城市交通控制[M].人民交通出版社,1989：3-4.
[3]彭维.城市交通信号智能控制方法研究[D].长春：吉林大学,2007：27-45.
[4]蔡蕾.城市平面交叉路口交通信号优化控制[D].长春：吉林大学,2007：18-40.
[5]Burmeister B., Haddadi A., Matylis G.. Application of multi-agent system in traffic and transportation [J]. IEEE Proceeding Software Engineering, 1997, 144 (1):51-60.
[6]Laichour H., Maouche S., Mandiau R.. Traffic control assistance in connection nodes:Multi-agent application in urban transport systems [C]. Proceedings of International Workshop on Intelligent Data Application and Advanced Computing System:Technology and Application, 2001:133-137.
[7]Bingham E.. Reinforcement learning in neuro-fuzzy traffic signal control [J]. European Journal of Operational Research, 2001,131(2):232-241.
[8]魏武,张起森,王明俊,黄中祥.一种基于模糊逻辑的城市交叉口交通信号控制方法[J].交通运输工程学报,2001(2)：99-102.
[9]陈阳舟,张辉,杨玉珍,胡全连.基于Q学习的Agent在单路口交通控制中的应用[J].公路交通科技,2007(5)：117-120.
[10]万伟,陈峰.基于遗传算法的单交叉口信号优化控制[J].计算机工程,2007,33(16)：217-219.
[11]王秋平,谭学龙,张生瑞.城市单点交叉口信号配时优化[J].交通运输工程学报,2006,(2)：60-64.
[12]赵伟,高凤玲,张毅.道路交叉口交通控制模拟系统[J].交通科技,2004(3)：98-100.
[13]吴义虎,喻丹,何霞,郭文莲.单路口低饱和交通流的多相位混沌控制仿真研究[J].系统仿真技术,2007,3(2)：63-67.
[14]贺国光,崔岩,王桂珠.单路口交通流控制动态响应的仿真研究[J].系统工程学报,2005,20(3)：323-329.
[15]Halim C., Michael G.H.. Traffic signal timing optimization based on genetic algorithm approach including drivers'routing [J]. Transportation Research Part B,2004,38 (2):329-342.
[16]靳文舟,黄一峰,荣利利,李俊辉,刘颖杰.基于粒子群理论的干道协调控制优化研究[J].交通与计算机,2008,26(1)：31-35.
[17]吴恩,杨晓光,吴震,常云涛.基于遗传算法的干线协调控制参数共同优化[J].同济大学学报(自然科学版),2008,36(7)：921-926.
[18]陈娟，徐立鸿,袁长亮.分层控制算法在过饱和交通于线控制中的应用[J].系统仿真学报,2008,20(15)：4122-4137.
[19]赵晓华,李振龙,于泉,荣建.基于Q学习算法的两交叉信号灯博弈协调控制[J].系统仿真学报,2007,19(18)：4253-4256.
[20]朱文兴,贾磊.城市主干路交通流多目标优化控制[J].山东大学学报(工学版),2004,34(4)：72-78.
[21]Gartner N.H., Stamatiadis C.. Arterial-based control of traffic flow in urban grid networks [J]. Mathematics and Computer Modelling, 2002,35(5):657-671.
[22]杨晓芳.基于模糊控制的城市交通信号控制系统的研究[D].西安：长安大学,2003：18-40.
[23]Nathan H.G., John D.C.. Little H.G.. Optimization of traffic signal settings by mixed integer linear programming Part I:the network coordination problem [J]. Transportation Science,1975,9(4):321-343.
[24]Gartner N.H., Little J.D.C., Gabbay H.. Optimization of traffic signal settings by mixed integer linear programming. Part II:the network synchronization problem [J]. Transportation Science, 1975,9(4):344-363.
[25]Little J.D.C., Kelson M.D., Gartner N.H.. A program for setting signals on arterials and triangular networks [J]. Transportation Research Record,1981, 795:40-46.
[26]Cohen S.L., Liu C.C.. The band width-constrained TRANSYT signal optima-zation program [J]. Transportation Research Record,1986,1057:1-7.
[27]Gartner N.H., Assmann S.F., Lasaga F.L., Hou D.L.. A multi-band approach to arterial traffic signal optimization [J]. Transportation Research Part B,1991,25 (1):55-74.
[28]Chaudhary N.A., Messer C.J.. A program for optimizing signal timing in grid networks [C]. Proceedings of 72nd Annual Meeting of the Transportation Research Board,1993:82-93.
