摘要
随着城市规模的不断膨胀,各类交通问题,诸如拥堵、效率低下等,日益突出,严重影响了城市道路交通系统的日常运行；城市道路交通系统中蕴含的问题为复杂系统理论和城市道路交通网络的研究提供了新的机遇与挑战。
城市道路交通系统的整体行为特征分析是该领域内研究的难点与重点之一这一问题映射到复杂系统理论研究层次即涌现行为的形成与演进过程的特征分析,映射到城市道路交通网络研究层次即网络动态拓扑特征分析。从不同的抽象层次思考城市道路交通中的各种问题能够使我们更清晰地认识到问题的本质和发展方向。
本文在深刻理解复杂系统定义与基本属性的基础上,对涌现作了较为清晰的描述,并对涌现形成和演进过程进行初步探讨,为理解复杂系统本质提供了一种新的框架；同时,为进一步研究复杂系统涌现行为形成和演进过程提供理论依据。本文指出系统行为在某个时段内受到系统状态空间中若干涌现吸引子的共同作用,正是这种联合作用使系统行为表现出了多个模态的特性,每个参与施加影响的吸引子都属于某一种独立的系统模态。在此基础上,本文进一步提出了基于多模态特征的复杂系统动态性建模方法,该方法将多模态联合作用的思想引入系统动态性建模,为研究复杂系统涌现行为的动态演进特征提供了一种新的理论指导；为具体应用领域的相关问题建模分析提供依据。
网络化模型是城市道路交通领域研究最常用的表达方式之一；同时,复杂网络是复杂系统领域相关研究重要分支之一。本文通过采用道路服务水平和交通不连通性等概念构建了具有可变结构的城市道路交通动态网络模型及其扩展模型,其中后者将道路交通状态的变化与网络拓扑变化紧密关联起来,使网络拓扑更完整地反映真实交通流网络的特性。基于北京市道路交通流数据的实验分析表明：城市道路交通网络具有三个基本模态：静态网络模态、随机网络模态和无标度网络模态,这三种基本模态分别定义了对应的系统行为的演进规律,即模态子动态性。城市道路交通系统行为的演进过程受到这三种模态的联合作用,在某个时段内因为产生较为主要的影响而被用于表征该时段内系统动态行为特征的被称为主模态。当主模态产生的影响占优觉得优势地位时,被称为单一作用模式；否则为联合作用模式；本文将模态的作用模式定义为七种,其中三个单一作用模式和四个联合作用模式。模态对系统行为的演进过程产生影响的程度通过模态相似性测度计算方法获得。
模态子动态性描述的目的是为了获得某时段网络行为受该模态作用而发生行为改变的程度。通过三种模态子动态性仿真演进,获得某时段三组仿真演进网络数据,包括节点度分布及平均节点度等,通过模态相似性计算公式,获得在任意时段内网络行为演进过程中各模态产生影响的程度,并以此来区分各模态的重要程度和模态的作用模式。
北京市道路交通网络为多模态动态性建模实验与分析提供了完整的数据支持；本文选取了具有代表性的五个时段作为考察对象进行了多模态动态性建模实验。北京市道路交通网络动态性建模与分析实验表明：北京市道路交通网络行为在一个以天为单位的周期内呈现出多个模态共同作用的特征；在全天的各时段内,主模态所定义的动态性基本能够描述北京市道路交通网络的行为特征；基于多模态特征的动态性建模方法能够将北京市道路交通网络任意时段内的网络行为通过量化的方法进行解析,并指出各时段的主模态、模态作用模式及主要行为特征,该方法所定义的动态性建模方法为以北京市道路交通网络为代表的城市道路交通网络的动态性建模及行为分析提供了建模与分析工具,同时该方法为分析复杂系统涌现行为的演进规律及动态特征提供了建模与描述工具。
With the rapid city development, various kinds problems emerging in urban road traffic systems, such as increasing jams etc., decrease the daily operation efficiency of urban road traffic systems. To solve those problems provides new issues for the research of complex system theory and urban road traffic networks.
The character analysis of the whole behavior of specific urban road traffic systems is one of the important and hot topics, which can be described as the analysis of the formation and evolving processes of emergent behavior in complex systems, and the analysis of topological dynamics in urban road traffic networks. It helps us to find the essential characteristics and the development trend of the problems in urban road traffic systems from the perspectives of different abstract level.
Complex system theory is and still will be for a long time an important issue in many specific research domains. Complex system theory aims at explaining the mechanisms and laws on which higher-level emergent phenomenon is generated by lower-level components and interactions among them. The critical point of the current research of complex systems is to understand complex systems and to formally define related concepts. Furthermore, emergence is the most intrinsic characteristics of complex systems. And understanding emergence is the main task in understanding complex systems.
In this dissertation, based on comprehensively understanding the basic character of complex systems, we define emergence and related concepts that explain the forming process of emergence. According to our thinking about the forming and evolving process, the multimode-based complex system dynamics modeling method is presented. The method determines the correlation coefficient of each system mode that is denoted by a corresponding emergence attractor at a time phase, by simulating system behavior evolving processes under each system mode's affection only. The multimode-based complex system dynamics modeling method provides a new promising approach to study the dynamic characteristics of the evolving process of emergent behavior in complex systems, but also a modeling and analyzing tool for specific systems.
As we known, large-scale urban road traffic systems are kind typical complex systems, including all research topics in complex system domain, and provide a platform for related study. The network-like models are always adopted in urban road traffic system domain; as well, complex network theory is often used in urban road traffic systems. As for network-like models, we introduce traffic level-of-service (LOS) described traffic states on roads, into urban road traffic networks to construct the variable-structure dynamic network model and the extended variable-structure dynamic network model. Based on the traffic data from the Beijing road traffic network, the structural dynamic characteristics of the extended variable-structure dynamic network model is validated; and the experiment shows that the model has three interindependent system modes:the static network mode, the stochastic network mode and the scale-free network mode. The three system modes define the corresponding evolving mechanisms of system behavior respectively, also called sub-dynamics.The modes'functioning patterns are concluded into two classes:the single pattern and the union pattern. Therefore, we construct the sub-dynamics models of the three system modes, according to which the evolving processes under three modes can be achieved respectively. In the correlation coefficient equation, the average node degree and the scaling exponent of node degree distribution are considered.
In this dissertation, we select five time phases for the urban road traffic network dynamics modeling and analyzing experiments based on the real traffic data from the Beijing road traffic network. The experimental results show that the Beijing road traffic network has the multimode feature in a 24h time cycle; the major mode can characterize the Beijing road traffic network at each time phase; the multimode-based dynamics modeling method can quantitatively analyze the behavior of urban road traffic network, and point out the major mode and the mode functioning pattern.
In conclusion, the multimode-based complex system dynamics modeling and analyzing method provides a new tool to both dynamics modeling of urban road traffic networks and evolving mechanism analysis of emergent behavior in complex systems.
引文
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