弹性需求下的网络交通流逐日动态演化

在现实交通系统中,网络的交通需求是可变的,随交通运行状态而改变.针对需求可变情形,以含两条路径的简单路网为例,建立了弹性需求下的网络交通流逐日动态演化模型,基于非线性动力学理论,证明了动态演化模型的不动点存在且唯一,并且推导出了弹性需求下网络交通流动态演化的稳定性条件.通过数值实验,分析了网络交通流演化特征.研究发现:在一定条件下流量演化会出现分岔和混沌现象,并且出行者的出行需求对费用越敏感,系统演化越可能稳定;出行者路径选择的随机性越小,系统演化越不可能稳定;出行者对前一天实际费用的依赖程度越小,系统演化越可能稳定.     

有限理性视野下网络交通流逐日演化规律研究

基于有限理性的前提假设,建立了"有限理性二项logit"模型,用以描述出行者路径选择行为,并以一个由2条路径构成的路网为例,探讨了理性程度不同群体的网络交通流逐日动态演化过程,通过数值实验,分析了网络交通流的演化特征,发现网络交通流演化最终状态除了与出行者群体对费用的敏感程度、对实际费用的依赖程度有关,还与出行者群体的理性程度有很大关系.在一定的情况下,出行者理性程度很高或很低均可以使系统稳定,而恰恰是理性程度一般的群体不容易达到稳定.     

短时交通流复杂动力学特性分析及预测

为揭示短时交通流的内在动态特性,利用非线性方法对交通流混沌特性进行识别,为短时交通流的预测提供基础.基于混沌理论对交通流时间序列进行相空间重构,利用C-C算法计算时间延迟和嵌入维数,采用Grassberger-Procaccia算法计算吸引子关联维数,通过改进小数据量法计算最大Lyapunov指数来判别交通流时间序列的混沌特性.针对局域自适应预测方法在交通流多步预测中预测器系数无法调节的问题,提出了交通流多步自适应预测方法.通过实测数据计算,结果表明:2,4和5 min三种统计尺度的交通流时间序列均具有混沌特性;改进的小数据量法能够准确地计算出最大Lyapunov指数;构建的交通流多步自适应预测模型能够有效地预测交通流量的变化.为智能交通系统诱导和控制提供了依据.     

基于自适应斜坡补偿的双环电流模DC/DC混沌控制

提出了一种自适应斜坡补偿方法,将该方法引入到双环电流模buckDC/DC的混沌控制中,并给出实现该方法的电路结构.建立了双环电流模DC/DC系统稳定性分析的离散模型,理论分析了自适应斜坡补偿在双环控制下系统的稳定性条件,推导出了自适应因子k与系统工作的最大占空比的关系式.仿真结果表明该方法可有效控制系统的分岔和混沌现象,提高系统的工作范围和动态响应速度.     

环形腔中激光振荡输出的横向斑图及向光学湍流的转变

在研究环形腔中激光振荡输出的分岔与混沌的基础上,采用耦合映象格子模型研究了其空间扩展系统的横向效应.数值模拟表明,随着参数的改变,空间扩展系统由均匀稳态、行波解向时空混沌演化.在一定的参数条件下,空间扩展系统从光场取入射平面波(均匀分布)开始,经对称破缺向光学湍流转变. 关键词： 横向斑图 时空混沌 湍流 数值模拟     

机动车协商模型与分岔特性研究

在环行交叉路口交通流中, 由于行驶目的的不同存在三种类型冲突. 为了真实模拟人类的自治性和智能性, 先将机动车建立为一个含有驾驶员模型的智能体, 再耦合环行交叉口的元胞自动机模型组成多智能体系统. 在总结每种类型交通冲突特点和规律的基础上, 提出通过优先级策略和动态协商机制消解机动车智能体相互之间的冲突问题. 以某中小城市城的典型环行交叉路口交通流量为样本数据, 对比验证模型的正确性, 并且进一步研究了交通流的分岔特性, 发现一定条件下流量的周期分岔和混沌现象. 数值模拟结果表明, 所建模型符合实际情况, 并且内环发生冲突越严重车流量越低, 随着机动车属性参数k和p的变化, 系统从稳定走向分岔再到混沌. 关键词： 多智能体 元胞自动机 协商 分岔     

基于自适应斜坡补偿的双环电流模DC/DC混沌控制

提出了一种自适应斜坡补偿方法,将该方法引入到双环电流模buck DC/DC的混沌控制中,并给出实现该方法的电路结构.建立了双环电流模DC/DC系统稳定性分析的离散模型,理论分析了自适应斜坡补偿在双环控制下系统的稳定性条件,推导出了自适应因子k与系统工作的最大占空比的关系式.仿真结果表明该方法可有效控制系统的分岔和混沌现象,提高系统的工作范围和动态响应速度.     