[29]Allsop R.E.. Some possibilities for using traffic control to influence trip destinations and route choice [C]. Proceedings of the Sixth International Symposium on Transportation and Traffic Theory,1974:345-374.
[30]Nathan H.G.. Area traffic control and network equilibrium [R]. Boston: Massachusetts Institute of Technology,1975:1-26.
[31]Hai Y. Traffic assignment and signal control in saturated road networks [J]. Transportion Research A, 1995,29(2):125-139.
[32]Wann M.W.. Model formulation and solution algorithm of traffic signal control in an urban network [J]. Computers, Environment and Urban Systems,2000, 24(4):355-378.
[33]Hong K.L., Elbert C, Yiu C.C.. Dynamic network traffic control [J]. Transportation Research Part A:Policy and Practice, 2001,35(8):721-744.
[34]Ernesto C., Gaetano F.. Combined signal setting design and traffic assignment problem [J]. European Journal of operation research, 2004, 155(3):569-583.
[35]Mariagrazia D., Maria P.F., Carlo M.. A signal timing plan formulation for urban traffic control [J]. Control Engineering Practice, 2006, 14(11):1297-1311.
[36]宋现敏.城市交叉口信号协调控制方法研究[D].长春：吉林大学,2008：15-16.
[37]石建军,于泉,任福田.大城市交通信号控制系统层次与区域动态划分的研究[J].道路交通与安全,2004(4)：7-9.
[38]卢凯,徐建闽,李轶舜.基于关联度分析的协调控制子区划分方法[J].华南理工大学学报,2009,37(7)：6-9.
[39]高海军,俞国军,李振龙.基于agent的城市交通信号控制[J].控制与决策,2004,19(7)：737-740.
[40]傅惠,徐建闽,卢凯.基于粒子群优化的关联交叉口群信号控制策略研究[J].交通与计算机,2007,25(3)：23-26.
[41]高云峰,胡华,陈红洁,杨晓光.交叉口群交通控制实时评价模型仿真研究[J].系统仿真学报,2007,19(24)：5607-5612.
[42]连爱萍.城市动态网络交通流分配及相关问题的研究[D].北京：北京交通大学,2007：91-109.
[43]王浩.城市交通动态协调控制优化方法及实用技术研究[D].上海：同济大学,2008：37-65.
[44]卢守峰.基于元胞自动机的交通信号控制与路径诱导的协同系统[D].长春：吉林大学,2006：45-67.
[45]郭金,黄崇超.交通信号控制的二层规矩模与算法研究[J].数学杂志2008,28(5)：559-564.
[46]龙建成,高自友,任华玲.城市网络交通动态信号控制方法[J].中国公路学报,2009,22(4)：108-114.
[47]徐建闽,许伦辉,撒元功.交叉口有交通信号控制时用户最优动态配流模型[J].控制理论与应用,2000,17(1)：117-120.
[48]徐丽群,杨兆升,贾正锐.信号控制对动态路线选择的影响研究[J].中国公路学报,2000,13(2)：99-101.
[49]李润梅,汤淑明.饱和路网中动态交通分配与路口控制一体化建模研究[J].系统仿真学报,2007,19(8)：1811-1815.
[50]Chard B.M., Line X.C.. TRANSYT: The latest development [J]. Traffic Engineering and control,1987,28:32-35.
[51]刘智勇.智能交通控制理论及其应用[M].科学出版社,2003：2-20.
[52]Shah A.A., Lee J.. Intelligent transportation systems in transitional and developing countries[J]. Aerospace and Electronic Systems Magazine, 2007, 22(8):27-33.
[53]Hunt P.B.. The SCOOT online traffic signal optimization technique [J]. Traffic Engineering and Control,1982,23:190-192.
[54]Martin P.T., Hockaday Stephen L.M.. SCOOT-An update [J]. Institute of Transportation Engineers, 1995,65(1):44-48.
[55]Wong Y.K., Woon W.L.. An iterative approach to enhanced traffic signal optimization [J]. Expert Systems with Applications,2008,34(4):2885-2890.
[56]Lowrie P.R.. SCATS principles, methodologies, algorithm [C]. IEEE Conference on Road Traffic Signal,1982:67-70.
[57]黄德双.神经网络模式识别系统理论[M].北京：电子工业出版社,1996：254-276.
[58]杨立才.道路交通智能控制策略的研究[D].济南：山东大学,2005：31-34.
[59]Amit K., Uday K., Chakraborty P.P.. Supervised learning on a fuzzy Petri net [J]. Information Sciences,2005,172:397-416.
[60]Pads A., Mastorocostas John B.T.. An orthogonal least-squares method for recurrent fuzzy-neural modeling [J]. Fuzzy Sets and Systems,2003, 140(2):285-300.
[61]孙海蓉.模糊神经网络的研究及其应用[D].北京：华北电力大学,2006：17-30.
[62]张文修,梁怡.遗传算法的数学基础[M].西安交通大学出版社.2000：23-36.
[63]李敏强,寇纪淞,林丹等.遗传算法的基本理论与应用[M].科学出版社.2002：12-34.
[64]周明,孙树栋.遗传算法原理及应用[M].国防工业出版社,1999：15-30.
[65]吴志远,邵惠鹤,吴新余.遗传退火进化算法[J].上海交通大学学报,1997,31(12)：69-72.
[66]王殿海.交通流理论[M].人民交通出版社,2002：7-28,60-77.
[67]丹尼尔L.鸠洛夫,马休J.休伯,蒋璜等.交通流理论[M].人民交通出版社,1983：86-115,184-224.
[68]王炜.交通规划[M].人民交通出版社,2007：56-75.
[69]Chen A., Subprasom K., JI Z.W.. Mean variance model for the build operate transfer scheme under demand uncertainty [J]. Transportation Research Record, 2003,1857:93-101.
[70]Chen A., Subprasom K.. Analysis of regulation and policy of private toll roads in a build operate transfer scheme under demand uncertainty [J]. Transportation Research A,2007,41(6):537-558.
[71]陆化普,蔚欣欣,卞长志.OD需求不确定的离散交通网络设计模型研究[J].公路交通科技,2011,28(5)：128-132.
[72]四兵锋,赵小梅,孙壮志.城市混合交通网络系统优化模型及其算法[J].中国公路学报,2008,21(1)：77-82.
[73]Chootinan P., Wong S.C., Chen A.. A reliability based network design problem [J]. Journal of Advanced Transportation, 2005,39(3):247-270.
[74]Sumalee A.,Watling D.P., Nakayama S.. Reliable network design problem:the case with uncertain demand and total travel time reliability [J]. Transportation Research Record,2006(1964):81-90.
[75]许良,高自友.基于路段能力可靠性的城市交通网络设计问题[J].中国公路学报,2006,19(2)：86-90.
[76]曾明华,李复苗.多层次多模式综合交通网络设计研究[J].交通运输系统工程与信息,2010,10(2)：23-29.
[77]张江华,陈克东,韩强.一种新的交通网络设计优化算法[J].运筹与管理,2007,16(3)：41-46.
[78]Chen M.Y., Alfa A.S.. A network design algorithm using a stochastic incremental traffic assignment approach [J]. Transportation Science,1991, 25(3):215-224.
[79]David G.A.. Exact local solution of the continuous network design problem via stochastic user equilibrium assignment [J]. Transportation Research B,1994, 28:61-75.
[80]Yang H., Bell M.G.. Transport bi-level programming problems:recent method logical advances [J]. Transportation Research B, 2001,35:1-4.
[81]Yang H., Bell M.G.. Traffic restraint, road pricing and network equilibrium [J]. Transportation Research B,1997,31:303-314.
[82]赵彤,高自友.交通离散网络设计与土地使用问题的组合模型及求解算法[J].土木工程学报,2003,36(1)：6-10.
[83]Gao Z.Y., Song Y.F.. A reserve capacity model of optimal signal control with user equilibrium route choice [J]. Transportation Research B, 2002, 36:313-323.
[84]Aldeek H.M., Emam E.B.. Computing travel time reliability in transportation networks with multi-states and dependent link failures [J]. Journal of Computing in Civil Engineering, 2006,20(5):317-327.
[85]李先,温慧敏,高永等.北京市路网单位距离行程时间可靠性评价[J].交通运输系统工程与信息,2007,7(2)：73-77.
[86]郭继孚,高永,温慧敏.基于替代路径的路网连通可靠性评价方法研究[J].公路交通科技,2007,24(7)：91-96.
[87]Chen A., Yang H., Hong K.L.. Capacity reliability of a road network:an assessment methodology and numerical results [J]. Transportation Research B, 2002,36:1-28.
[88]Uno N., Kurauchi F., Tamura H.. Using bus probe data for analysis of travel time variability [J]. Journal of Intelligent Transportation Systems,2009, 13(1):2-15.
[89]张勇,白玉,杨晓光.城市道路网络的行程时间可靠性[J].系统工程理论与实践,2009,29(8)：171-176.