弯道交通流跟驰建模与稳定性分析

为发现弯道道路条件下交通流的演化特性及稳定条件,在全速度差最优模型的基础上,研究了弯道情况下的交通流跟驰模型表达式,并以状态空间法和控制系统的稳定性判据对其进行了稳定性分析,得到弯道情况下交通流的稳定条件,最后进行了数值模拟,验证了模型稳定条件的正确性.研究结果表明在相同的初始交通流密度情况下,弯道道路随着道路弧度的增大,交通流稳定性逐渐降低.     

环形加权网络的时空混沌延迟同步

研究了环形加权网络的时空混沌延迟同步问题.以随时间和空间演化均呈现混沌行为的时空混沌系统作为网络的节点,通过环形加权连接使所有节点建立关联.基于线性稳定性定理,通过确定网络的最大Lyapunov指数,得到了实现网络延迟同步的条件.在最大Lyapunov指数小于零的区域内,任取节点之间耦合强度的权重值,均可以使整个网络实现延迟同步.采用具有时空混沌行为的自催化反应扩散系统作为网络节点,仿真模拟验证了该方法的有效性. 关键词： 延迟同步 加权网络 时空混沌 Lyapunov指数     

Chua混沌系统的一种模糊控制器设计——LMI法

研究了Chua混沌系统的稳定控制问题.采用模糊动态模型逼近非线性混沌系统,将非线性混沌系统模糊化为局部线性模型.用Lyapunov稳定性理论设计出,确保模糊动态模型全局渐近稳定的控制器.再用线性矩阵不等式的凸优化方法求出模糊控制器的参数.仿真验证了方案的有效性.模糊控制器简单,规则少. 关键词： Chua混沌系统 模糊动态模型 线性矩阵不等式     

Behaviours in a dynamical model of traffic assignment with elastic demand

This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.     

日常择路行为的多智能体模拟

日常路径选择是一个长期的、多体参与的非合作博弈过程.基于多智能体环境，对交通信息公开和不公开两种路径更新规则进行了模拟研究，结果表明，信息公开比不公开能够使路径流量更快地演化到logit随机用户均衡状态，但若对信息的依赖程度过大，则可能导致系统振荡；出行者完全依靠自身经验完成路径选择也可以使系统演化至稳定态，但代价是演化效率太低.因此，既要公开交通信息，又要注意合理使用信息.     

The Stability of Multi-modal Traffic Network

There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion.     

The Stability of Multi-modal Traffic Network

There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion.     

Dynamics of Transiently Chaotic Neural Network and Its Application to Optimization

Through adding a nonlinear self-feedback term in the evolution equations of nerual network,we introduced a transiently chaotic neural network model.In order to utilize the transiently chaotic dynamics mechanism in optimization problem efficiently,we have analyzed the dynamical pocedure of the transiently chaotic neural network model and studied the function of the crucial bifurcation parameter which governs the chaotic behavior of the system.Based on the dynamical analysis of the transiently chaotic neural network model,Chaotic annealing algorithm is also examined and improved.As an example,we applied chaotic annealing method to the traveling salesman problem and obtained good results.     

Scale-Free Properties in Traffic System

In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model. The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution (i.e., the scale-free distribution) and random distribution etc.     

Scale-Free Properties in Traffic System

In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution （i.e., the scale-free distribution） and random distribution etc.     

基于一阶广义忆阻器的文氏桥混沌振荡器研究

通过在文氏桥振荡器中引入广义忆阻器和LC吸收网络,提出了一种忆阻文氏桥混沌振荡器.建立了忆阻文氏桥混沌振荡器的动力学模型,研究了它的平衡点和稳定性,进一步开展了电路元件参数变化时的动力学行为分析.研究发现,忆阻文氏桥混沌振荡器有3个确定的平衡点,其稳定性取决于电路元件参数,当参数发生变化时,存在周期振荡、混沌振荡、快慢效应等复杂的非线性现象.实验电路简单易制作,实验波形和数值仿真一致,较好地验证了理论分析结果.     

Network Traffic Anomaly Detection Method Based on a Feature of Catastrophe Theory

For the existing problems of current network traffic anomaly detection, the behavior of the network traffic anomaly will show nonlinearity, non-stationarity and complexity according to the network traffic often driven by the control of multiple factors. Owing to the characteristic that the internal evolution equation will lead to dynamical structure catastrophe, the phase space reconstruction method and the statistical physics method can be used to compute the macro feature values of the network traffic. By choosing some of the feature values which can obviously retlect the unusual change in the network traffic volume as control variables, a network traffic anomaly detection method based on the catastrophe series theory model is developed. Many experimental results show that the proposed network traffic anomaly detection method has a low false alarm rate under the same condition of detection rate.