[90]邓键.双层规划若干问题的解法[D].长春：吉林大学,2009：19-33.
[91]李和成.非线性双层规划问题的遗传算法研究[D].西安：西安电子科技大学,2009：20-35.
[92]Bard J., Moore J. A branch and bound algorithm for the bi-level programming problem [J]. Journal on Scientific and Statistical Computing,1990,11:281-292.
[93]Al Khayyal F.A., Horst R., Pardalos P.M.. Global optimization of concave functions subject to quadratic constraints:An application in nonlinear bi-level programming [J]. Annals of Operations Researeh,1992,34:125-147.
[94]Abdulaal M., Leblanc L.J.. Continuous equilibrium network design models [J]. Transportation Research B,1979,13:19-32.
[95]Bialas W., Karwan M.. Two level linear programming [J]. Management Seience, 1954,30:1004-1020.
[96]姜桂艳.道路交通状态判别技术与应用[M].人民交通出版社,2004：23-45.
[97]于春全,郭敏,梁玉庆.关于建立城市道路交通运行状况宏观评价系统的研究[J].道路交通与安全,2007,7(1)：1-6.
[98]皮晓亮,王正,韩皓等.基于环形线圈检测器采集信息的交通状态分类方法应用研究[J].公路交通科技,2006,23(4)：115-119.
[99]任江涛,欧晓凌,张毅等.交通状态模式识别研究[J].公路交通科技,2003,20(2)：63-67.
[100]张和生,张毅,胡东成等.区域交通状态分析的时空分层模型[J].清华大学学报(自然科学版),2007,47(1)：157-160.
[101]王伟,杨兆升,李贻武等.基于信息协同的子区交通状态加权计算与判别方法[J].吉林大学学报(工学版),2007,37(3)：524-527.
[102]Walinchus R.J.. Real time network decomposition and sub-network interfacing [R/CD]. Washington DC: Transportation Research Board, 1971:46-52.
[103]Yagoda N.H.. Subdivision of signal systems into control areas [J]. Traffic Engineering,1973,43(12):42-48.
[104]王学堂.城市交通信号整体优化理论的概念与方法[J].长安大学学报(自然科学版),2002,22(5)：90-92.
[105]高云峰.动态交叉口群协调控制基础问题研究[D].上海：同济大学2007：25-36.
[106]杨庆芳,陈林.交通控制子区动态划分方法[J].吉林大学学报(工学版),2009,36(增)：139-142.
[107]杨祖元.城市交通信号系统智能控制策略研究[D].重庆：重庆大学,2008：90-100.
[108]孔祥杰,沈国江,梁同海.具有公交优先的路网交通流智能协调控制研究[J].浙江大学学报(工学版),2009,43(6)：1026-1031.
[109]Wang D.H., Song X.M., Li F.. Research on offset optimization of signalized arterials [C]. Proceedings of the Fifth International Conference on Traffic and Transportation Studies,2006:584-594.
[110]李威武.城域智能交通系统中的控制与优化的问题研究[D].杭州：浙江大学2003：87-98.
[111]沈国江.城市区域交通智能分散控制研究[J].浙江大学学报(工学版),2006,40(4)：585-589.
[112]姜桂艳,李继伟,张春勤.城市主干路段行程时间估计的BPR修正模型[J].西南交通大学学报,2010,45(1)：124-130.
[113]Laudy M., Mees A.. Convergence of an annealing algorithm [J]. Mathematical Programming, 1986,34(1):111-124.
[114]刘伟铭,姜山.基于GASA混合优化策略的双层规划模型求解算法研究[J].土小工程学报,2003,36(7)：27-32.
[115]葛洪伟,王银年.求解VRPSDP问题的改进模拟退火遗传算法[J].计算机工程与应用,2010,46(30)：36-40.
[116]崔洪军.大型活动交通组织管理关键技术研究[D].南京：东南大学2006：1-9.
[117]赵佳琪,姜桂艳.大型活动的交通组织与管理研究[J].交通标准化,2009,6：60-63.
[118]赵晓辉,吴兵,董治,李林波.大型活动吣交通需求管理策略研究[J]. 现代交通技术,2009,6(1)：80-83.
[119]严新平,吕能超,刘正林.大型活动后车道单行优化的双层规划[J].西南交通大学学报,2009,44(1)：112-117.
[120]王素欣,王雷震,高利.BPR路阻函数的改进研究[J].武汉理工大学学报,2009,33(3)：446-449.
[2]全永燊.城市交通控制[M].人民交通出版社,1989：3-4.
[3]彭维.城市交通信号智能控制方法研究[D].长春：吉林大学,2007：27-45.
[4]蔡蕾.城市平面交叉路口交通信号优化控制[D].长春：吉林大学,2007：18-40.
[5]Burmeister B., Haddadi A., Matylis G.. Application of multi-agent system in traffic and transportation [J]. IEEE Proceeding Software Engineering, 1997, 144 (1):51-60.
[6]Laichour H., Maouche S., Mandiau R.. Traffic control assistance in connection nodes:Multi-agent application in urban transport systems [C]. Proceedings of International Workshop on Intelligent Data Application and Advanced Computing System:Technology and Application, 2001:133-137.
[7]Bingham E.. Reinforcement learning in neuro-fuzzy traffic signal control [J]. European Journal of Operational Research, 2001,131(2):232-241.
[8]魏武,张起森,王明俊,黄中祥.一种基于模糊逻辑的城市交叉口交通信号控制方法[J].交通运输工程学报,2001(2)：99-102.
[9]陈阳舟,张辉,杨玉珍,胡全连.基于Q学习的Agent在单路口交通控制中的应用[J].公路交通科技,2007(5)：117-120.
[10]万伟,陈峰.基于遗传算法的单交叉口信号优化控制[J].计算机工程,2007,33(16)：217-219.
[11]王秋平,谭学龙,张生瑞.城市单点交叉口信号配时优化[J].交通运输工程学报,2006,(2)：60-64.
[12]赵伟,高凤玲,张毅.道路交叉口交通控制模拟系统[J].交通科技,2004(3)：98-100.
[13]吴义虎,喻丹,何霞,郭文莲.单路口低饱和交通流的多相位混沌控制仿真研究[J].系统仿真技术,2007,3(2)：63-67.
[14]贺国光,崔岩,王桂珠.单路口交通流控制动态响应的仿真研究[J].系统工程学报,2005,20(3)：323-329.
[15]Halim C., Michael G.H.. Traffic signal timing optimization based on genetic algorithm approach including drivers'routing [J]. Transportation Research Part B,2004,38 (2):329-342.
[16]靳文舟,黄一峰,荣利利,李俊辉,刘颖杰.基于粒子群理论的干道协调控制优化研究[J].交通与计算机,2008,26(1)：31-35.
[17]吴恩,杨晓光,吴震,常云涛.基于遗传算法的干线协调控制参数共同优化[J].同济大学学报(自然科学版),2008,36(7)：921-926.
[18]陈娟，徐立鸿,袁长亮.分层控制算法在过饱和交通于线控制中的应用[J].系统仿真学报,2008,20(15)：4122-4137.
[19]赵晓华,李振龙,于泉,荣建.基于Q学习算法的两交叉信号灯博弈协调控制[J].系统仿真学报,2007,19(18)：4253-4256.
[20]朱文兴,贾磊.城市主干路交通流多目标优化控制[J].山东大学学报(工学版),2004,34(4)：72-78.
[21]Gartner N.H., Stamatiadis C.. Arterial-based control of traffic flow in urban grid networks [J]. Mathematics and Computer Modelling, 2002,35(5):657-671.
[22]杨晓芳.基于模糊控制的城市交通信号控制系统的研究[D].西安：长安大学,2003：18-40.
[23]Nathan H.G., John D.C.. Little H.G.. Optimization of traffic signal settings by mixed integer linear programming Part I:the network coordination problem [J]. Transportation Science,1975,9(4):321-343.
[24]Gartner N.H., Little J.D.C., Gabbay H.. Optimization of traffic signal settings by mixed integer linear programming. Part II:the network synchronization problem [J]. Transportation Science, 1975,9(4):344-363.
[25]Little J.D.C., Kelson M.D., Gartner N.H.. A program for setting signals on arterials and triangular networks [J]. Transportation Research Record,1981, 795:40-46.
[26]Cohen S.L., Liu C.C.. The band width-constrained TRANSYT signal optima-zation program [J]. Transportation Research Record,1986,1057:1-7.
[27]Gartner N.H., Assmann S.F., Lasaga F.L., Hou D.L.. A multi-band approach to arterial traffic signal optimization [J]. Transportation Research Part B,1991,25 (1):55-74.
[28]Chaudhary N.A., Messer C.J.. A program for optimizing signal timing in grid networks [C]. Proceedings of 72nd Annual Meeting of the Transportation Research Board,1993:82-93.
[29]Allsop R.E.. Some possibilities for using traffic control to influence trip destinations and route choice [C]. Proceedings of the Sixth International Symposium on Transportation and Traffic Theory,1974:345-374.
[30]Nathan H.G.. Area traffic control and network equilibrium [R]. Boston: Massachusetts Institute of Technology,1975:1-26.
[31]Hai Y. Traffic assignment and signal control in saturated road networks [J]. Transportion Research A, 1995,29(2):125-139.
[32]Wann M.W.. Model formulation and solution algorithm of traffic signal control in an urban network [J]. Computers, Environment and Urban Systems,2000, 24(4):355-378.
[33]Hong K.L., Elbert C, Yiu C.C.. Dynamic network traffic control [J]. Transportation Research Part A:Policy and Practice, 2001,35(8):721-744.
[34]Ernesto C., Gaetano F.. Combined signal setting design and traffic assignment problem [J]. European Journal of operation research, 2004, 155(3):569-583.
[35]Mariagrazia D., Maria P.F., Carlo M.. A signal timing plan formulation for urban traffic control [J]. Control Engineering Practice, 2006, 14(11):1297-1311.
[36]宋现敏.城市交叉口信号协调控制方法研究[D].长春：吉林大学,2008：15-16.
[37]石建军,于泉,任福田.大城市交通信号控制系统层次与区域动态划分的研究[J].道路交通与安全,2004(4)：7-9.
[38]卢凯,徐建闽,李轶舜.基于关联度分析的协调控制子区划分方法[J].华南理工大学学报,2009,37(7)：6-9.
[39]高海军,俞国军,李振龙.基于agent的城市交通信号控制[J].控制与决策,2004,19(7)：737-740.
[40]傅惠,徐建闽,卢凯.基于粒子群优化的关联交叉口群信号控制策略研究[J].交通与计算机,2007,25(3)：23-26.
[41]高云峰,胡华,陈红洁,杨晓光.交叉口群交通控制实时评价模型仿真研究[J].系统仿真学报,2007,19(24)：5607-5612.
[42]连爱萍.城市动态网络交通流分配及相关问题的研究[D].北京：北京交通大学,2007：91-109.
[43]王浩.城市交通动态协调控制优化方法及实用技术研究[D].上海：同济大学,2008：37-65.
[44]卢守峰.基于元胞自动机的交通信号控制与路径诱导的协同系统[D].长春：吉林大学,2006：45-67.
[45]郭金,黄崇超.交通信号控制的二层规矩模与算法研究[J].数学杂志2008,28(5)：559-564.
[46]龙建成,高自友,任华玲.城市网络交通动态信号控制方法[J].中国公路学报,2009,22(4)：108-114.
[47]徐建闽,许伦辉,撒元功.交叉口有交通信号控制时用户最优动态配流模型[J].控制理论与应用,2000,17(1)：117-120.
[48]徐丽群,杨兆升,贾正锐.信号控制对动态路线选择的影响研究[J].中国公路学报,2000,13(2)：99-101.
[49]李润梅,汤淑明.饱和路网中动态交通分配与路口控制一体化建模研究[J].系统仿真学报,2007,19(8)：1811-1815.
[50]Chard B.M., Line X.C.. TRANSYT: The latest development [J]. Traffic Engineering and control,1987,28:32-35.
[51]刘智勇.智能交通控制理论及其应用[M].科学出版社,2003：2-20.
[52]Shah A.A., Lee J.. Intelligent transportation systems in transitional and developing countries[J]. Aerospace and Electronic Systems Magazine, 2007, 22(8):27-33.
[53]Hunt P.B.. The SCOOT online traffic signal optimization technique [J]. Traffic Engineering and Control,1982,23:190-192.
[54]Martin P.T., Hockaday Stephen L.M.. SCOOT-An update [J]. Institute of Transportation Engineers, 1995,65(1):44-48.
[55]Wong Y.K., Woon W.L.. An iterative approach to enhanced traffic signal optimization [J]. Expert Systems with Applications,2008,34(4):2885-2890.
[56]Lowrie P.R.. SCATS principles, methodologies, algorithm [C]. IEEE Conference on Road Traffic Signal,1982:67-70.
[57]黄德双.神经网络模式识别系统理论[M].北京：电子工业出版社,1996：254-276.
[58]杨立才.道路交通智能控制策略的研究[D].济南：山东大学,2005：31-34.
[59]Amit K., Uday K., Chakraborty P.P.. Supervised learning on a fuzzy Petri net [J]. Information Sciences,2005,172:397-416.
[60]Pads A., Mastorocostas John B.T.. An orthogonal least-squares method for recurrent fuzzy-neural modeling [J]. Fuzzy Sets and Systems,2003, 140(2):285-300.
[61]孙海蓉.模糊神经网络的研究及其应用[D].北京：华北电力大学,2006：17-30.
[62]张文修,梁怡.遗传算法的数学基础[M].西安交通大学出版社.2000：23-36.
[63]李敏强,寇纪淞,林丹等.遗传算法的基本理论与应用[M].科学出版社.2002：12-34.
[64]周明,孙树栋.遗传算法原理及应用[M].国防工业出版社,1999：15-30.
[65]吴志远,邵惠鹤,吴新余.遗传退火进化算法[J].上海交通大学学报,1997,31(12)：69-72.
[66]王殿海.交通流理论[M].人民交通出版社,2002：7-28,60-77.
[67]丹尼尔L.鸠洛夫,马休J.休伯,蒋璜等.交通流理论[M].人民交通出版社,1983：86-115,184-224.
[68]王炜.交通规划[M].人民交通出版社,2007：56-75.
[69]Chen A., Subprasom K., JI Z.W.. Mean variance model for the build operate transfer scheme under demand uncertainty [J]. Transportation Research Record, 2003,1857:93-101.
[70]Chen A., Subprasom K.. Analysis of regulation and policy of private toll roads in a build operate transfer scheme under demand uncertainty [J]. Transportation Research A,2007,41(6):537-558.
[71]陆化普,蔚欣欣,卞长志.OD需求不确定的离散交通网络设计模型研究[J].公路交通科技,2011,28(5)：128-132.
[72]四兵锋,赵小梅,孙壮志.城市混合交通网络系统优化模型及其算法[J].中国公路学报,2008,21(1)：77-82.
[73]Chootinan P., Wong S.C., Chen A.. A reliability based network design problem [J]. Journal of Advanced Transportation, 2005,39(3):247-270.
[74]Sumalee A.,Watling D.P., Nakayama S.. Reliable network design problem:the case with uncertain demand and total travel time reliability [J]. Transportation Research Record,2006(1964):81-90.
[75]许良,高自友.基于路段能力可靠性的城市交通网络设计问题[J].中国公路学报,2006,19(2)：86-90.
[76]曾明华,李复苗.多层次多模式综合交通网络设计研究[J].交通运输系统工程与信息,2010,10(2)：23-29.
[77]张江华,陈克东,韩强.一种新的交通网络设计优化算法[J].运筹与管理,2007,16(3)：41-46.
[78]Chen M.Y., Alfa A.S.. A network design algorithm using a stochastic incremental traffic assignment approach [J]. Transportation Science,1991, 25(3):215-224.
[79]David G.A.. Exact local solution of the continuous network design problem via stochastic user equilibrium assignment [J]. Transportation Research B,1994, 28:61-75.
[80]Yang H., Bell M.G.. Transport bi-level programming problems:recent method logical advances [J]. Transportation Research B, 2001,35:1-4.
[81]Yang H., Bell M.G.. Traffic restraint, road pricing and network equilibrium [J]. Transportation Research B,1997,31:303-314.
[82]赵彤,高自友.交通离散网络设计与土地使用问题的组合模型及求解算法[J].土木工程学报,2003,36(1)：6-10.
[83]Gao Z.Y., Song Y.F.. A reserve capacity model of optimal signal control with user equilibrium route choice [J]. Transportation Research B, 2002, 36:313-323.
[84]Aldeek H.M., Emam E.B.. Computing travel time reliability in transportation networks with multi-states and dependent link failures [J]. Journal of Computing in Civil Engineering, 2006,20(5):317-327.
[85]李先,温慧敏,高永等.北京市路网单位距离行程时间可靠性评价[J].交通运输系统工程与信息,2007,7(2)：73-77.
[86]郭继孚,高永,温慧敏.基于替代路径的路网连通可靠性评价方法研究[J].公路交通科技,2007,24(7)：91-96.
[87]Chen A., Yang H., Hong K.L.. Capacity reliability of a road network:an assessment methodology and numerical results [J]. Transportation Research B, 2002,36:1-28.
[88]Uno N., Kurauchi F., Tamura H.. Using bus probe data for analysis of travel time variability [J]. Journal of Intelligent Transportation Systems,2009, 13(1):2-15.
[89]张勇,白玉,杨晓光.城市道路网络的行程时间可靠性[J].系统工程理论与实践,2009,29(8)：171-176.
[90]邓键.双层规划若干问题的解法[D].长春：吉林大学,2009：19-33.
[91]李和成.非线性双层规划问题的遗传算法研究[D].西安：西安电子科技大学,2009：20-35.
[92]Bard J., Moore J. A branch and bound algorithm for the bi-level programming problem [J]. Journal on Scientific and Statistical Computing,1990,11:281-292.
[93]Al Khayyal F.A., Horst R., Pardalos P.M.. Global optimization of concave functions subject to quadratic constraints:An application in nonlinear bi-level programming [J]. Annals of Operations Researeh,1992,34:125-147.
[94]Abdulaal M., Leblanc L.J.. Continuous equilibrium network design models [J]. Transportation Research B,1979,13:19-32.
[95]Bialas W., Karwan M.. Two level linear programming [J]. Management Seience, 1954,30:1004-1020.
[96]姜桂艳.道路交通状态判别技术与应用[M].人民交通出版社,2004：23-45.
[97]于春全,郭敏,梁玉庆.关于建立城市道路交通运行状况宏观评价系统的研究[J].道路交通与安全,2007,7(1)：1-6.
[98]皮晓亮,王正,韩皓等.基于环形线圈检测器采集信息的交通状态分类方法应用研究[J].公路交通科技,2006,23(4)：115-119.
[99]任江涛,欧晓凌,张毅等.交通状态模式识别研究[J].公路交通科技,2003,20(2)：63-67.
[100]张和生,张毅,胡东成等.区域交通状态分析的时空分层模型[J].清华大学学报(自然科学版),2007,47(1)：157-160.
[101]王伟,杨兆升,李贻武等.基于信息协同的子区交通状态加权计算与判别方法[J].吉林大学学报(工学版),2007,37(3)：524-527.
[102]Walinchus R.J.. Real time network decomposition and sub-network interfacing [R/CD]. Washington DC: Transportation Research Board, 1971:46-52.
[103]Yagoda N.H.. Subdivision of signal systems into control areas [J]. Traffic Engineering,1973,43(12):42-48.
[104]王学堂.城市交通信号整体优化理论的概念与方法[J].长安大学学报(自然科学版),2002,22(5)：90-92.
[105]高云峰.动态交叉口群协调控制基础问题研究[D].上海：同济大学2007：25-36.
[106]杨庆芳,陈林.交通控制子区动态划分方法[J].吉林大学学报(工学版),2009,36(增)：139-142.
[107]杨祖元.城市交通信号系统智能控制策略研究[D].重庆：重庆大学,2008：90-100.
[108]孔祥杰,沈国江,梁同海.具有公交优先的路网交通流智能协调控制研究[J].浙江大学学报(工学版),2009,43(6)：1026-1031.
[109]Wang D.H., Song X.M., Li F.. Research on offset optimization of signalized arterials [C]. Proceedings of the Fifth International Conference on Traffic and Transportation Studies,2006:584-594.
[110]李威武.城域智能交通系统中的控制与优化的问题研究[D].杭州：浙江大学2003：87-98.
[111]沈国江.城市区域交通智能分散控制研究[J].浙江大学学报(工学版),2006,40(4)：585-589.
[112]姜桂艳,李继伟,张春勤.城市主干路段行程时间估计的BPR修正模型[J].西南交通大学学报,2010,45(1)：124-130.
[113]Laudy M., Mees A.. Convergence of an annealing algorithm [J]. Mathematical Programming, 1986,34(1):111-124.
[114]刘伟铭,姜山.基于GASA混合优化策略的双层规划模型求解算法研究[J].土小工程学报,2003,36(7)：27-32.
[115]葛洪伟,王银年.求解VRPSDP问题的改进模拟退火遗传算法[J].计算机工程与应用,2010,46(30)：36-40.
[116]崔洪军.大型活动交通组织管理关键技术研究[D].南京：东南大学2006：1-9.
[117]赵佳琪,姜桂艳.大型活动的交通组织与管理研究[J].交通标准化,2009,6：60-63.
[118]赵晓辉,吴兵,董治,李林波.大型活动吣交通需求管理策略研究[J]. 现代交通技术,2009,6(1)：80-83.
[119]严新平,吕能超,刘正林.大型活动后车道单行优化的双层规划[J].西南交通大学学报,2009,44(1)：112-117.
[120]王素欣,王雷震,高利.BPR路阻函数的改进研究[J].武汉理工大学学报,2009,33(3)：446-449.